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

• Published in: Bioinformatics 2009-10, Vol.25 (19), p.2615-2616
• Main Authors: Cloonan, Nicole, Xu, Qinying, Faulkner, Geoffrey J., Taylor, Darrin F., Tang, Dave T. P., Kolle, Gabriel, Grimmond, Sean M.
• Format: Article
• Language: English
• Subjects: Applications Note; Base Sequence; Biological and medical sciences; Computational Biology - methods; Databases, Genetic; Fundamental and applied biological sciences. Psychology; General aspects; Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects); Sequence Analysis, RNA - methods; Software
• ISSN: 1367-4803; 1460-2059; 1367-4811
• DOI: 10.1093/bioinformatics/btp459

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/ Contact: [e-mail] Supplementary information: Supplementary data are available at Bioinformatics Online.