Journal
BIOINFORMATICS
Volume 25, Issue 19, Pages 2615-2616Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btp459
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Funding
- National Health and Medical Research Council [455857, 456140]
- Australian Research Council [DP0988754]
- Australian Stem Cell Centre
- University of Queensland
- Australian Research Council [DP0988754] Funding Source: Australian Research Council
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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 colorspace sequencing data, collate this information and generate files for examining gene-expression data in a genomic context.
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