RNA-MATE: a recursive mapping strategy for high-throughput RNA-sequencing data

Bioinformatics. 2009 Oct 1;25(19):2615-6. doi: 10.1093/bioinformatics/btp459. Epub 2009 Jul 30.

Abstract

Mapping of next-generation sequencing data derived from RNA samples (RNAseq) presents different genome mapping challenges than data derived from DNA. For example, tags that cross exon-junction boundaries will often not map to a reference genome, and the strand specificity of the data needs to be retained. Here we present RNA-MATE, a computational pipeline based on a recursive mapping strategy for placing strand specific RNAseq data onto a reference genome. Maximizing the mappable tags can provide significant savings in the cost of sequencing experiments. This pipeline provides an automatic and integrated way to align color-space sequencing data, collate this information and generate files for examining gene-expression data in a genomic context.

Availability: Executables, source code, and exon-junction libraries are available from http://grimmond.imb.uq.edu.au/RNA-MATE/

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Base Sequence
  • Computational Biology / methods*
  • Databases, Genetic
  • Sequence Analysis, RNA / methods*
  • Software*