STAR

MOTIVATION: Accurate alignment of high-throughput RNA-seq data is a challenging
and yet unsolved problem because of the non-contiguous transcript structure,
relatively short read lengths and constantly increasing throughput of the
sequencing technologies. Currently available RNA-seq aligners suffer from high
mapping error rates, low mapping speed, read length limitation and mapping
biases. RESULTS: To align our large (>80 billon reads) ENCODE Transcriptome
RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference
(STAR) software based on a previously undescribed RNA-seq alignment algorithm
that uses sequential maximum mappable seed search in uncompressed suffix arrays
followed by seed clustering and stitching procedure. STAR outperforms other
aligners by a factor of >50 in mapping speed, aligning to the human genome 550
million 2 x 76 bp paired-end reads per hour on a modest 12-core server, while at
the same time improving alignment sensitivity and precision. In addition to
unbiased de novo detection of canonical junctions, STAR can discover
non-canonical splices and chimeric (fusion) transcripts, and is also capable of
mapping full-length RNA sequences. Using Roche 454 sequencing of reverse
transcription polymerase chain reaction amplicons, we experimentally validated
1960 novel intergenic splice junctions with an 80-90% success rate, corroborating
the high precision of the STAR mapping strategy. AVAILABILITY AND IMPLEMENTATION:
STAR is implemented as a standalone C++ code. STAR is free open source software
distributed under GPLv3 license and can be downloaded from
http://code.google.com/p/rna-star/.

STAR: ultrafast universal RNA-seq aligner.

A tool to align RNA-seq data. The STAR algorithm uses suffix arrays, seed clustering, and stitching. It can detect non-canonical splice sites, chimeric sequences, and can also map full-length RNA sequences.

STAR

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