Methods are provided to improve the positive predictive value for cancer detection using cell-free nucleic acid samples. Various embodiments are directed to applications (e.g., diagnostic applications) of the analysis of the fragmentation patterns and size of cell-free DNA, e.g., plasma DNA and serum DNA, including nucleic acids from pathogens, including viruses. Embodiments of one application can determine if a subject has a particular condition. For example, a method of present disclosure can determine if a subject has cancer or a tumor, or other pathology. Embodiments of another application can be used to assess the stage of a condition, or the progression of a condition over time. For example, a method of the present disclosure may be used to determine a stage of cancer in a subject, or the progression of cancer in a subject over time (e.g., using samples obtained from a subject at different times).
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12Q 1/686 - Réaction en chaine par polymérase [PCR]
C12Q 1/70 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des virus ou des bactériophages
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
G16B 20/10 - Ploïdie ou détection du nombre de copies
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
A predictive cancer model generates a cancer prediction for an individual of interest by analyzing values of one or more types of features that are derived from cfDNA obtained from the individual. Specifically, cfDNA from the individual is sequenced to generate sequence reads using one or more physical assays, examples of which include a small variant sequencing assay, whole genome sequencing assay, and methylation sequencing assay. The sequence reads of the physical assays are processed through corresponding computational analyses to generate each of small variant features, whole genome features, and methylation features. The values of features can be provided to a predictive cancer model that generates a cancer prediction. In some embodiments, the values of different types of features can be separately provided into different predictive models. Each separate predictive model can output a score that can serve as input into an overall model that outputs the cancer prediction.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
3.
Cancer Classification with Tissue of Origin Thresholding
Methods and systems for detecting cancer and/or determining a cancer tissue of origin are disclosed. In some embodiments, a multiclass cancer classifier is disclosed that is trained with a plurality of biological samples containing cfDNA fragments. The analytics system derives a feature vector for each sample, and the multiclass classifier predicts a probability likelihood for each of a plurality of tissue of origin (TOO) classes. In some embodiments, the plurality of TOO classes include hematological subtypes, including both hematological malignancies and precursor conditions. In one embodiment, non-cancer samples having high tissue signal are pruned from the training sample set. In another embodiment, the analytics system stratifies samples according to tissue signal and applies binary threshold cutoffs determined for each stratum.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 20/10 - TIC spécialement adaptées aux thérapies ou aux plans d’amélioration de la santé, p. ex. pour manier les prescriptions, orienter la thérapie ou surveiller l’observance par les patients concernant des médicaments ou des médications, p. ex. pour s’assurer de l’administration correcte aux patients
G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
4.
SYSTEMS AND METHODS FOR CONSTRUCTING AND UTILIZING A PLASMA CELL DISORDER CLASSIFIER TO PERFORM INFORMED FEATURE ANALYSIS
A computer-implemented method for characterizing disease progression is provided. The computer-implemented method may include: receiving, at a computing device, a set of nucleic acid methylation data; receiving, at the computing device, a designation of one or more genomic regions; generating, using a processor of the computing device, a trajectory of disease progression; identifying, using the processor and within the set of nucleic acid methylation data, one or more temporal methylation features associated with progression along the trajectory; and mapping, using the processor, the one or more temporal methylation features to the one or more genomic regions.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
5.
SOURCE OF ORIGIN DECONVOLUTION BASED ON METHYLATION FRAGMENTS IN CELL-FREE DNA SAMPLES
A method and system for determining one or more sources of a cell free deoxyribonucleic acid (cfDNA) test sample from a test subject. The cfDNA test sample contains a plurality of deoxyribonucleic acid (DNA) molecules with numerous CpG sites that may be methylated or unmethylated. A trained deconvolution model comprises a plurality of methylation parameters, including a methylation level at each CpG site for each source, and a function relating a sample vector as input and a source of origin prediction as output. The method generates a test sample vector comprising a site methylation metric relating to DNA molecules from the test sample that are methylated at that CpG site. The method inputs the test sample vector into the trained deconvolution model to generate a source of origin prediction indicating a predicted DNA molecule contribution of each source.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
Detecting cross-contamination between test samples used for determining cancer in a subject is beneficial. To detect cross-contamination, test sequences including at least one single nucleotide polymorphism are prepared using genome sequencing techniques. Some of the test sequences can be filtered to improve accuracy and precision. A prior contamination probability for each test sequence is determined based on a minor allele frequency. A contamination model including a likelihood test is applied to a test sequence. The likelihood test obtains a current contamination probability representing the likelihood that the test sample is contaminated. The contamination model can also determine a likelihood that the sample includes loss of heterozygosity representing the likelihood that the test sequence is contaminated. Test samples that are contaminated are removed. A source for the contaminated test sample can be found by comparing contaminated test sequences to other test sequences.
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
G16B 30/10 - Alignement de séquenceRecherche d’homologie
A method for training a convolutional neural net for contamination analysis is provided. A training dataset is obtained comprising, for each respective training subject in a plurality of subjects, a variant allele frequency of each respective single nucleotide variant in a respective plurality of single nucleotide variants, and a respective contamination indication. First and second subsets of the plurality of training subjects have first and second contamination indication values, respectively. A corresponding first channel comprising a first plurality of parameters that include a respective parameter for a single nucleotide variant allele frequency of each respective single nucleotide variant in a set of single nucleotide variants in a reference genome is constructed for each respective training subject. An untrained or partially trained convolutional neural net is trained using, for each respective training subject, at least the corresponding first channel of the respective training subject as input against the respective contamination indication.
Systems and methods for estimating tumor fraction in a biological sample are disclosed. One method may include: receiving sequencing data for each of a plurality of biological samples included on a combined targeted sequencing panel, wherein the sequencing data for each of the plurality of biological samples includes: genetic variant sequencing data covering one or more genetic variants of each of the plurality of biological samples; and background sequencing data covering all other genetic variants from all of the other biological samples; calculating, from the background sequencing data associated with each of the plurality of biological samples, a site-specific error rate for each genomic location associated with each of the one or more genetic variants; and establishing, based on the calculated site-specific error rate, a threshold for tumor fraction estimation for each of the one or more genetic variants. Other aspects are described and claimed.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
In an automated liquid processing system, a first centrifuge performs a centrifuging cycle on a plurality of first inserts, a pairing robot to places first tubes, including pairs of first tubes, from the first inserts on a pairing platform, an excising station excises labels on the first tubes, captures an image of the excised first tubes, and determines, using an image analysis process, a height of a portion of the liquid within the first tubes. A first liquid handling station combines a portion of the liquid within first tubes, including pairs of first tubes, into a second tube. A second centrifuge performs a second centrifuging cycle, and a second liquid handling station aspirates liquid from the second tube and dispenses the liquid into an output container.
G01N 21/25 - CouleurPropriétés spectrales, c.-à-d. comparaison de l'effet du matériau sur la lumière pour plusieurs longueurs d'ondes ou plusieurs bandes de longueurs d'ondes différentes
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
In an automated liquid processing system, a first centrifuge performs a centrifuging cycle on a plurality of first inserts, a pairing robot to places first tubes, including pairs of first tubes, from the first inserts on a pairing platform, an excising station excises labels on the first tubes, captures an image of the excised first tubes, and determines, using an image analysis process, a height of a portion of the liquid within the first tubes. A first liquid handling station combines a portion of the liquid within first tubes, including pairs of first tubes, into a second tube. A second centrifuge performs a second centrifuging cycle, and a second liquid handling station aspirates liquid from the second tube and dispenses the liquid into an output container.
Systems and methods of the disclosure may include a computer-implemented method, the computer-implemented method may include: receiving, at a system, a source dataset comprising a first set of data samples; receiving, at the system, a target dataset comprising a second set of data samples; performing, using a processor, feature extraction on the source dataset and the target dataset to obtain a first set of features associated with the source dataset and a second set of features associated with the target dataset; computing, via employing a non-parametric importance-weighting technique, importance weights for each of the first set of data samples and the second set of data samples; assigning the computed importance weights to each of the first set of data samples and the second set of data samples; and training a diagnostic classifier using the importance-weighted first set of data samples and the importance-weighted second set of data samples.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
12.
