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


ABSTRACT:

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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 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/

SUBMITTER: Cloonan N 

PROVIDER: S-EPMC2752615 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Publications

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

Cloonan Nicole N   Xu Qinying Q   Faulkner Geoffrey J GJ   Taylor Darrin F DF   Tang Dave T P DT   Kolle Gabriel G   Grimmond Sean M SM  

Bioinformatics (Oxford, England) 20090730 19


<h4>Unlabelled</h4>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 mappa  ...[more]

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