Abstract: Systems and methods are provided for identifying a diagnosis of a cancer condition for a somatic tumor specimen of a subject. The method receives sequencing information comprising analysis of a plurality of nucleic acids derived from the somatic tumor specimen. The method identifies a plurality of features from the sequencing information, including two or more of RNA, DNA, RNA splicing, viral, and copy number features. The method provides a first subset of features and a second subset of features from the identified plurality of features as inputs to a first classifier and a second classifier, respectively. The method generates, from two or more classifiers, two or more predictions of cancer condition based at least in part on the identified plurality of features. The method combines, at a final classifier, the two or more predictions to identify the diagnosis of the cancer condition for the somatic tumor specimen of the subject.

Abstract: The disclosure provides methods and systems for detecting alternative splicing variants in a patient sample. The methods involve comparison of splice junction data from RNA sequencing with principal splicing isoforms and identifying those sequences, identifying those sequences that do not match the principal splicing isoform. These sequences are categorized into alternative splicing events and documented. Optionally, previously identified target sequences can be utilized in the comparison where the method seeks sequences which do match. Other methods and systems of the present disclosure include those for building a splice profile of alternative splicing variants for a patient sample and those for developing a companion diagnostic test for a treatment method of a disease based on the presence or absence of alternative splicing variants in a patient sample.

Abstract: Methods, systems, and software are provided for an ensemble model trained to distinguish between cancers with homologous recombination pathway deficiencies (HRD positive cancers) and cancers without homologous recombination pathway deficiencies (HRD negative cancers) based on nucleic acid sequencing data, e.g., both RNA and DNA sequencing data, generated from a cancerous tissue sample of the subject.

Abstract: Disclosed herein are systems, methods, and compositions useful for determining cellular pathway disruption comprising the use of RNA expression level information. This determined level of disruption can assist in the identification of genetic variants that alter pathway activity, to correlate these variants with disease state and disease progression, and to identify those therapeutics most likely to be effective and which should be avoided.

Abstract: Methods, systems, and software are provided for an ensemble model trained to distinguish between cancers with homologous recombination pathway deficiencies (HRD positive cancers) and cancers without homologous recombination pathway deficiencies (HRD negative cancers) based on nucleic acid sequencing data, e.g., both RNA and DNA sequencing data, generated from a cancerous tissue sample of the subject.

Abstract: Systems and methods are provided for performing quality control analysis. The method obtains, in electronic form, a batch dataset comprising, for each respective sample in a batch of samples, a corresponding plurality of sequence reads derived from the respective sample by targeted or whole transcriptome RNA sequencing and corresponding metadata for the respective sample. The method determines for the batch dataset a cohort-matched reference batch, where the cohort-matched reference batch is balanced for tissue site, tumor purity, cancer type, sequencer identity, or date sequenced. The method performs one or more global batch quality control tests on the batch dataset using at least the cohort-matched reference batch. The method removes respective samples from the batch dataset that fail any one of the one or more global batch quality control tests or flagging for manual inspection respective samples that fail any one of the one or more global batch quality control tests.

Abstract: Methods, systems, and software are provided for determining a homologous recombination pathway status of a cancer in a test subject, e.g., to improve cancer treatment predictions and outcomes. In some embodiments, classifiers using one or more of (i) a heterozygosity status for DNA damage repair genes in a cancerous tissue, (ii) a measure of the loss of heterozygosity across the genome of the cancerous tissue, (iii) a measure of variant alleles detected in a second plurality of DNA damage repair genes in the genome of the cancerous tissue, (iv) a measure of variant alleles detected in the second plurality of DNA damage repair genes in the genome of a non-cancerous tissue, and (v) tumor sample purity are provided.

Abstract: Techniques for analysis of gene expression data contained in real world data and real word evidence for assessing biologic pathways for identifying molecular subtypes are provided. Systems and methods include, for a plurality of biological pathways, determining a pathway score using gene expression data and determining of summary score for the plurality of biological pathways. That summary score may be compared to one or more enrichment scores each associated with a pre-determined molecular subtype. A molecular subtype is determined based on that comparison. Various heuristics may be applied to filter pathways before summary scoring.

