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- W4311152530 abstract "Analysis of the expression activity of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. The nature of sRNA calls for bioinformatical approaches, adapted for the specific structure of the data. Despite a number of approaches proposed, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This article is dedicated to identifying the optimal pipeline configurations for each step of sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. For categorical factors and two groups of biosamples, we suggest approaches for the most crucial stages of sRNA analysis pipeline such as: (1) trimming with the lower length bound = 15 and the upper length bound = Readlength−40%Adapterlength; (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold &gt; 5; and (4) analyzing differential expression with DESeq2 with adjusted p-value &lt; 0.05 or limma with p-value &lt; 0.05 if there is very little signal and few transcripts." @default.
- W4311152530 created "2022-12-23" @default.
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- W4311152530 date "2022-12-09" @default.
- W4311152530 modified "2023-10-18" @default.
- W4311152530 title "Approaches for sRNA Analysis of RNA-seq Data: Comparison, Benchmarking" @default.
- W4311152530 doi "https://doi.org/10.20944/preprints202212.0177.v1" @default.
- W4311152530 hasPublicationYear "2022" @default.
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