A deep learning approach to automate refinement of somatic variant calling from cancer sequencing da...
A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data
About this item
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Publisher
New York: Nature Publishing Group US
Journal title
Language
English
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Publisher
New York: Nature Publishing Group US
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Scope and Contents
Contents
Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consuming, costly, poorly standardized, and non-reproducible. Here, we systematized and standardized somatic...
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Full title
A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data
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Record Identifier
TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6428590
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6428590
Other Identifiers
ISSN
1061-4036
E-ISSN
1546-1718
DOI
10.1038/s41588-018-0257-y
