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Anti-bias training for (sc)RNA-seq : experimental and computational approaches to improve precision
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Davies, Philip, Jones, Matt, Liu, Juntai and Hebenstreit, Daniel (2021) Anti-bias training for (sc)RNA-seq : experimental and computational approaches to improve precision. Briefings in Bioinformatics, 22 (6). bbab148. doi:10.1093/bib/bbab148 ISSN 1467-5463.
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Official URL: https://doi.org/10.1093/bib/bbab148
Abstract
RNA-seq, including single cell RNA-seq (scRNA-seq), is plagued by insufficient sensitivity and lack of precision. As a result, the full potential of (sc)RNA-seq is limited. Major factors in this respect are the presence of global bias in most datasets, which affects detection and quantitation of RNA in a length-dependent fashion. In particular, scRNA-seq is affected by technical noise and a high rate of dropouts, where the vast majority of original transcripts is not converted into sequencing reads. We discuss these biases origins and implications, bioinformatics approaches to correct for them, and how biases can be exploited to infer characteristics of the sample preparation process, which in turn can be used to improve library preparation.
Item Type: | Journal Article | |||||||||||||||
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Subjects: | Q Science > QH Natural history Q Science > QP Physiology |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Physics |
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Library of Congress Subject Headings (LCSH): | RNA, Nucleotide sequence, Gene expression, Bioinformatics -- Software | |||||||||||||||
Journal or Publication Title: | Briefings in Bioinformatics | |||||||||||||||
Publisher: | Oxford University Press | |||||||||||||||
ISSN: | 1467-5463 | |||||||||||||||
Official Date: | November 2021 | |||||||||||||||
Dates: |
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Volume: | 22 | |||||||||||||||
Number: | 6 | |||||||||||||||
Article Number: | bbab148 | |||||||||||||||
DOI: | 10.1093/bib/bbab148 | |||||||||||||||
Status: | Peer Reviewed | |||||||||||||||
Publication Status: | Published | |||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | |||||||||||||||
Date of first compliant deposit: | 30 March 2021 | |||||||||||||||
Date of first compliant Open Access: | 24 May 2021 | |||||||||||||||
RIOXX Funder/Project Grant: |
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