Abstract: Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from training subjects and their a responsiveness to checkpoint inhibition treatment and the machine-learning classifier is trained to predict responsiveness to the treatment, and generating a checkpoint inhibition responsiveness classification predictive of the subject's responding to the checkpoint inhibition with the trained machine-learning classifier, and reporting the checkpoint inhibition responsiveness classification using a graphical user interface. Also provided are a computer system for performing the method and a machine learning classifier trained by the method.

Abstract: A potential prognostic biomarker is based on a combination of a composite score generated by sequence analysis of global human endogenous retrovirus (hERV)/retro-transposon transactivation and a cell signature generated using deconvolution of immune cells within a tumor sample for predicting the efficacy of chemotherapeutic agents and immune checkpoint inhibitors. Correlation analysis of the composite score with cell signature within a tumor sample enables survival analysis in individuals receiving chemotherapeutic agents and immune checkpoint inhibitors.

Abstract: Presented herein are methods and compositions for determining MSI status and LS screening in a single test of colorectal cancer tissue. Also presented herein are methods for determining MSI status in a sample of cell-free DNA obtained from blood obtained from a cancer patient.

Abstract: Provided herein are systems and methods for quantitating the HLA diversity in a solid tissue or circulating tumor DNA sample that is predictive of a patient's responsiveness to immune checkpoint inhibitory therapies.

Abstract: Provided is a computer-implemented method, including inputting to a trained machine learning classifier genomic information of a non-training subject that includes features from a tumor sample, wherein the trained machine learning classifier trained on features of tumor samples obtained from training subjects and their a responsiveness to checkpoint inhibition treatment and the machine-learning classifier is trained to predict responsiveness to the treatment, and generating a checkpoint inhibition responsiveness classification predictive of the subject's responding to the checkpoint inhibition with the trained machine-learning classifier, and reporting the checkpoint inhibition responsiveness classification using a graphical user interface. Also provided are a computer system for performing the method and a machine learning classifier trained by the method.

Abstract: Methods and systems are provided for validating variant calls. Sequencing data is received for a sample read along the genomic sequence of interest. An indication is received of a potential variant call at a designated position within the sequence of nucleotides along the genomic sequence of interest. The methods and systems obtain baseline variant frequencies at the designated position within one or more baseline genomic sequences, determine a sample variant frequency at the designated position for the genomic sequence of interest, analyze the baseline and sample variant frequencies at the designated position to obtain a quality score, and validate the potential variant call for the genomic sequence of interest based on the quality score.

Abstract: Presented herein are techniques for determining microsatellite instability. The techniques include generating a reference sample dataset representative of or mimicking a hypothetical matched sample for an individual sample of interest. The reference sample dataset may be generated from a set of reference normal samples that are not matched to the sample of interest. For samples of interest lacking a matched sample, the reference sample dataset may be used to determine microsatellite instability and to provide an indication of a presence, absence, or degree of microsatellite instability of the sample of interest. The reference sample dataset may be generated such that individual microsatelliate regions associated with a high degree of variability between ethnic groups are filtered out, masked, or otherwise not considered.

Abstract: Methods, compositions, and devices are disclosed which use microRNA to detect, predict, treat, and monitor physiological conditions such as disease or injury. microRNA are isolated and their differential expression is measured to provide diagnostic information. This information may then be utilized for evaluation and/or treatment purposes.

Abstract: Improved methods to quantitate RNA in biological or other analytical samples employ extended RNAs containing adaptors at the 5? end and polyA sequences coupled to a tag at the 3? end. The invention method is particularly useful in quantitating microRNAs as primers can be used that need not complement the non-conserved 3? ends of these molecules.

Abstract: Methods, compositions, and devices are disclosed which use microRNA to detect, predict, treat, and monitor physiological conditions such as disease or injury. microRNA are isolated and their differential expression is measured to provide diagnostic information. This information may then be utilized for evaluation and/or treatment purposes.

Abstract: Methods, compositions, and devices are disclosed which use microRNA to detect, predict, treat, and monitor physiological conditions such as disease or injury. microRNA are isolated and their differential expression is measured to provide diagnostic information. This information may then be utilized for evaluation and/or treatment purposes.

Abstract: Improved methods to quantitate RNA in biological or other analytical samples employ extended RNAs containing adaptors at the 5? end and polyA sequences coupled to a tag at the 3? end. The invention method is particularly useful in quantitating microRNAs as primers can be used that need not complement the non-conserved 3? ends of these molecules.

Abstract: Methods, compositions, and devices are disclosed which use microRNA to detect, predict, treat, and monitor physiological conditions such as disease or injury. microRNA are isolated and their differential expression is measured to provide diagnostic information. This information may then be utilized for evaluation and/or treatment purposes.