MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning.
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ABSTRACT:
SUBMITTER: Li C
PROVIDER: S-EPMC9548151 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
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MetaRNN: differentiating rare pathogenic and rare benign missense SNVs and InDels using deep learning.
Li Chang C Zhi Degui D Wang Kai K Liu Xiaoming X
Genome medicine 20221008 1
Multiple computational approaches have been developed to improve our understanding of genetic variants. However, their ability to identify rare pathogenic variants from rare benign ones is still lacking. Using context annotations and deep learning methods, we present pathogenicity prediction models, MetaRNN and MetaRNN-indel, to help identify and prioritize rare nonsynonymous single nucleotide variants (nsSNVs) and non-frameshift insertion/deletions (nfINDELs). We use independent test sets to de ...[more]
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