Abstract: Disclosed herein include systems, machines, devices, and methods for single-pass methylation mapping. C-to-T converted sequence reads and G-to-A converted sequence reads generated from a sample subjected to a methylation assay can be mapped to a mapping reference sequence comprising a C-to-T converted reference sequence and a G-to-A converted reference sequence generated to a reference genome sequence. The counts of Cs and Ts of sequence reads mapped to each of one or more positions with Cs in the reference genome sequence can be used to determine whether the position is a methylated C or an unmethylated C in the sample.

Abstract: Methods, systems, and apparatuses, including computer programs for identifying a gene fusion in a biological sample is disclosed. The method can include actions of obtaining first data that represents a plurality of aligned reads, identifying a plurality of fusion candidates included within the obtained first data, filtering the plurality of fusion candidates to determine a filtered set of fusion candidates, for each particular fusion candidate of the filtered set of fusion candidates: generating, by one or more computers, input data for input to a machine learning model that includes extracted feature data that to represents the particular fusion candidate, providing the generated input data as an input to the machine learning model that has been trained to generate output data representing a likelihood that a fusion candidate is a valid gene fusion, and determining whether the particular fusion candidate corresponds to a valid gene fusion based on the output data.

Abstract: A “dynamic” reference is presented that utilizes population level information to improve reference-based alignment to detect novel, deleterious, or functional variants in clinical sequencing applications. An automatically updated database of known genetic variants is provided to a memory connected with an integrated circuit configured for genetic sequence data with the dynamic reference and reference variants.

Abstract: A “dynamic” reference is presented that utilizes population level information to improve reference-based alignment to detect novel, deleterious, or functional variants in clinical sequencing applications. An automatically updated database of known genetic variants is provided to a memory connected with an integrated circuit configured for genetic sequence data with the dynamic reference and reference variants.

Abstract: A “dynamic” reference is presented that utilizes population level information to improve reference-based alignment to detect novel, deleterious, or functional variants in clinical sequencing applications. An automatically updated database of known genetic variants is provided to a memory connected with an integrated circuit configured for genetic sequence data with the dynamic reference and reference variants.