SYSTEMS AND METHODS TO IDENTIFY CLONAL HEMATOPOIESIS RELATED METHYLATION SIGNATURES
Systems and methods of the disclosure may include a computer-implemented method, the computer-implemented method may include: receiving, at a computing device, a set of nucleic acid methylation data; receiving, at the computing device, a designation of one or more genomic regions; identifying, using a process of the computing device and within the set of nucleic acid methylation data, one or more abnormal methylation features; and mapping, using the processor, the one or more abnormal methylation features to the one or more genomic regions. Other aspects are described and claimed.
In various aspects, the present disclosure provides methods for the modification and purification of nucleic acid, e.g., DNA molecules, as well as methods for nucleic acid extraction for further processing or analysis. Also provided are methods for performing a bisulfite conversion reaction on nucleic acid molecules, and performing subsequent desulfonation and purification steps facilitated by a substrate (e.g., magnetic beads) for the purification and recovery of converted nucleic acid molecules. Methods for the separation of nucleic acids, e.g., DNA, from other components of a biological sample are also provided.
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12N 15/10 - Procédés pour l'isolement, la préparation ou la purification d'ADN ou d'ARN
C12Q 1/68 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des acides nucléiques
14.
Methods of Preparing Dual-Indexed DNA Libraries for Bisulfite Conversion Sequencing
Described herein are methods of preparing dual-indexed nucleic acid libraries for methylation profiling using bisulfite conversion sequencing. In various embodiments, the methods use a two-step indexing process to tag bisulfite-treated DNA with unique molecular identifiers (UMIs).
Systems and methods of the disclosure may include receiving, at a computing device, a first set of nucleic acid methylation data and a second set of nucleic acid methylation data, wherein the first set of nucleic acid methylation data is associated with a pre-treatment sample and wherein the second set of nucleic acid methylation data is associated with a post-treatment sample. The method may include comparing, using a processor of the computing device, a first feature set of the first set of nucleic acid methylation data against a second feature set of the second set of nucleic acid methylation data; determining, based on the comparing, at least one treatment affected feature in the second feature set of the second set of nucleic acid methylation data; and implementing, based on the determining, an exclusion process on the at least one treatment affected feature in the second feature set.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
16.
SYSTEMS AND METHODS FOR SYNTHETIC DATA TITRATION FOR DATA AUGMENTATION
Systems and methods for generating synthetic data may include receiving an indication to generate a synthetic data set having characteristics associated with a designated tumor methylation fraction; identifying, based on the received indication, a first data set associated with a real cancer sample and a second data set associated with a real non-cancer sample; determining, based on the designated tumor methylation fraction, a first proportion of the first data set to combine with a second proportion of the second data set; selecting, based on the determining, a first subset of the first data set that corresponds to the first proportion and a second subset of the second data set that corresponds to the second proportion; and generating, using the processor, at least one synthetic data sample in the synthetic data set by combining the first subset of the first data set with the second subset of the second data set.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
17.
SYSTEMS AND METHODS FOR ASSESSING SIMILARITY BETWEEN SAMPLES USING GENOTYPE SIGNATURES
Systems and methods for verifying the similarity between biological samples are disclosed. One method may include: receiving genomic data associated with a first sample from a participant; generating a numerical representation for each single nucleotide polymorphism (SNP) in the genomic data that satisfy predetermined criteria, wherein a value of each numerical representation is based on an allele characteristic associated with each of the SNPs; assembling the numerical representation for each of the SNPs into a first genotype signature associated with the first sample; comparing the first genotype signature associated with the first sample to a second genotype signature associated with a second sample; and identifying a sample match or a sample mismatch based on the comparing. Other aspects are described and claimed.
Methods for cancer source of origin (CSO) prediction are disclosed to predict CSO characteristics. The CSO prediction may include the affected organ or organ group and tumor biology. The method for training parallel CSO classifiers includes obtaining training samples derived from subjects with known cancer diagnosis, each training sample comprising methylation sequence reads corresponding to nucleic acid fragments in a biological sample collected from each subject and each known cancer signal origin including a known affected organ or organ group a plurality of organs or organ groups and a known tumor biology from a plurality of tumor biology classes. The method includes generating, for each training sample, a feature vector based on the methylation sequence reads. The method includes generating a first training data set comprising the feature vectors for the training samples and the known organs or organ groups, and training an organ or organ group classifier with the first training data set to predict organ or organ group from the plurality of organs or organ groups based on an input feature vector. The method includes generating a second training data set comprising the feature vectors for the training samples and the known tumor biology classes, and training a tumor biology classifier with the second training data set to predict tumor biology from the plurality of tumor biology classes based on input feature vector.
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
19.
PARALLEL CANCER SOURCE OF ORIGIN CLASSIFICATION FOR ORGAN TYPE AND TUMOR BIOLOGY TYPE
Methods for cancer source of origin (CSO) prediction are disclosed to predict CSO characteristics. The CSO prediction may include the affected organ or organ group and tumor biology. The method for training parallel CSO classifiers includes obtaining training samples derived from subjects with known cancer diagnosis, each training sample comprising methylation sequence reads corresponding to nucleic acid fragments in a biological sample collected from each subject and each known cancer signal origin including a known affected organ or organ group a plurality of organs or organ groups and a known tumor biology from a plurality of tumor biology classes. The method includes generating, for each training sample, a feature vector based on the methylation sequence reads. The method includes generating a first training data set comprising the feature vectors for the training samples and the known organs or organ groups, and training an organ or organ group classifier with the first training data set to predict organ or organ group from the plurality of organs or organ groups based on an input feature vector. The method includes generating a second training data set comprising the feature vectors for the training samples and the known tumor biology classes, and training a tumor biology classifier with the second training data set to predict tumor biology from the plurality of tumor biology classes based on input feature vector.
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
Systems and methods for differentiating between somatic and germline variants using a single biological sample are disclosed. One method may include: receiving, at a computer system and from a genotyping workflow performed on a biological sample, genotype data for a plurality of variants identified in a sequence of the biological sample; receiving, at the computer system and from an orthogonal assay workflow performed on the biological sample, tumor fraction data; providing, as input to a multinomial model, the genotype data and the tumor fraction data; and receiving, from the multinomial model, output that identifies a first portion of the plurality of variants as germline. variants, and a second portion of the plurality of variants as somatic variants.
Various applications can use fragmentation patterns related of cell-free DNA, e.g., plasma DNA and serum DNA. For example, the end positions of DNA fragments can be used for various applications. The fragmentation patterns of short and long DNA molecules can be associated with different preferred DNA end positions, referred to as size-tagged preferred ends. In another example, the fragmentation patterns relating to tissue-specific open chromatin regions were analyzed. A classification of a proportional contribution of a particular tissue type can be determined in a mixture of cell-free DNA from different tissue types. Additionally, a property of a particular tissue type can be determined, e.g., whether a sequence imbalance exists in a particular region for a tissue type or whether a pathology exists for the tissue type.
The present disclosure relates to a method for designing an optimized targeted sequencing panels. In one aspect, the method includes assessing whether the optimized targeted sequencing panel produces a limit of detection below a threshold.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
The present disclosure relates to a method for improving tumor fraction estimation by identifying and excluding variants having outlier allele fractions. For example, the methods described herein include assessing, for each identified somatic variant, an allele fraction, wherein if the allele fraction for the identified somatic variant significantly deviates from the current shedding rate the identified somatic variant is excluded from a TF estimation.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
24.
