Abstract: Gene copy number variations are identified for genes in a targeted gene panel. For each gene, coverage at each base position across the gene is determined. The coverage at each base position can be influenced by the hybridization probes that are used to determine the base level coverage of the base position. The base level coverage for each base position is normalized to account for the characteristics of the hybridization probes. To determine whether a copy number variation exists for a gene, the base level coverage of base positions across the gene for a subject is analyzed to determine whether it deviates from the base level coverage of base positions across the gene for previously analyzed, healthy individuals. If a significant deviation exists, a copy number variation for the gene is called.

Abstract: The disclosure relates to computer technology for precision diagnosis of various states of genetic material such as a gene sequenced from cell-free DNA in a sample. The state may include a somatic homozygous deletion, a somatic heterozygous deletion, a copy number variation, or other states. A computer system may generate competing probabilistic models that each output a probability that the genetic material is in a certain state. Each model may be trained on a training sample set to output a probability that the genetic material is in a respective state. In some embodiments, the computer system may use various probabilistic distributions to generate the models. For example, the computer system may use a beta-binomial distribution, a binomial distribution, a normal (also referred to as “Gaussian”) distribution, or other type of probabilistic modeling techniques.

Abstract: Gene copy number variations are identified for genes in a targeted gene panel. For each gene, coverage at each base position across the gene is determined. The coverage at each base position can be influenced by the hybridization probes that are used to determine the base level coverage of the base position. The base level coverage for each base position is normalized to account for the characteristics of the hybridization probes. To determine whether a copy number variation exists for a gene, the base level coverage of base positions across the gene for a subject is analyzed to determine whether it deviates from the base level coverage of base positions across the gene for previously analyzed, healthy individuals. If a significant deviation exists, a copy number variation for the gene is called.

Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

Abstract: Cross-contamination of a test sample used to determine cancer is identified using gene sequencing data. Each test sample includes a number of test sequences that may include a single nucleotide polymorphism (SNP) that can be indicative of cancer. The test sequences are be filtered to remove or negate at least some of the SNPs from the test sequences. Negating the test sequences allows more test sequences to be simultaneously analyzed to determine cross-contamination. Cross-contamination is determined by modeling the variant allele frequency for the test sequences as a function of minor allele frequency, contamination level, and background noise. In some cases, the variant allele frequency is based on a probability function including the minor allele frequency. Cross-contamination of the test sample is determined if the determined contamination level is above a threshold and statistically significant.

Abstract: Cross-contamination of a test sample used to determine cancer is identified using gene sequencing data. Each test sample includes a number of test sequences that may include a single nucleotide polymorphism (SNP) that can be indicative of cancer. The test sequences are be filtered to remove or negate at least some of the SNPs from the test sequences. Negating the test sequences allows more test sequences to be simultaneously analyzed to determine cross-contamination. Cross-contamination is determined by modeling the variant allele frequency for the test sequences as a function of minor allele frequency, contamination level, and background noise. In some cases, the variant allele frequency is based on a probability function including the minor allele frequency. Cross-contamination of the test sample is determined if the determined contamination level is above a threshold and statistically significant.

Abstract: The disclosure relates to computer technology for precision diagnosis of various states of genetic material such as a gene sequenced from cell-free DNA in a sample. The state may include a somatic homozygous deletion, a somatic heterozygous deletion, a copy number variation, or other states. A computer system may generate competing probabilistic models that each output a probability that the genetic material is in a certain state. Each model may be trained on a training sample set to output a probability that the genetic material is in a respective state. In some embodiments, the computer system may use various probabilistic distributions to generate the models. For example, the computer system may use a beta-binomial distribution, a binomial distribution, a normal (also referred to as “Gaussian”) distribution, or other type of probabilistic modeling techniques.

Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

Abstract: The disclosure relates to computer technology for precision diagnosis of various states of genetic material such as a gene sequenced from cell-free DNA in a sample. The state may include a somatic homozygous deletion, a somatic heterozygous deletion, a copy number variation, or other states. A computer system may generate competing probabilistic models that each output a probability that the genetic material is in a certain state. Each model may be trained on a training sample set to output a probability that the genetic material is in a respective state. In some embodiments, the computer system may use various probabilistic distributions to generate the models. For example, the computer system may use a beta-binomial distribution, a binomial distribution, a normal (also referred to as “Gaussian”) distribution, or other type of probabilistic modeling techniques.

Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

Abstract: Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs known or suspected to be associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by deriving a fragment size parameter. In some implementations, information from fragments of different sizes are used to evaluate copy number variations. In some implementations, one or more t-statistics obtained from coverage information of the sequence of interest is used to evaluate copy number variations. In some implementations, one or more fetal fraction estimates are combined with one or more t-statistics to determine copy number variations.

Abstract: In implementations described herein, information derived from a sample that is derived from off-target sequences can be used to determine estimates for the copy number of tumor cells and/or the tumor fraction of a sample. Additionally, information derived from the presence of germline SNPs can be used to determine estimates for at least one of the copy number of tumor cells or the tumor fraction of a sample.

Abstract: Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs known or suspected to be associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by deriving a fragment size parameter. In some implementations, information from fragments of different sizes are used to evaluate copy number variations. In some implementations, one or more t-statistics obtained from coverage information of the sequence of interest is used to evaluate copy number variations. In some implementations, one or more fetal fraction estimates are combined with one or more t-statistics to determine copy number variations.

Abstract: Provided herein are methods of making negative predictions. In some aspects, methods of determining that a first target nucleic acid variant is absent at a first genetic locus in a cell-free nucleic acid (cfNA) sample obtained from a subject having a given cancer type at least partially using a computer are provided. Certain of these methods include determining that the first target nucleic acid variant is not detected in the cfNA sample obtained from the subject, generating, by the computer, at least one tumor fraction based value; generating, by the computer, at least one mutual exclusivity value; and determining that the first target nucleic acid variant is absent at the first genetic locus in the cfNA sample using the tumor fraction based value and/or the mutual exclusivity value. Additional methods and related systems and computer readable media are also provided.

Abstract: Disclosed are methods for determining copy number variation (CNV) associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation (CNV) of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by deriving a fragment size parameter, such as a size-weighted coverage or a fraction of fragments in a size range. In some embodiments, the fragment size parameter is adjusted to remove within-sample GC-content bias. In some embodiments, removal of within-sample GC-content bias is based on sequence data corrected for systematic variation common across unaffected training samples. Also disclosed are systems and computer program products for evaluation of CNV of sequences of interest.

Abstract: Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.

Abstract: The present disclosure provides methods for sequencing and analysis of nucleic acids.

Abstract: Disclosed are methods for determining copy number variation (CNV) known or suspected to be associated with a variety of medical conditions. In some embodiments, methods are provided for determining copy number variation (CNV) of fetuses using maternal samples comprising maternal and fetal cell free DNA. In some embodiments, methods are provided for determining CNVs known or suspected to be associated with a variety of medical conditions. Some embodiments disclosed herein provide methods to improve the sensitivity and/or specificity of sequence data analysis by deriving a fragment size parameter, such as a size-weighted coverage or a fraction of fragments in a size range. In some embodiments, the fragment size parameter is adjusted to remove within-sample GC-content bias. In some embodiments, removal of within-sample GC-content bias is based on sequence data corrected for systematic variation common across unaffected training samples.

Abstract: The present disclosure provides methods for diagnosis of interstitial lung diseases (ILDs). The present disclosure provides methods for differential diagnosis of idiopathic pulmonary fibrosis from other ILDs. Compositions and kits useful in carrying out a subject method are also provided.

Abstract: The disclosure relates to computer technology for precision diagnosis of various states of genetic material such as a gene sequenced from cell-free DNA in a sample. The state may include a somatic homozygous deletion, a somatic heterozygous deletion, a copy number variation, or other states. A computer system may generate competing probabilistic models that each output a probability that the genetic material is in a certain state. Each model may be trained on a training sample set to output a probability that the genetic material is in a respective state. In some embodiments, the computer system may use various probabilistic distributions to generate the models. For example, the computer system may use a beta-binomial distribution, a binomial distribution, a normal (also referred to as “Gaussian”) distribution, or other type of probabilistic modeling techniques.