SRNAnalyzer—a flexible and customizable small RNA sequencing data analysis pipeline. Issue 21 (24th October 2017)

• Record Type: Journal Article
• Authors: Wu, Xiaogang; Kim, Taek-Kyun; Baxter, David; Scherler, Kelsey; Gordon, Aaron; Fong, Olivia; Etheridge, Alton; Galas, David J.; Wang, Kai
• Is Part Of: Nucleic acids research. Volume 45:Issue 21(2017)
• Page Start: 12140
• Page End: 12151
• Publication Date: 2017-10-24
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx999
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Although many tools have been developed to analyze small RNA sequencing (sRNA-Seq) data, it remains challenging to accurately analyze the small RNA population, mainly due to multiple sequence ID assignment caused by short read length. Additional issues in small RNA analysis include low consistency of microRNA (miRNA) measurement results across different platforms, miRNA mapping associated with miRNA sequence variation (isomiR) and RNA editing, and the origin of those unmapped reads after screening against all endogenous reference sequence databases. To address these issues, we built a comprehensive and customizable sRNA-Seq data analysis pipeline— sRNAnalyzer, which enables: (i) comprehensive miRNA profiling strategies to better handle isomiRs and summarization based on each nucleotide position to detect potential SNPs in miRNAs, (ii) different sequence mapping result assignment approaches to simulate results from microarray/qRT-PCR platforms and a local probabilistic model to assign mapping results to the most-likely IDs, (iii) comprehensive ribosomal RNA filtering for accurate mapping of exogenous RNAs and summarization based on taxonomy annotation. We evaluated our pipeline on both artificial samples (including synthetic miRNA and Escherichia coli cultures) and biological samples (human tissue and plasma). sRNAnalyzer is implemented in Perl and available at: http://srnanalyzer.systemsbiology.net/ .