METHODS AND COMPOSITIONS FOR ANALYSIS OF CELL-FREE BIOMARKERS
In various aspects, the present disclosure provides methods for detection of various cancer types, comprising measuring the level of target molecules in a sample. In some embodiments, the one or more target molecules include a cell-free DNA (cfDNA) from a plurality of different target genomic regions that are differentially methylated in at least one of a plurality of cancer, and a plurality of different polypeptides that are differentially expressed in at least one of the plurality of cancer types. Methods for training a classifier for detecting target molecules from a cancer are also provided.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G01N 33/53 - Tests immunologiquesTests faisant intervenir la formation de liaisons biospécifiquesMatériaux à cet effet
Techniques are provided for analyzing circular DNA in a biological sample (e.g., including cell-free DNA, such as plasma). For example, to measure circular DNA, cleaving can be performed to linearize the circular DNA so that they may be sequenced. Example cleaving techniques include restriction enzymes and transposases. Then, one or more criteria can be used to identify linearized DNA molecules, e.g., so as to differentiate from linear DNA molecules. An example criterion is mapping a pair of reversed end sequences to a reference genome. Another example criterion is identification of a cutting tag, e.g., associated with a restriction enzyme or an adapter sequence added by a transposase. Once circular DNA molecules (e.g., eccDNA and circular mitochondrial DNA) are identified, they may be analyzed (e.g., to determine a count, size profile, and/or methylation) to measure a property of the biological sample, including genetic properties and level of a disease.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/10 - Ploïdie ou détection du nombre de copies
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/10 - Alignement de séquenceRecherche d’homologie
The present disclosure describes techniques for measuring quantities (e.g., relative frequencies) of sequence end motifs of cell-free DNA fragments in a biological sample of an organism for measuring a property of the sample (e.g., fractional concentration of clinically-relevant DNA) and/or determining a condition of the organism based on such measurements. Different tissue types exhibit different patterns for the relative frequencies of the sequence end motifs. The present disclosure provides various uses for measures of the relative frequencies of sequence end motifs of cell-free DNA, e.g., in mixtures of cell-free DNA from various tissues. DNA from one of such tissue may be referred to as clinically-relevant DNA.
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/10 - Ploïdie ou détection du nombre de copies
G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
27.
CANCER CLASSIFICATION WITH CANCER SIGNAL OF ORIGIN THRESHOLDING
Methods and systems for detecting cancer and/or determining a cancer tissue of origin are disclosed. In some embodiments, a multiclass cancer classifier is disclosed that is trained with a plurality of biological samples containing cfDNA fragments. The analytics system derives a feature vector for each sample, and the multiclass classifier predicts a probability likelihood for each of a plurality of cancer signal origin (CSO) classes. In some embodiments, the plurality of CSO classes include hematological subtypes, including both hematological malignancies and precursor conditions. In one embodiment, non-cancer samples having high prediction score are pruned from the training sample set. In another embodiment, the analytics system stratifies samples according to prediction score and applies binary threshold cutoffs determined for each stratum.
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
Aspects of the invention relate to methods for tracking patient health by longitudinally tracking genetic variants in patients, such that it is possible to provide a tumor, or mutation, classification signature. Longitudinal tracking improves the ability to detect minimal residual disease (MRD; the small number of cells that remain in the patient after treatment and/or during remission) and/or treatment response at an early stage, both of which can help guide treatment decisions and guard against missing different intra-/inter-tumor responses in a patient.
G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 25/00 - TIC spécialement adaptées à l’hybridationTIC spécialement adaptées à l’expression de gènes ou de protéines
G16B 25/10 - Profilage de l’expression de gènes ou de protéinesEstimation ou normalisation de ratio d’expression
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
The present disclosure relates to a method for improving sequencing panel assignments for samples from two or more individual. The system is configured to generate a sequencing panel assignment having an optimized set of samples for each panel that reduces sequencing costs but does not compromise Limit of Detection of the assay.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
C12Q 1/6809 - Méthodes de détermination ou d’identification des acides nucléiques faisant intervenir la détection différentielle
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
30.
METHODS FOR ANALYSIS OF CELL-FREE NUCLEIC ACIDS IN URINE
In various aspects, the present disclosure provides methods, compositions, reactions mixtures, kits, and systems for analysis of cell-free nucleic acid molecules (e.g., cfRNA and/or cfDNA) from a urine sample. In some embodiments, the analysis is an analysis of methylation patterns in target genomic regions among cfDNA fragments in a urine sample. In some embodiments, compositions include a plurality of different bait oligonucleotides. Methods for the detection of cancer of various cancer types are also provided.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
A61K 45/06 - Mélanges d'ingrédients actifs sans caractérisation chimique, p. ex. composés antiphlogistiques et pour le cœur
C12N 15/10 - Procédés pour l'isolement, la préparation ou la purification d'ADN ou d'ARN
C12Q 1/34 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir une hydrolase
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12Q 1/6809 - Méthodes de détermination ou d’identification des acides nucléiques faisant intervenir la détection différentielle
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
Provided herein are compositions comprising tissue-specific markers for identifying a tissue of origin of a cell-free nucleic acid, e.g., a cell-free DNA molecule. Also provided herein are methods, compositions, and systems for identifying a tissue of origin of a cell-free nucleic acid by determining an absolute amount of cell-free nucleic acids comprising the tissue-specific marker. Also provided herein are methods, compositions, and systems for detecting a cancer in a tissue of an organism by analyzing tissue-specific markers.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
32.
SYSTEMS AND METHODS FOR PERFORMING METHYLATION-BASED RISK STRATIFICATION FOR MYELODYSPLASTIC SYNDROMES
Systems and methods for predicting survival outcomes in patients diagnosed with Myelodysplastic Syndrome (MDS) are disclosed. One method may include: receiving DNA sequencing data derived from a methylation assay performed on a biological sample associated with the at least one patient; computing methylation beta-values for one or more CpG-sites identified in the sequencing data; identifying one or more differentially methylated regions (DMRs) based on statistical analysis of the methylation beta-values for the one or more CpG-sites; selecting, via a feature selection process, a subset of the one or more DMRs to utilize as training data; and training, using the training data, the classifier to predict the survival outcome of the at least one patient. Other aspects are described and claimed.
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
33.
METHYLATED DNA FRAGMENT ENRICHMENT, METHODS, COMPOSITIONS AND KITS
A method of processing an input sample, as well as related kits and compositions, is provided herein. In various instances, the disclosure relates to providing an input sample comprising nucleic acid fragments, wherein in at least a portion of the nucleic acid fragments each fragment comprises one or more methylated cytosines; converting unmethylated cytosines of nucleic acid fragments of the input sample to uracils, yielding converted fragments; copying the converted fragments using a mixture of nucleotides, the mixture comprising a mixture of: binding moiety-modified cytosines and binding moiety-lacking cytosines; binding moiety-modified guanines and binding moiety-lacking guanines; or binding moiety-modified cytosines, binding moiety-lacking cytosines, binding moiety-modified guanines, and binding moiety-lacking guanines; wherein the copying yields a mixture of binding moiety-modified fragments and unmodified fragments which may be separated to provide a set of fragments enriched for hypermethylated fragments.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
34.
Methylation markers and targeted methylation probe panel
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
G16B 25/20 - Réaction en chaîne par polyméraseConception d’amorces ou de sondesOptimisation de la sonde
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C40B 20/00 - Procédés spécialement adaptés à l'identification des éléments d'une bibliothèque
C40B 40/08 - Bibliothèques comprenant de l'ARN ou de l'ADN codant des protéines, p. ex. bibliothèques de gènes
36.
Convolutional neural network systems and methods for data classification
Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
37.
SYSTEMS AND METHODS FOR DETECTING DISEASE SUBTYPES
Systems and methods for detecting a subtype of a disease state and for determining the development of a resistance mechanism in a disease are disclosed. One method may include: receiving, at an input component of the system, a set of sequence reads associated with a nucleic acid sample; generating, using a processor of the system and via analysis of the set of sequence reads, methylation data; and analyzing, using the processor, the methylation data to identify the subtype of the disease state. Another method may include: obtaining methylation data from a targeted methylation sequencing assay, applying the methylation data to a trained machine learning model, and receiving an output indicating whether MRD is present in a test subject and/or whether a resistance mechanism has been developed by a disease. Other aspects are described and claimed.
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
G16H 50/50 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour la simulation ou la modélisation des troubles médicaux
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
42 - Services scientifiques, technologiques et industriels, recherche et conception
44 - Services médicaux, services vétérinaires, soins d'hygiène et de beauté; services d'agriculture, d'horticulture et de sylviculture.
Produits et services
Scientific and medical research services; providing information in the field of genetics and cancer for medical or scientific research via an online database; providing temporary use of on-line non-downloadable software and applications for use in studying, diagnosing or screening for cancer and studying genetics and DNA; providing temporary use of on-line non-downloadable cloud computing software for use in studying, diagnosing or screening cancer and studying genetics and DNA; software as a service (SaaS) services featuring software in the nature of a platform for genetic and bioinformatics analysis. Genetic testing and reporting for medical purposes; medical testing for diagnostic or treatment purposes; medical screening; medical diagnostic testing, monitoring and reporting services; providing medical information regarding genetics via a website; genetic analysis and reporting services for medical purposes.
