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


BACKGROUND
Executables, source code, and exon-junction libraries are available from http://grimmond.imb.uq.edu.au/RNA-MATE/
Cloonan
Nicole
N
Queensland Centre for Medical Genomics, Institute for Molecular Bioscience, The University of Queensland, St. Lucia 4072, Australia. n.cloonan@imb.uq.edu.au
Xu
Qinying
Q
Faulkner
Geoffrey J
GJ
Taylor
Darrin F
DF
Tang
Dave T P
DT
Kolle
Gabriel
G
Grimmond
Sean M
SM
D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D017423:Sequence Analysis, RNA / Q000379:methods*; D012984:Software