CBS-miRSeq: A comprehensive tool for accurate and extensive analyses of microRNA-sequencing data

Research output: Contribution to journalArticlepeer-review


Several online and local tools have been developed to analyze microRNA-sequencing (miRNA-Seq) data, but usually they are limited by many factors including: inaccurate processing, lack of optimal parameterization, outdated references plus annotations, restrictions in uploading large datasets, and shortage of biological inferences. In this work, we have developed a fully customized bioinformatics analysis pipeline (Color and Base-Space miRNA-Seq – CBS-miRSeq) for the seamless processing of short-reads miRNA-Seq data. The pipeline has been designed using Bash, Perl, and R scripts. CBS-miRSeq includes modules for read pre- and post-processing (quality assessment, filtering, adapter trimming and mapping) and different types of downstream analyses (identification of miRNA variants (isomiRs), novel miRNA prediction, miRNA:mRNA interaction target prediction, robust differential miRNA analysis, and target gene functional analysis). In this manuscript, we show that re-analysis of two published datasets using the CBS-miRSeq pipeline leads to better performance and efficiency in terms of their pipelines set and biomarker discovery between two biological conditions.

Original languageEnglish
Pages (from-to)234-243
Number of pages10
JournalComputers in Biology and Medicine
Publication statusPublished - Jul 2019


  • Base-space
  • Bioinformatics pipeline
  • Color-space
  • Gene expression profiling
  • microRNA

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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