Various embodiments are directed to detecting infection-causing microbial cell-free DNA from a biological sample based on their size profiles and/or end signatures, in which the detection of infection-causing microbial DNA can be performed without no template control (NTC) samples. Embodiments can include identifying the infection-causing pathogen-derived microbial DNA based on sizes of microbial cell-free DNA molecules. Embodiments can also include identifying from the infection-causing pathogen-derived microbial DNA based on end signatures of microbial cell-free DNA molecules. Embodiments can also include applying a machine-learning algorithm to a plurality of vectors that represent end signatures of the microbial cell-free DNA molecules, to identify the infection-causing pathogen-derived microbial DNA. By detecting the infection-causing pathogen-derived microbial DNA, a level of infection for the biological sample can be predicted.
C12Q 1/6888 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour la détection ou l’identification d’organismes
G16B 30/10 - Alignement de séquenceRecherche d’homologie
C12Q 1/686 - Réaction en chaine par polymérase [PCR]
C12Q 1/6809 - Méthodes de détermination ou d’identification des acides nucléiques faisant intervenir la détection différentielle
40.
METHODS AND SYSTEMS FOR ANALYZING NUCLEIC ACID SEQUENCES
Methods of identifying changes in genomic DNA copy number are disclosed. This disclosure provides methods for detecting chromosomal aberrations in a subject using Hidden Markov modeling. In some cases, methods provided herein use de novo sequence assembly to detect chromosomal aberrations in a subject. The methods can be used to detect copy number changes in cancerous tissue compared to normal tissue. The methods can be used to diagnose cancer and other diseases associated with chromosomal anomalies.
Systems and methods of providing access to a resource via an access management system may include: receiving, at an authorization server, a login request to a user profile from a client application, wherein the login request comprises a set of login credentials; transmitting, from the authorization server to an identity provider, the set of login credentials; authenticating, upon validation of the set of login credentials by the identity provider, the user; receiving, at the authorization server and subsequent to the authenticating, an authentication request from the client application; issuing, subsequent to validating the authentication request and by the authorization server, an access token to the client application; detecting, at a resource server, a request from the client application to access a resource, wherein the request comprises the access token; and enabling, by the resource server and responsive to validating the access token, the client application access to the resource.
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Methods for generating a sequencing library from a sample comprising a plurality of single-stranded DNA molecules are provided, along with methods of using the generated sequencing library for detecting cancer, determining cancer stage, monitoring cancer progression, and/or determining a cancer classification from a test sample obtained from a subject.
C12N 15/10 - Procédés pour l'isolement, la préparation ou la purification d'ADN ou d'ARN
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Downloadable scientific and medical data via the internet
(term considered too vague by the International Bureau -
rule 13 (2) (b) of the Regulations); downloadable electronic
data files featuring genetic information; downloadable
electronic data files featuring medical information;
downloadable electronic data files featuring cancer
screening information and results; scientific instruments
and apparatus for use in genetic research and analysis;
scientific instruments and apparatus for use in medical
research and analysis; scientific instruments and apparatus
for use in cancer research and analysis; scientific
instruments and apparatus for use in body fluid collection
and analysis; medical laboratory research instruments for
use in detecting cancer; medical laboratory research
instruments for use in detecting genetic sequences; medical
laboratory research instruments for use in collecting and
analyzing body fluids; test tubes. Medical apparatus and instruments for use in detecting
cancer; medical apparatus and instruments for use in
detecting genetic sequences; medical apparatus and
instruments for use in collecting and analyzing body fluids;
blood testing apparatus.
44.
SYSTEMS AND METHODS FOR PERFORMING ADDITIVE SMOOTHING ON LOW-COVERAGE SEQUENCING DATA FROM A NUCLEIC ACID SAMPLE
Systems and methods for reducing noise for the analysis of low coverage sequencing data from a nucleic acid sample using a method, including: receiving, at an input component of the system, a set of sequence reads associated with the nucleic acid sample; allocating, using a processor component of the system, the set of sequence reads into a plurality of genomic bins; and introducing, subsequent to the allocating, a pseudocount number to bincount values to produce a smoothed dataset, wherein each of the bincount values is associated with one of the plurality of genomic bins. Other aspects are described and claimed.
G16H 50/50 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour la simulation ou la modélisation des troubles médicaux
45.
TUMOR FRACTION ESTIMATION USING METHYLATION VARIANTS
A computer-implemented method for generating a tumor fraction estimate from a DNA sample of a subject is disclosed. The method may include receiving a dataset of methylation sequence reads from the sample of the subject. The method may also include dividing the dataset into a plurality of variants. The method, may further include determining methylation states of the plurality of variants. The method may further include filtering the plurality of variants based on a bank of reference sequence reads to generate a filtered subset of variants. The bank may include reads generated from non-cancer samples and biopsy samples of a plurality of tissues of reference individuals. The counts of the methylation states of variants in the filtered subset are determined and input to a model that is trained based on recurrence rates of the variants in the reference sequence reads. The tumor fraction estimate may be generated by the model.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
46.
COMPOSITIONS AND METHODS FOR IDENTIFYING CELL TYPES
The present disclosure relates generally to compositions and methods for determining cell type based on a methylation profile of associated DNA. For cell free DNA, such determination can be used to identify disease or conditions relating to the cell type. For tumor cells, such determination is useful for identifying their primary origin.
C12Q 1/6881 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour le typage de tissu ou de cellule, p. ex. sondes d’antigène leucocytaire humain [HLA]
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
Provided herein are methods for enriching a biological sample for a target nucleic acid, and analyzing the nucleic acid. In some cases, a biological sample is enriched for target nucleic acids associated with a cancer or tumor. In some cases, a biological sample is enriched for target nucleic acids, and the target nucleic acids vary in length. In some cases, one or more probes are used to enrich the biological sample for the target nucleic acid. In some cases, one or more probes hybridize to one or more ends of a target nucleic acid.
Technical solutions for classifying patients with respect to multiple cancer classes are provided. The classification can be done using cell-free whole genome sequencing information from subjects. A reference set of subjects is used to train classifiers to recognize genomic markers that distinguish such cancer classes. The classifier training includes dividing the reference genome into a set of non-overlapping bins, applying a dimensionality reduction method to obtain a feature set, and using the feature set to train classifiers. For subjects with unknown cancer class, the trained classifiers provide probabilities or likelihoods that the subject has a respective cancer class for each cancer in a set of cancer classes. The present disclosure thus describes methods to improve the screening and detection of cancer class from among several cancer classes. This serves to facilitate early and appropriate treatment for subjects afflicted with cancer.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p. ex. pour des dossiers électroniques de patients
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
G16H 70/60 - TIC spécialement adaptées au maniement ou au traitement de références médicales concernant des pathologies
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
(1) Downloadable electronic data files containing genetic sequence analysis results; downloadable electronic data files containing medical test results; downloadable electronic data files containing cancer screening test results; scientific instruments and apparatus for use in genetic, medical and cancer research and analysis and in body fluid collection and analysis, namely, analytical apparatus in the form of nucleic acid hybridization panels, diagnostic DNA sequence detection devices for scientific research purposes, laboratory instruments for the detection of cancer in a blood sample for use in a medical laboratory, and nucleic acid sequencers for scientific purposes; medical laboratory research instruments for use in detecting cancer; medical laboratory research instruments for use in detecting genetic sequences; medical laboratory research instruments for use in collecting and analyzing body fluids; test tubes.
(2) Medical apparatus and instruments for use in detecting cancer; medical apparatus and instruments for use in detecting genetic sequences; medical apparatus and instruments for use in collecting and analyzing body fluids; body fluids analyzer for medical purpose, namely, blood testing analyzers.
50.
DIAGNOSTIC APPLICATIONS USING NUCLEIC ACID FRAGMENTS
Various embodiments are directed to applications (e.g., classification of biological samples) of the analysis of the count, the fragmentation patterns, and size of cell-free nucleic acids, e.g., plasma DNA and serum DNA, including nucleic acids from pathogens, such as viruses. Embodiments of one application can determine if a subject has a particular condition. For example, a method of present disclosure can determine if a subject has cancer or a tumor, or other pathology. Embodiments of another application can be used to assess the stage of a condition, or the progression of a condition over time. For example, a method of the present disclosure may be used to determine a stage of cancer in a subject, or the progression of cancer in a subject over time (e.g., using samples obtained from a subject at different times).
