期刊
NATURE METHODS
卷 14, 期 4, 页码 417-+出版社
NATURE PORTFOLIO
DOI: 10.1038/nmeth.4197
关键词
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资金
- Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative [GBMF4554]
- US National Science Foundation [CCF-1256087, CCF-1319998, BBSRC-NSF/BIO-1564917]
- US National Institutes of Health [R21HG006913, R01HG007104]
- NIH [5T32CA009337-35, HG005220]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [1564917] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1256087, 1319998] Funding Source: National Science Foundation
We introduce Salmon, a lightweight method for quantifying transcript abundance from RNA-seq reads. Salmon combines a new dual-phase parallel inference algorithm and feature-rich bias models with an ultra-fast read mapping procedure. It is the first transcriptome-wide quantifier to correct for fragment GC-content bias, which, as we demonstrate here, substantially improves the accuracy of abundance estimates and the sensitivity of subsequent differential expression analysis.
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