Grail, Inc.

Pranav Parmjit Singh

Onur Sakarya

Xiao Yang

Samuel S Gross

Oliver Claude Venn

Matthew H Larson

Robert Abe Paine Calef

Hyunsung John Kim

Wenying Pan

Collin Melton

Joshua Newman

Eric Michael Scott

Mohini Jangi Desai

Christopher-James AV Yakym

Richard Huang

Systems and methods for cancer subject tumor fraction estimation comprise obtaining a first plurality of nucleic acid fragment sequences from the subject's liquid biological sample. The first plurality of sequences represent cell-free nucleic acids in the liquid sample. A second plurality of nucleic acid fragment sequences is obtained from the subject's tumor sample. The second plurality of sequences represent nucleic acid molecules in the tumor. Smoothed noise rates, each determined using nucleic acid fragment sequences from non-cancer samples mapping to a corresponding allele position in a plurality of allele positions, are obtained. Variant allele counts and coverages are determined for the allele positions using the first plurality of sequences. Solid variant allele fractions are determined for the plurality of allele positions using the second plurality of sequences. The subject tumor fraction is calculated using the smoothed noise rates, variant allele counts, coverages, and solid variant allele fractions.

Systems and methods for tumor fraction estimation from small variants

Cell free nucleic acids from a test sample obtained from an individual are analyzed to identify possible fusion events. Cell free nucleic acids are sequenced and processed to generate fragments. Fragments are decomposed into kmers and the kmers are either analyzed de novo or compared to targeted nucleic acid sequences that are known to be associated with fusion gene pairs of interest. Thus, kmers that may have originated from a fusion event can be identified. These kmers are consolidated to generate gene ranges from various genes that match sequences in the fragment. A candidate fusion event can be called given the spanning of one or more gene ranges across the fragment.

Alignment free filtering for identifying fusions

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Mountain View, CA, United States of America

Pranav Parmjit Singh