Machine learning for somatic single nucleotide variant detection in cell-free tumor nucleic acid sequencing applications
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United States of America Patent
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Dec 13, 2022
Grant Date -
Aug 26, 2021
app pub date -
Feb 17, 2021
filing date -
Sep 2, 2015
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Abstract
Systems and methods are disclosed to detect single-nucleotide variations (SNVs) from somatic sources in a cell-free biological sample of a subject by generating training data with class labels; in computer memory, generating a machine learning unit comprising one output for each of adenine (A), cytosine (C), guanine (G), and thymine (T) calls; training the machine learning unit; and applying the machine learning unit to detect the SNVs from somatic sources in the cell-free biological sample of the subject, wherein the cell-free biological sample comprises a mixture of nucleic acid molecules from somatic and germline sources.
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