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

by: Nicole Cloonan, Qinying Xu, Geoffrey J. Faulkner, Darrin F. Taylor, Dave T. P. Tang, Gabriel Kolle, Sean M. Grimmond
Bioinformatics, Vol. 25, No. 19. (1 October 2009), pp. 2615-2616, doi:10.1093/bioinformatics/btp459  Key: citeulike:5308811

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Abstract

Summary: 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: n.cloonan@imb.uq.edu.auSupplementary information: Supplementary data are available at Bioinformatics Online.


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