CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data

Abstract

BackgroundmiRNAs play a key role in normal physiology and various diseases. miRNA profiling through next generation sequencing (miRNA-seq) has become the main platform for biological research and biomarker discovery. However, analyzing miRNA sequencing data is challenging as it needs significant amount of computational resources and bioinformatics expertise. Several web based analytical tools have been developed but they are limited to processing one or a pair of samples at time and are not suitable for a large scale study. Lack of flexibility and reliability of these web applications are also common issues.ResultsWe developed a Comprehensive Analysis Pipeline for microRNA Sequencing data (CAP-miRSeq) that integrates read pre-processing, alignment, mature/precursor/novel miRNA detection and quantification, data visualization, variant detection in miRNA coding region, and more flexible differential expression analysis between experimental conditions. According to computational infrastructure, users can install the package locally or deploy it in Amazon Cloud to run samples sequentially or in parallel for a large number of samples for speedy analyses. In either case, summary and expression reports for all samples are generated for easier quality assessment and downstream analyses. Using well characterized data, we demonstrated the pipeline’s superior performances, flexibility, and practical use in research and biomarker discovery.ConclusionsCAP-miRSeq is a powerful and flexible tool for users to process and analyze miRNA-seq data scalable from a few to hundreds of samples. The results are presented in the convenient way for investigators or analysts to conduct further investigation and discovery.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-423) contains supplementary material, which is available to authorized users.

MicroRNA and mRNA cargo of extracellular vesicles from porcine adipose tissue-derived mesenchymal stem cells

“…The mRNA-Seq data were analyzed using the MAPRSeq v.1.2.1 system for RNA-sequencing data analysis (http://bioinformaticstools.mayo.edu/research/maprseq/), the Bioinformatics Core standard tool, which includes alignment with TopHat 2.0.6 20, 21 and gene counts with the featureCounts software 22 . The miRNA-Seq data were analyzed using CAP-miRSeq v1.1 23 . Normalization and differential expression analysis were performed using edgeR 2.6.2 24 .…”

Integrated transcriptomic and proteomic analysis of the molecular cargo of extracellular vesicles derived from porcine adipose tissue-derived mesenchymal stem cells

“…Cells were sequenced on an Illumina HiSeq 2000 using TruSeq SBS kit version 3 and HCS v2.0.12 data collection software and data analyzed using the MAPRSeq v.1.2.1 system and the Bioinformatics Core standard tool, which includes alignment with TopHat 2.0.6 [17, 18] and gene counts with the featureCounts software [19]. miRNA-Seq data were analyzed using CAP-miRSeq v1.1 [20] and normalization and differential expression analysis performed using edgeR 2.6.2 [21]. Gene expression was normalized to 1 million reads and corrected for gene length (reads per kilobasepair per million mapped reads, RPKM), and miRNA expression levels expressed as normalized total reads.…”

1α,25-Dihydroxyvitamin D3 Regulates Mitochondrial Oxygen Consumption and Dynamics in Human Skeletal Muscle Cells

“…miRNA-seq Data Analysis-miRNA-seq data were processed with a microRNA deep sequencing analysis workflow called CAP-miRSeq version 1.1 (46). This workflow provides comprehensive analysis of miRNA sequencing data, including read preprocessing, alignment, mature/precursor/novel miRNA quantification, and variant detection in the miRNA coding region.…”