DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification

Genes (Basel). 2020 Dec 30;12(1):46. doi: 10.3390/genes12010046.

Abstract

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

Keywords: NGS; analysis; bioinformatics; expression; microRNA; pipeline; quantification; small RNA-Seq.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Benchmarking
  • Computational Biology / methods*
  • Data Mining / methods
  • Databases, Genetic
  • Gene Expression Regulation
  • Gene Library
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Mice
  • MicroRNAs / classification
  • MicroRNAs / genetics*
  • MicroRNAs / metabolism
  • Sequence Analysis, RNA / methods*
  • Sequence Analysis, RNA / statistics & numerical data
  • Software*

Substances

  • MicroRNAs