Abstract: Techniques are provided for replacing image assays using real world data and real word evidence RNA-seq analysis for assessing biologic pathways for identifying molecular subtypes. Systems of a methods diagnose HER2 status for a patient, by identifying discordant HER2 status result between the HER2 status from immunohistochemistry (IHC) and the HER2 status from fluorescence in-situ hybridization (FISH) and diagnosing HER2 status based gene expression data.

Abstract: Techniques for analysis of gene expression data contained in real world data and real word evidence for assessing biologic pathways for identifying molecular subtypes are provided. Systems and methods include, for a plurality of biological pathways, determining a pathway score using gene expression data and determining of summary score for the plurality of biological pathways. That summary score may be compared to one or more enrichment scores each associated with a pre-determined molecular subtype. A molecular subtype is determined based on that comparison. Various heuristics may be applied to filter pathways before summary scoring.

Abstract: Systems and methods are provided for performing quality control analysis. The method obtains, in electronic form, a batch dataset comprising, for each respective sample in a batch of samples, a corresponding plurality of sequence reads derived from the respective sample by targeted or whole transcriptome RNA sequencing and corresponding metadata for the respective sample. The method determines for the batch dataset a cohort-matched reference batch, where the cohort-matched reference batch is balanced for tissue site, tumor purity, cancer type, sequencer identity, or date sequenced. The method performs one or more global batch quality control tests on the batch dataset using at least the cohort-matched reference batch. The method removes respective samples from the batch dataset that fail any one of the one or more global batch quality control tests or flagging for manual inspection respective samples that fail any one of the one or more global batch quality control tests.

Abstract: Methods, systems, and software are provided for an ensemble model trained to distinguish between cancers with homologous recombination pathway deficiencies (HRD positive cancers) and cancers without homologous recombination pathway deficiencies (HRD negative cancers) based on nucleic acid sequencing data, e.g., both RNA and DNA sequencing data, generated from a cancerous tissue sample of the subject.

Abstract: Systems and methods are provided for determining a cancer type of a somatic tissue in a subject. A first plurality of sequence reads is obtained from a plurality of RNA molecules in a biopsy of the subject. A first set of sequence features comprising relative miRNA abundance values of genes is determined from the first plurality of sequence reads. Sequence features are applied to a classification model trained to distinguish between each cancer type in a set of at least 50 cancer types, thus determining the cancer type of the somatic tissue in the subject. The classification model provides an indication that the somatic tissue is or is not a respective cancer type, and the set of cancer types includes at least two cancer types from one or more classes of cancer selected from the group consisting of hematological cancers, squamous cancers, endometrial cancers, sarcoma cancers, and neuroendocrine cancers.

Abstract: Disclosed herein are systems, methods, and compositions useful for determining cellular pathway disruption comprising the use of RNA expression level information. This determined level of disruption can assist in the identification of genetic variants that alter pathway activity, to correlate these variants with disease state and disease progression, and to identify those therapeutics most likely to be effective and which should be avoided.

Abstract: Systems and methods are provided for identifying a diagnosis of a cancer condition for a somatic tumor specimen of a subject. The method receives sequencing information comprising analysis of a plurality of nucleic acids derived from the somatic tumor specimen. The method identifies a plurality of features from the sequencing information, including two or more of RNA, DNA, RNA splicing, viral, and copy number features. The method provides a first subset of features and a second subset of features from the identified plurality of features as inputs to a first classifier and a second classifier, respectively. The method generates, from two or more classifiers, two or more predictions of cancer condition based at least in part on the identified plurality of features. The method combines, at a final classifier, the two or more predictions to identify the diagnosis of the cancer condition for the somatic tumor specimen of the subject.

Abstract: Methods, systems, and software are provided for determining a homologous recombination pathway status of a cancer in a test subject, e.g., to improve cancer treatment predictions and outcomes. In some embodiments, classifiers using one or more of (i) a heterozygosity status for DNA damage repair genes in a cancerous tissue, (ii) a measure of the loss of heterozygosity across the genome of the cancerous tissue, (iii) a measure of variant alleles detected in a second plurality of DNA damage repair genes in the genome of the cancerous tissue, (iv) a measure of variant alleles detected in the second plurality of DNA damage repair genes in the genome of a non-cancerous tissue, and (v) tumor sample purity are provided.