C12Q 1/6888 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour la détection ou l’identification d’organismes
C12Q 1/6879 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour la détermination du sexe
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/686 - Réaction en chaine par polymérase [PCR]
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
51.
Methylation markers and targeted methylation probe panel
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 25/20 - Réaction en chaîne par polyméraseConception d’amorces ou de sondesOptimisation de la sonde
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
Methods are provided to improve the positive predictive value for cancer detection using cell-free nucleic acid samples. Various embodiments are directed to applications (e.g., diagnostic applications) of the analysis of the fragmentation patterns and size of cell-free DNA, e.g., plasma DNA and serum DNA, including nucleic acids from pathogens, including viruses. Embodiments of one application can determine if a subject has a particular condition. For example, a method of present disclosure can determine if a subject has cancer or a tumor, or other pathology. Embodiments of another application can be used to assess the stage of a condition, or the progression of a condition over time. For example, a method of the present disclosure may be used to determine a stage of cancer in a subject, or the progression of cancer in a subject over time (e.g., using samples obtained from a subject at different times).
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6806 - Préparation d’acides nucléiques pour analyse, p. ex. pour test de réaction en chaîne par polymérase [PCR]
C12Q 1/686 - Réaction en chaine par polymérase [PCR]
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
C12Q 1/70 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des virus ou des bactériophages
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
Described herein are methods of preparing dual-indexed nucleic acid libraries for methylation profiling using bisulfite conversion sequencing. In various embodiments, the methods use a two-step indexing process to tag bisulfite-treated DNA with unique molecular identifiers (UMIs).
Various embodiments are directed to applications (e.g., classification of biological samples) of the analysis of the count and size of cell-free nucleic acids, e.g., plasma DNA and serum DNA, including nucleic acids from pathogens, such as viruses. Embodiments of one application can predict if a subject previously treated for a pathology will relapse at a future time point. Targeted sequencing (e.g., specifically designed capture probes, amplification primers) can be used to identify DNA across the entire viral genome.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
Methods for measuring subpopulations of target molecules (e.g., polypeptides and/or cell-free ribonucleic acid) are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.
G01N 33/574 - Tests immunologiquesTests faisant intervenir la formation de liaisons biospécifiquesMatériaux à cet effet pour le cancer
G01N 33/68 - Analyse chimique de matériau biologique, p. ex. de sang ou d'urineTest par des méthodes faisant intervenir la formation de liaisons biospécifiques par ligandsTest immunologique faisant intervenir des protéines, peptides ou amino-acides
56.
SOMATIC VARIANT COOCCURRENCE WITH ABNORMALLY METHYLATED FRAGMENTS
Systems and methods for identifying variant alleles as somatic or germline are provided. Reference and variant alleles for a genomic position are identified. Methylation states and sequences of nucleic acid fragment sequences that map to the genomic position are obtained from a sample of a subject. Using the sequences of nucleic acid fragment sequences, each nucleic acid fragment sequence that has the reference allele is assigned to a reference subset, and each nucleic acid fragment sequence that has the variant allele is assigned to a variant subset. One or more indications of the methylation states across the nucleic acid fragment sequences in the variant subset and an indication of the number of nucleic acid fragment sequences in the reference subset versus the variant subset are applied to a trained binary classifier. An identification of the variant allele at the genomic position as somatic or germline is obtained from the classifier.
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 20/10 - Ploïdie ou détection du nombre de copies
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 10/40 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données relatives aux analyses de laboratoire, p. ex. pour des analyses d’échantillon de patient
Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
Nuclease activity can affect the methylation level and fragmentation of cfDNA. Certain levels of nuclease activity may be correlated with certain levels of methylation in certain regions. Methylation level in certain genomic regions can be analyzed to classify nuclease activity. Methylation statuses of different genomic regions compared to methylation statuses of other genomic regions can determine a level of a condition (e.g., a disease such as cancer or disorder) in a subject. Nuclease activity can be monitored through analysis of methylation statuses of different sites. The efficacy of a treatment can also be determined using methylation levels at certain genomic regions. The number of fragments from genomic regions that are hypomethylated or hypermethylated in a reference genome can be used to provide information (e.g., fractional concentration) on the sample itself. The size distribution of extrachromosomal circular DNA can also be used to analyze a biological sample. Systems are also described.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
59.
Methylation markers and targeted methylation probe panel
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 25/20 - Réaction en chaîne par polyméraseConception d’amorces ou de sondesOptimisation de la sonde
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
42 - Services scientifiques, technologiques et industriels, recherche et conception
44 - Services médicaux, services vétérinaires, soins d'hygiène et de beauté; services d'agriculture, d'horticulture et de sylviculture.
Produits et services
Scientific and medical research services; providing
information in the field of genetics and cancer for medical
or scientific research via an online database; providing
temporary use of on-line non-downloadable software and
applications for use in studying, diagnosing or screening
for cancer and studying genetics and DNA; providing
temporary use of on-line non-downloadable cloud computing
software for use in studying, diagnosing or screening cancer
and studying genetics and DNA; software as a service (SaaS)
services featuring software in the nature of a platform for
genetic and bioinformatics analysis. Genetic testing and reporting for medical purposes; medical
testing for diagnostic or treatment purposes; medical
screening; medical diagnostic testing, monitoring and
reporting services; providing medical information regarding
genetics via a website; genetic analysis and reporting
services for medical purposes.
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Downloadable scientific and medical data via the internet; downloadable electronic data files featuring genetic information; downloadable electronic data files featuring medical information; downloadable electronic data files featuring cancer screening information and results; scientific instruments and apparatus for use in genetic research and analysis; scientific instruments and apparatus for use in medical research and analysis; scientific instruments and apparatus for use in cancer research and analysis; scientific instruments and apparatus for use in body fluid collection and analysis; medical laboratory research instruments for use in detecting cancer; medical laboratory research instruments for use in detecting genetic sequences; medical laboratory research instruments for use in collecting and analyzing body fluids; test tubes Medical apparatus and instruments for use in detecting cancer; medical apparatus and instruments for use in detecting genetic sequences; medical apparatus and instruments for use in collecting and analyzing body fluids; blood testing apparatus
62.
METHODS OF IDENTIFYING SOMATIC MUTATIONAL SIGNATURES FOR EARLY CANCER DETECTION
Aspects of the invention include methods and systems for identifying somatic mutational signatures for detecting, diagnosing, monitoring and/or classifying cancer in a patient known to have, or suspected of having cancer. In various embodiments, the methods of the invention use a non-negative matrix factorization (NMF) approach to construct a signature matrix that can be used to identify latent signatures in a patient sample for detection and classification of cancer. In some embodiments, the methods of the invention may use principal components analysis (PCA) or vector quantization (VQ) approaches to construct a signature matrix.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
63.
Systems and methods for automated classification of a document
A method for extracting information from a dataset, e.g., a document, includes: receiving the dataset at an information handling device, optionally, extracting, via optical character recognition implemented by a processor of the information handling device, textual information associated with the dataset, and classifying the dataset into one of a plurality of classes. Classifying the dataset may include computing a similarity score for each of the plurality of classes for each of a plurality of window regions of the dataset, calculating a subset of highest similarity scores for each of the plurality of classes for each of the plurality of window regions, determining overall similarity scores for each of the plurality of classes, and classifying the dataset as corresponding to a class with a highest overall similarity score.
42 - Services scientifiques, technologiques et industriels, recherche et conception
44 - Services médicaux, services vétérinaires, soins d'hygiène et de beauté; services d'agriculture, d'horticulture et de sylviculture.
Produits et services
Scientific and medical research services; providing
information in the field of genetics and cancer for medical
or scientific research via an online database; providing
temporary use of on-line non-downloadable software and
applications for use in studying, diagnosing or screening
for cancer and studying genetics and DNA; providing
temporary use of on-line non-downloadable cloud computing
software for use in studying, diagnosing or screening cancer
and studying genetics and DNA; software as a service (SaaS)
services featuring software in the nature of a platform for
genetic and bioinformatics analysis. Genetic testing and reporting for medical purposes; medical
testing for diagnostic or treatment purposes; medical
screening; medical diagnostic testing, monitoring and
reporting services; providing medical information regarding
genetics via a website; genetic analysis and reporting
services for medical purposes.
