Abstract: This disclosure describes methods, non-transitory computer readable media, and systems that can determine allele likelihoods of a genomic region exhibiting certain haplotype alleles using one or both of consolidated computations and data exchanges across specialized hardware. For instance, the disclosed systems can determine an intermediate allele likelihood of a genomic region comprising a haplotype allele by running a single-pass-concurrent-multiplication operation. In some cases, the disclosed systems determine and store subsets of intermediate allele likelihoods corresponding to marker-variant groups and extemporaneously generate sets of intermediate allele likelihoods for a set of marker variants by using the intermediate-allele-likelihood subsets as hot-start points.

Abstract: Disclosed herein are systems and methods for collapsing sequencing reads and identifying similar sequencing reads. In one example, a method includes generating a plurality of first identifier subsequences from a first identifier sequence of each nucleotide sequencing read and generating a first signature for the nucleotide sequencing read by applying hashing to the plurality of first identifier subsequences. The method may include assigning the nucleotide sequencing read to a first particular bin of a first data structure based on the first signature and determining a nucleotide sequence for each first particular bin of the first data structure with one or more nucleotide sequencing reads assigned.

Abstract: A nucleic acid sequencing technique is described. Sequence data, e.g., generated by a sequencing device, may be analyzed to scan k-mers of a fixed size n in individual reads in the sequence data. Exact matches of the k-mers in the sequence data with reference k-mers are identified. K-mer matching may be used to identify alternative alleles in sequence data with anomalous distribution associated with contamination or other quality issues and to determine a quality metric in real-time.

Abstract: Disclosed herein are systems and methods for collapsing sequencing reads and identifying similar sequencing reads. In one example, a method includes generating a plurality of first identifier subsequences from a first identifier sequence of each nucleotide sequencing read and generating a first signature for the nucleotide sequencing read by applying hashing to the plurality of first identifier subsequences. The method may include assigning the nucleotide sequencing read to a first particular bin of a first data structure based on the first signature and determining a nucleotide sequence for each first particular bin of the first data structure with one or more nucleotide sequencing reads assigned.

Abstract: A nucleic acid sequencing technique is described. Sequence data, e.g., generated by a sequencing device, may be analyzed to scan k-mers of a fixed size n in individual reads in the sequence data. Exact matches of the k-mers in the sequence data with reference k-mers are identified. The number of exact matches, their distribution in a reference genome, and/or a number of sequence reads in the sequence data that map to different target regions can be used to determine a characteristic of a sample. In one example, the characteristic is a presence of a pathogen in the sample.

Abstract: Disclosed herein are systems and methods for collapsing sequencing reads and identifying similar sequencing reads. In one example, a method includes generating a plurality of first identifier subsequences from a first identifier sequence of each nucleotide sequencing read and generating a first signature for the nucleotide sequencing read by applying hashing to the plurality of first identifier subsequences. The method may include assigning the nucleotide sequencing read to a first particular bin of a first data structure based on the first signature and determining a nucleotide sequence for each first particular bin of the first data structure with one or more nucleotide sequencing reads assigned.

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.