PASSion uses the mapped read in a pair as anchor and then uses a high resolution algorithm, pattern growth, to remap the proximal and distal fragments of the unmapped read to a local region of the reference indicated by the mate. It is capable of identifying both known and novel canonical and non-canonical junctions with SNP or sequencing error tolerance. In addition, our package can discover differential and shared splicing patterns among multiple samples.
The performance of PASSion is not affected by read length and coverage and it performs better than TopHat, MapSplice and HMMSplicer when detecting junctions in highly abundant transcripts. PASSion has the ability to detect junctions that do not have known splicing motifs, which cannot be found by the other tools.
Of two public RNA-Seq data sets, PASSion predicted around 137,000 and 173,000 splicing events, of which on average 82% are known junctions annotated in the Ensembl transcript database and 18% are novel. In addition, Our package can discover differential and shared splicing patterns among multiple samples.
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- Zhang Y, Lameijer EW, ‘t Hoen PA, Ning Z, Slagboom PE, Ye K. (2012) PASSion: A Pattern Growth Algorithm Based Pipeline for Splice Junction Detection in Paired-end RNA-Seq Data. Bioinformatics[Epub ahead of print]. [abstract]