65.
PREPARATION OF NUCLEIC ACID SAMPLES FOR SEQUENCING
Compositions and methods are provided for amplifying nucleic acids, including cell free nucleic acid fragments, in preparation for sequencing. Methods are provided for making circularized nucleic acid templates having the structure [T]-[PS1]-[L]-[PS2] or [PS1]-[L]-[PS2]-[T'], where (a) T is a target nucleic acid and T' is a complement to a target nucleic acid; (b) each of PS1 and PS2 is a nucleic acid primer site; (c) L is a linker having a primer extension reaction terminating organic molecule; and the structure is circularized by binding a 5' end thereof to a 3' end thereof. Target sequences in the circularized templates are amplified by binding to PS1 a primer complimentary to PS1 and binding to PS2 a primer complimentary to PS2 and copying the target sequences by a primer extension reaction. Advantages include a reduction in ligation steps, which can result in fewer clean up steps and improved library conversion efficiency.
05 - Produits pharmaceutiques, vétérinaires et hygièniques
10 - Appareils et instruments médicaux
Produits et services
Medical diagnostic reagents and medical diagnostic kits comprised of medical diagnostic reagents; reagents for medical use and medical diagnostics and screening kits comprised of reagents for medical diagnostics or screening use; reagents for use in genetic testing for medical and medical diagnostic purposes; diagnostic preparations for medical purposes; assays, reagents, enzymes, and nucleotides for medical purposes, including for medical diagnostics or screening purposes; diagnostic assays, reagents, enzymes, and nucleotides for medical purposes, including for medical diagnostics or screening purposes. Blood testing apparatus.
67.
METHODS USING CHARACTERISTICS OF URINARY AND OTHER DNA
The ends of cell-free DNA fragments may be used for analysis of a biological sample. In some embodiments, DNA from a urine sample may be analyzed. Cell-free DNA fragments often include jagged ends, where one end of one strand of double-stranded DNA extends beyond the other end of the other strand. The length and amount of these jagged ends may be used to determine a level of a condition of an individual. The density of ends of fragments in certain regions may also be used in classifying the level of a condition. Additionally, DNA fragments may show a periodic pattern with the amount of DNA fragments corresponding to a length of the overhang. The periodicity may be analyzed to determine properties of a biological sample. Jagged ends may also be analyzed with a technique that avoids trimming overhanging 3' ends of a double-stranded DNA.
C12Q 1/68 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des acides nucléiques
68.
METHODS USING CHARACTERISTICS OF URINARY AND OTHER DNA
The ends of cell-free DNA fragments may be used for analysis of a biological sample. In some embodiments, DNA from a urine sample may be analyzed. Cell-free DNA fragments often include jagged ends, where one end of one strand of double-stranded DNA extends beyond the other end of the other strand. The length and amount of these jagged ends may be used to determine a level of a condition of an individual. The density of ends of fragments in certain regions may also be used in classifying the level of a condition. Additionally, DNA fragments may show a periodic pattern with the amount of DNA fragments corresponding to a length of the overhang. The periodicity may be analyzed to determine properties of a biological sample. Jagged ends may also be analyzed with a technique that avoids trimming overhanging 3′ ends of a double-stranded DNA.
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
C12Q 1/6816 - Tests d’hybridation caractérisés par les moyens de détection
05 - Produits pharmaceutiques, vétérinaires et hygièniques
10 - Appareils et instruments médicaux
Produits et services
Medical diagnostic reagents and medical diagnostic kits comprised of medical diagnostic reagents; reagents for medical use and medical diagnostics or screening kits comprised of reagents for medical diagnostics or screening use; reagents for use in genetic testing for medical and medical diagnostic purposes; diagnostic preparations for medical purposes; assays, reagents, enzymes, and nucleotides for medical or clinical diagnostics or screening purposes; diagnostic assays, reagents, enzymes, and nucleotides for medical or clinical purposes. Blood testing apparatus.
70.
DETECTING CANCER, CANCER TISSUE OF ORIGIN, AND/OR A CANCER CELL TYPE
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel to detect cancer and particular types of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6827 - Tests d’hybridation pour la détection de mutation ou de polymorphisme
C12Q 1/6874 - Méthodes de séquençage faisant intervenir des réseaux d’acides nucléiques, p. ex. séquençage par hybridation [SBH]
71.
DETECTING CANCER, CANCER TISSUE OF ORIGIN, AND/OR A CANCER CELL TYPE
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel for detection of cancer tissue of origin (e.g., types of cancer).
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6827 - Tests d’hybridation pour la détection de mutation ou de polymorphisme
A method for training a convolutional neural net for contamination analysis is provided. A training dataset is obtained comprising, for each respective training subject in a plurality of subjects, a variant allele frequency of each respective single nucleotide variant in a respective plurality of single nucleotide variants, and a respective contamination indication. First and second subsets of the plurality of training subjects have first and second contamination indication values, respectively. A corresponding first channel comprising a first plurality of parameters that include a respective parameter for a single nucleotide variant allele frequency of each respective single nucleotide variant in a set of single nucleotide variants in a reference genome is constructed for each respective training subject. An untrained or partially trained convolutional neural net is trained using, for each respective training subject, at least the corresponding first channel of the respective training subject as input against the respective contamination indication.
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel to detect cancer and particular types of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6809 - Méthodes de détermination ou d’identification des acides nucléiques faisant intervenir la détection différentielle
Systems and methods for validating that a DNA sample is from a test subject are disclosed. The test subject reports one or more characteristics (biological sex, ethnicity, and/or age) that may be predicted from the DNA sample. The predictions are compared to the reported characteristics to validate the DNA sample. To validate according to biological sex, the system determines a Y-chromosome signal based on counts of sequence reads for a gene specific to the Y chromosome and, similarly, an X-chromosome signal using another gene specific to the X chromosome. The biological sex is predicted based on a comparison of the two signals. To validate according to ethnicity, the system predicts ethnicity based on detected allele frequencies for SNPs specific to each chromosome. To validate according to age, the system calculates the methylation densities for age-informative CpG sites. The system utilizes trained regression models to predict the age using the methylation densities.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6879 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour la détermination du sexe
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
Detecting cross-contamination between test samples used for determining cancer in a subject is beneficial. To detect cross-contamination, test sequences including at least one single nucleotide polymorphism are prepared using genome sequencing techniques. Some of the test sequences can be filtered to improve accuracy and precision. A prior contamination probability for each test sequence is determined based on a minor allele frequency. A contamination model including a likelihood test is applied to a test sequence. The likelihood test obtains a current contamination probability representing the likelihood that the test sample is contaminated. The contamination model can also determine a likelihood that the sample includes loss of heterozygosity representing the likelihood that the test sequence is contaminated. Test samples that are contaminated are removed. A source for the contaminated test sample can be found by comparing contaminated test sequences to other test sequences.
Detecting cross-contamination between test samples used for determining cancer in a subject is beneficial. To detect cross-contamination, test sequences including at least one single nucleotide polymorphism are prepared using genome sequencing techniques. Some of the test sequences can be filtered to improve accuracy and precision. A prior contamination probability for each test sequence is determined based on a minor allele frequency. A contamination model including a likelihood test is applied to a test sequence. The likelihood test obtains a current contamination probability representing the likelihood that the test sample is contaminated. The contamination model can also determine a likelihood that the sample includes loss of heterozygosity representing the likelihood that the test sequence is contaminated. Test samples that are contaminated are removed. A source for the contaminated test sample can be found by comparing contaminated test sequences to other test sequences.
Size-band analysis is used to determine whether a chromosomal region exhibits a copy number aberration or an epigenetic alteration. Multiple size ranges may be analyzed instead of focusing on specific sizes. By using multiple size ranges instead of specific sizes, methods may analyze more sequence reads and may be able to determine whether a chromosomal region exhibits a copy number aberration even when clinically-relevant DNA may be a low fraction of the biological sample. Using multiple ranges may allow for the use of all sequence reads from a genomic region, rather than a selected subset of reads in the genomic region. The accuracy of analysis may be increased with higher sensitivity at similar or higher specificity. Analysis may include fewer sequencing reads to achieve the same accuracy, resulting in a more efficient process.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/6809 - Méthodes de détermination ou d’identification des acides nucléiques faisant intervenir la détection différentielle
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
78.
