Article
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sRNAflow: A Tool for Analysis of Small RNA-Seq Data
Version 1
: Received: 29 December 2023 / Approved: 3 January 2024 / Online: 3 January 2024 (10:26:07 CET)
A peer-reviewed article of this Preprint also exists.
Zayakin, P. sRNAflow: A Tool for the Analysis of Small RNA-Seq Data. Non-Coding RNA 2024, 10, 6. Zayakin, P. sRNAflow: A Tool for the Analysis of Small RNA-Seq Data. Non-Coding RNA 2024, 10, 6.
Abstract
Аnalysis of small RNA sequencing data across a range of biofluids is a significant research area, given the diversity of RNA types that holds potential diagnostic, prognostic, and predictive value. The intricate task of segregating the complex mixture of small RNAs from both human and other species, including bacteria, fungi, and viruses, poses one of the most formidable challenges in the analysis of small RNA sequencing data, currently lacking satisfactory solutions. This study introduces sRNAflow, a user-friendly bioinformatic tool with a web interface designed for the analysis of small RNAs obtained from biological fluids. Tailored to the unique requirements of such samples, the proposed pipeline addresses various challenges, including filtering potential RNAs from reagents and environment, classifying small RNA types, managing small RNA annotation overlap, conducting differential expression assays, analysing isomiRs, and presenting an approach to identify the sources of small RNAs within samples. sRNAflow also encompasses an alternative alignment-free analysis of RNA-seq data, featuring clustering and initial RNA source identification using BLAST. This comprehensive approach facilitates meaningful comparisons of results between different analytical methods. The source code can be accessed at https://github.com/zajakin/sRNAflow under the GPL3 licence.
Keywords
bioinformatics; small RNA; microbiome; non-coding RNA; biofluids; miRNA; isomiR; tRF; biomarker; cancer biology
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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