Abstract: This disclosure describes methods, non-transitory computer-readable media, and systems that can (i) identify reads that align with at least some portion of alternative contiguous sequences representing structural variant haplotypes within a structural variant reference genome and (ii) generate a structural-variant-alignment tag within an alignment file for such read alignments to guide identifying candidate structural-variant locations. In addition to employing structural-variant-alignment tags, the disclosed systems identify read fragments that align or overlap with portions of alternate contiguous sequences representing an insertion (or other structural variant) and further masks such insertion-overlapping read fragments as part of an alignment file.

Abstract: Improved copy number variant (CNV) calling in a genomic sequence, and potential recovery, includes (i) obtaining genetic sequence variant data that includes records indicating structural variant(s) (SVs) and records indicating CNV(s) in the genomic sequence, (ii) determining, based on an initial CNV indicated in the genetic sequence variant data and on initial SV(s) indicated in the genetic sequence variant data, an SV-informed CNV call as an updated version of the initial CNV, where the determining uses information from the initial SV(s) to determine a start breakpoint position and an end breakpoint position for the SV-informed CNV call, at least one of the start breakpoint position and end breakpoint position being updated, informed by the initial SV(s), in comparison to a corresponding start breakpoint position and/or end breakpoint position of the initial CNV, and (ii) writing the determined SV-informed CNV call as record(s) in a genetic sequence variant data file.

Abstract: This disclosure describes methods, non-transitory-computer readable media, and systems that can use a single executable file to run a single-cell multiomics analysis that (i) aligns multiomics reads with a reference genome and (ii) jointly filters cellular barcode sequences for cells based on feature-specific, single-cell read counts. To run such an assay, the disclosed systems identify transcriptomic reads and genomic reads for a sample, where such reads comprise different sets of cellular barcode sequences. In some cases, the disclosed systems further use separate invocations of a configurable processor to align the transcriptomic reads and genomics reads with a reference genome. Based on single-cell counts of aligned transcriptomic reads and aligned genomic reads for target nucleotide sequences, the disclosed systems select a subset of candidate cells corresponding to a subset of cellular barcode sequences.

Abstract: This disclosure describes methods, non-transitory computer readable media, and systems that can generate a structural variation graph genome with alternate contiguous sequences representing structural variant haplotypes. For instance, the disclosed systems can identify candidate structural variants that satisfy an occurrence threshold within a genomic sample database. From among the candidate structural variants, the systems select structural variant haplotypes based on one or both of the structural variant haplotypes satisfying a relative haplotype frequency and finding flanking variants adjacent to particular structural variant haplotypes. The systems can likewise select reference haplotypes corresponding to the selected structural variant haplotypes from a reference genome.

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: Adaptive path selection for interference cancellation is provided for wireless communication devices. Signal strength metrics are obtained for each of multiple signal paths. One or more of the signal paths are selected as cancellation candidates in response to determining that the signal paths are associated with a strong interfering path based at least in part on the signal strength metrics for the signal paths and threshold criteria. Cancellation is enabled for an estimated signal generated using the signal paths in response to the signal paths being selected as cancellation candidates.

Abstract: Disclosed are various embodiments providing adaptive path selection for interference cancellation for wireless communication devices. Signal strength metrics are obtained for each of multiple signal paths. One or more of the signal paths are selected as cancellation candidates in response to determining that the signal paths are associated with a strong interfering path based at least in part on the signal strength metrics for the signal paths and threshold criteria. Cancellation is enabled for an estimated signal generated using the signal paths in response to the signal paths being selected as cancellation candidates.