DETECTING CANCER, CANCER TISSUE OF ORIGIN, AND/OR A CANCER CELL TYPE
The present description provides a hematological disorder (HD) assay panel for targeted detection of methylation patterns or variants specific to various hematological disorders, such as clonal hematopoiesis of indeterminate potential (CHIP) and blood cancers, such as leukemia, lymphoid neoplasms (e.g. lymphoma), multiple myeloma, and myeloid neoplasm. Further provided herein includes methods of designing, making, and using the HD assay panel for detection of various hematological disorders.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 25/10 - Profilage de l’expression de gènes ou de protéinesEstimation ou normalisation de ratio d’expression
Systems and methods for validating that a DNA sample is from a test subject are disclosed. The test subject reports one or more characteristics (biological sex, ethnicity, and/or age) that may be predicted from the DNA sample. The predictions are compared to the reported characteristics to validate the DNA sample. To validate according to biological sex, the system determines a Y-chromosome signal based on counts of sequence reads for a gene specific to the Y chromosome and, similarly, an X-chromosome signal using another gene specific to the X chromosome. The biological sex is predicted based on a comparison of the two signals. To validate according to ethnicity, the system predicts ethnicity based on detected allele frequencies for SNPs specific to each chromosome. To validate according to age, the system calculates the methylation densities for age-informative CpG sites. The system utilizes trained regression models to predict the age using the methylation densities.
Various embodiments are performed to using nuclease expression in tissues that influences cell-free DNA end signatures/motifs and size of overhang between DNA strands. Embodiments can identify a nuclease that is being differentially regulated in abnormal cells relative to normal cells. Embodiments can determine that the nuclease preferentially cuts DNA into DNA molecules having: (i) a particular sequence end signature; or (ii) a specified length of overhang between a first strand and a second strand. A parameter can be determined for a biological sample based on an amount of DNA molecules that include an end sequence corresponding to the particular sequence end signature and/or a measured property correlating to the specified length of overhang. The parameter can be used to determine a characteristic of a tissue type, a fractional concentration of clinically-relevant DNA molecules, or a level of abnormality of a tissue type in the biological sample.
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
81.
NUCLEASE-ASSOCIATED END SIGNATURE ANALYSIS FOR CELL-FREE NUCLEIC ACIDS
Various embodiments are directed to using nuclease expression in tissues that influences cell-free DNA end signatures/motifs and size of overhang between DNA strands. Embodiments can identify a nuclease that is being differentially regulated in abnormal cells relative to normal cells. Embodiments can determine that the nuclease preferentially cuts DNA into DNA molecules having: (i) a particular sequence end signature; or (ii) a specified length of overhang between a first strand and a second strand. A parameter can be determined for a biological sample based on an amount of DNA molecules that include an end sequence corresponding to the particular sequence end signature and/or a measured property correlating to the specified length of overhang. The parameter can be used to determine a characteristic of a tissue type, a fractional concentration of clinically-relevant DNA molecules, or a level of abnormality of a tissue type in the biological sample.
C12Q 1/34 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir une hydrolase
Systems and methods described herein include detecting a presence or absence of HPV in a biological sample having cell-free nucleic acids from a subject and potentially cell-free nucleic acids from an HPV strain. Based on a detection of HPV viral nucleic acids in the biological sample, an HPV-based multiclass classifier that predicts a score for each HPV-associated cancer type is applied. The HPV-based multiclass classifier is trained on a training set of HPV-positive cancer samples. An HPV-associated cancer associated with the biological sample is determined based on the scores predicted by the HPV multiclass classifier.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
C12Q 1/70 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des virus ou des bactériophages
83.
METHYLATED DNA FRAGMENT ENRICHMENT, METHODS, COMPOSITIONS AND KITS
A method of processing an input sample, as well as related kits and compositions, is provided herein. In various instances, the disclosure relates to providing an input sample comprising nucleic acid fragments, wherein in at least a portion of the nucleic acid fragments each fragment comprises one or more methylated cytosines; converting unmethylated cytosines of nucleic acid fragments of the input sample to uracils, yielding converted fragments; copying the converted fragments using a mixture of nucleotides, the mixture comprising a mixture of: binding moiety-modified cytosines and binding moiety-lacking cytosines; binding moiety-modified guanines and binding moiety-lacking guanines; or binding moiety-modified cytosines, binding moiety-lacking cytosines, binding moiety-modified guanines, and binding moiety-lacking guanines; wherein the copying yields a mixture of binding moiety-modified fragments and unmodified fragments which may be separated to provide a set of fragments enriched for hypermethylated fragments.
Methods for measuring subpopulations of cell-free ribonucleic acid (RNA) molecules are provided. In some embodiments, methods of generating a sequencing library from a plurality of RNA molecules in a test sample obtained from a subject are provided, as well as methods for analyzing the sequencing library to detect, e.g., the presence or absence of a disease.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
85.
GENERATING CANCER DETECTION PANELS ACCORDING TO A PERFORMANCE METRIC
A system generates a cancer detection panel. The system is configured to generate an assay having a minimized size and number of genomic regions while still detecting the presence of cancer at or above a specific performance threshold. To select the genomic regions for the panel, the system employs a classification model. The classification model receives a set of genomic regions that may be associated with disease presence. The model then determines a sensitivity score for each genomic region and ranks the regions according to their score. The sensitivity score is based on a likelihood that variations in the genomic region are indicative of cancer. The model then selects genomic regions for the panel based on their rank. The model only selects as many genomic indicators as are needed for desired detection performance. The genomic regions can be associated with solid or liquid cancers, viral regions, or cancer hotspots.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
86.
CANCER CLASSIFICATION WITH SYNTHETIC SPIKED-IN TRAINING SAMPLES
Methods and systems for detecting cancer and/or determining a cancer tissue of origin are disclosed. A multiclass cancer classifier is disclosed that is trained with a plurality of biological samples containing cfDNA fragments and at least one synthetic training sample generated from the biological samples. The analytics system generates the synthetic training sample by sampling fragments from a training sample labeled as cancer and sampling fragments from another training sample labeled as non-cancer. The sampling probability is determined based on a limit of detection of the cancer classifier, e.g., in order to generate synthetic training samples with cancer tumor fraction proximate to the limit of detection.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 30/00 - TIC spécialement adaptées à l’analyse de séquences impliquant des nucléotides ou des aminoacides
87.
CANCER CLASSIFICATION WITH GENOMIC REGION MODELING
Methods and systems for detecting cancer and/or determining a cancer tissue of origin are disclosed. Fragments are grouped into genomic regions, wherein a region model is trained for each genomic region using a neural network with hidden layers. Fragments are input into the region models, and the outputs are used to generate a feature vector for cancer classification. In one embodiment, the region models are shallow neural networks configured to generate a score indicating a likelihood that a fragment is derived from a cancer biological sample. The feature vector is determined based on counts of fragments having scores above threshold scores for the various genomic regions. In another embodiment, the regions models are configured to generate a region embedding for an input methylation embedding of a fragment. The region embeddings are pooled by region and then pooled again to generate the feature vector.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
88.
SYSTEMS AND METHODS FOR CALLING VARIANTS USING METHYLATION SEQUENCING DATA
An allelic position variant calling method using a prior genotype probability at the allelic position is provided. A strand specific base count set in forward and reverse directions for the allelic position is obtained, using strand orientation and identity of a respective base at the allelic position in each respective nucleic acid fragment sequence that maps to the allelic position, where bases at the allelic position whose identity can be affected by conversion of cytosine to uracil do not contribute to the strand specific base count set. Respective forward and reverse strand conditional probabilities are computed for each candidate genotype for the allelic position using the strand specific base count set and sequencing error estimate. Likelihoods are computed using a combination of these conditional probabilities and the prior genotype probability. From this, a determination is made as to whether the likelihoods support a variant call at the allelic position.
