CPSS: a computational platform for the analysis of small RNA deep sequencing data

UNLABELLED Next generation sequencing (NGS) techniques have been widely used to document the small ribonucleic acids (RNAs) implicated in a variety of biological, physiological and pathological processes. An integrated computational tool is needed for handling and analysing the enormous datasets from small RNA deep sequencing approach. Herein, we present a novel web server, CPSS (a computational platform for the analysis of small RNA deep sequencing data), designed to completely annotate and functionally analyse microRNAs (miRNAs) from NGS data on one platform with a single data submission. Small RNA NGS data can be submitted to this server with analysis results being returned in two parts: (i) annotation analysis, which provides the most comprehensive analysis for small RNA transcriptome, including length distribution and genome mapping of sequencing reads, small RNA quantification, prediction of novel miRNAs, identification of differentially expressed miRNAs, piwi-interacting RNAs and other non-coding small RNAs between paired samples and detection of miRNA editing and modifications and (ii) functional analysis, including prediction of miRNA targeted genes by multiple tools, enrichment of gene ontology terms, signalling pathway involvement and protein-protein interaction analysis for the predicted genes. CPSS, a ready-to-use web server that integrates most functions of currently available bioinformatics tools, provides all the information wanted by the majority of users from small RNA deep sequencing datasets. AVAILABILITY CPSS is implemented in PHP/PERL+MySQL+R and can be freely accessed at http://mcg.ustc.edu.cn/db/cpss/index.html or http://mcg.ustc.edu.cn/sdap1/cpss/index.html.

[1]  Yu Xue,et al.  Prediction of novel pre-microRNAs with high accuracy through boosting and SVM , 2011, Bioinform..

[2]  Yanqing Wang,et al.  Bioinformatics Applications Note Databases and Ontologies Waprna: a Web-based Application for the Processing of Rna Sequences , 2022 .

[3]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[4]  Christian von Mering,et al.  STRING 8—a global view on proteins and their functional interactions in 630 organisms , 2008, Nucleic Acids Res..

[5]  Gang Xu,et al.  mirTools: microRNA profiling and discovery based on high-throughput sequencing , 2010, Nucleic Acids Res..

[6]  F. Zhao,et al.  Small RNA transcriptome investigation based on next-generation sequencing technology. , 2011, Journal of genetics and genomics = Yi chuan xue bao.

[7]  Susumu Goto,et al.  KEGG for representation and analysis of molecular networks involving diseases and drugs , 2009, Nucleic Acids Res..

[8]  E. Sontheimer,et al.  Origins and Mechanisms of miRNAs and siRNAs , 2009, Cell.

[9]  D. Moazed Small RNAs in transcriptional gene silencing and genome defence , 2009, Nature.

[10]  Xavier Estivill,et al.  SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells , 2009, Nucleic acids research.

[11]  Hsien-Da Huang,et al.  miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression , 2009, BMC Bioinformatics.

[12]  Peter F. Stadler,et al.  DARIO: a ncRNA detection and analysis tool for next-generation sequencing experiments , 2011, Nucleic Acids Res..

[13]  N. Rajewsky,et al.  Discovering microRNAs from deep sequencing data using miRDeep , 2008, Nature Biotechnology.

[14]  Ana M. Aransay,et al.  miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments , 2009, Nucleic Acids Res..