A method for discriminating a cancer state is provided. A first dataset is obtained for a plurality of subjects having a first cancer state. Each subject has a plurality of nucleic acid methylation fragments with methylation patterns comprising CpG site methylation states. An autoencoder including an encoder and decoder is trained by evaluating the error in the autoencoder reconstruction of the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the first dataset. A second dataset is obtained for a plurality of subjects having a second cancer state. A plurality of features is identified by inputting the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the second dataset into the trained autoencoder and computing a score determined by the autoencoder reconstruction of the methylation pattern. The plurality of features is used to train a supervised model that discriminates a cancer state.
An allelic position variant calling method using a prior genotype probability at the allelic position is provided. A strand specific base count set in forward and reverse directions for the allelic position is obtained, using strand orientation and identity of a respective base at the allelic position in each respective nucleic acid fragment sequence that maps to the allelic position, where bases at the allelic position whose identity can be affected by conversion of cytosine to uracil do not contribute to the strand specific base count set. Respective forward and reverse strand conditional probabilities are computed for each candidate genotype for the allelic position using the strand specific base count set and sequencing error estimate. Likelihoods are computed using a combination of these conditional probabilities and the prior genotype probability. From this, a determination is made as to whether the likelihoods support a variant call at the allelic position.
Systems and methods of identifying methylation patterns discriminating or indicating a cancer condition are provided. First and second datasets are obtained. Each dataset comprises a plurality of fragment methylation patterns determined by methylation sequencing of nucleic acids obtained from a first or second set of subjects and comprising a methylation state of each CpG site in a corresponding plurality of CpG sites. Each plurality of subjects has a respective first or second state of the cancer condition. First and second interval maps are generated for each respective dataset, each comprising a plurality of nodes characterized by a start methylation site, an end methylation site, a representation of each different fragment methylation pattern and a count of fragments. The first and second interval maps are scanned for qualifying methylation patterns within a predetermined range of CpG sites, satisfying one or more selection criteria, thereby identifying methylation patterns discriminating a cancer condition.
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 25/20 - Réaction en chaîne par polyméraseConception d’amorces ou de sondesOptimisation de la sonde
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein are methods of designing, making, and using the cancer assay panel for the diagnosis of cancer.
G16B 40/00 - TIC spécialement adaptées aux biostatistiquesTIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p. ex. extraction de connaissances ou détection de motifs
G16B 30/10 - Alignement de séquenceRecherche d’homologie
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16B 20/20 - Détection d’allèles ou de variantes, p. ex. détection de polymorphisme d’un seul nucléotide
G16B 25/20 - Réaction en chaîne par polyméraseConception d’amorces ou de sondesOptimisation de la sonde
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
94.
BITERMINAL DNA FRAGMENT TYPES IN CELL-FREE SAMPLES AND USES THEREOF
The present disclosure describes techniques for measuring quantities (e.g., relative frequencies) of end motif pairs of cell-free DNA fragments in a biological sample of an organism for measuring a property of the sample (e.g., fractional concentration of clinically-relevant DNA) and/or determining a pathology of the organism based on such measurements. Different tissue types exhibit different patterns for the relative frequencies of the end motif pairs. The present disclosure provides various uses for measurements of the relative frequencies of end motif pairs of cell-free DNA, e.g., in mixtures of cell-free DNA from various tissues. DNA from certain tissue(s) may be referred to as clinically-relevant DNA.
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
95.
BITERMINAL DNA FRAGMENT TYPES IN CELL-FREE SAMPLES AND USES THEREOF
It describes techniques for measuring quantities (e.g., relative frequencies) of end motif pairs of cell-free DNA fragments in a biological sample of an organism for measuring a property of the sample (e.g., fractional concentration of clinically-relevant DNA) and/or determining a pathology of the organism based on such measurements. Different tissue types exhibit different patterns for the relative frequencies of the end motif pairs. It provides various uses for measurements of the relative frequencies of end motif pairs of cell-free DNA, e.g., in mixtures of cell-free DNA from various tissues. DNA from certain tissue(s) may be referred to as clinically-relevant DNA.
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
Various methods, apparatuses, and systems are provided for detecting a genetic disorder in a gene associated with a nuclease, for determining an efficacy of a dosage of an anticoagulant, and for monitoring an activity of a nuclease. Measured parameter values can be compared to a reference value to determine classifications of a genetic disorder, efficiency, or activity. An amount of a particular base (e.g., in an end motif) at fragment ends, an amount of a particular base at fragment ends of a particular size, or a total amount of cell-free DNA fragments (e.g., as a concentration) can be used. Certain samples may be treated with an anticoagulant, and different incubation times can be used for certain methods.
C12Q 1/6827 - Tests d’hybridation pour la détection de mutation ou de polymorphisme
C12Q 1/6883 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique
C12Q 1/6886 - Produits d’acides nucléiques utilisés dans l’analyse d’acides nucléiques, p. ex. amorces ou sondes pour les maladies provoquées par des altérations du matériel génétique pour le cancer
97.
SYSTEMS AND METHODS FOR ESTIMATING CELL SOURCE FRACTIONS USING METHYLATION INFORMATION
A method of identifying a plurality of features for estimating subject cell source fraction is provided. For each respective training subject in a plurality of training subjects, a corresponding methylation pattern of each respective cell-free fragment in a corresponding training plurality of cell-free fragments and a corresponding subject cancer indication is obtained. Each cell-free fragment is mapped to a bin in a plurality of bins, each bin representing a portion of a human reference genome. A cell-free fragment cancer condition is assigned to each cell-free fragment, as a function of a classifier upon inputting a corresponding methylation pattern of the respective cell-free fragment into the classifier. A measure of association is determined for each bin between the subject cancer condition and the cell-free fragment cancer condition. The plurality of features for estimating subject cell source fraction are identified as a subset of the plurality of bins.
Methods for determining a disease condition of a subject of a species are provided that comprises obtaining a dataset of fragment methylation patterns determined by methylation sequencing of nucleic acid from a biological sample of the subject. A fragment methylation pattern comprises the methylation state of each CpG site in the fragment. A patch including a channel comprising parameters for the methylation status of respective CpG sites in a set of CpG sites in a reference genome represented by the patch is constructed by populating, for each respective fragment in the plurality of fragments that aligns to the set of CpG sites, an instance of all or a portion of the plurality of parameters based on the methylation pattern of the respective fragment. Application of the patch to a patch convolutional neural network determines the disease condition of the subject.
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
99.
SYSTEMS AND METHODS FOR EVALUATING LONGITUDINAL BIOLOGICAL FEATURE DATA
Systems and methods are provided for determining whether a test subject has a disease condition. In one aspect, the method includes determining at least first and second genotypic data constructs for a test subject, formed from data collected from first and second sample from the subject, respectively, at different times. The first and second genotypic data constructs are inputted into a model for the disease condition, thereby generating first and second model score sets for the disease condition, respectively. A test delta score set is determined based on a difference between the first and second model score sets. The test delta score set is evaluated against a plurality of reference delta score sets, to determine the disease condition of the test subject, where each reference delta score set is for a respective reference subject in a plurality of reference subjects.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
G16B 5/00 - TIC spécialement adaptées à la modélisation ou aux simulations dans la biologie des systèmes, p. ex. réseaux de régulation génétique, réseaux d’interaction entre protéines ou réseaux métaboliques
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
G16H 50/30 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le calcul des indices de santéTIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour l’évaluation des risques pour la santé d’une personne
100.
SYSTEMS AND METHODS FOR EVALUATING LONGITUDINAL BIOLOGICAL FEATURE DATA
Systems and methods are provided for determining whether a test subject has a disease condition. In one aspect, the method includes determining at least first and second genotypic data constructs for a test subject, formed from data collected from first and second sample from the subject, respectively, at different times. The first and second genotypic data constructs are inputted into a model for the disease condition, thereby generating first and second model score sets for the disease condition, respectively. A test delta score set is determined based on a difference between the first and second model score sets. The test delta score set is evaluated against a plurality of reference delta score sets, to determine the disease condition of the test subject, where each reference delta score set is for a respective reference subject in a plurality of reference subjects.
C12Q 1/68 - Procédés de mesure ou de test faisant intervenir des enzymes, des acides nucléiques ou des micro-organismesCompositions à cet effetProcédés pour préparer ces compositions faisant intervenir des acides nucléiques
