{"doi":"10.1093/bioinformatics/bts635","title":"STAR: ultrafast universal RNA-seq aligner","abstract":"<jats:title>Abstract</jats:title>\n                  <jats:p>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.</jats:p>\n                  <jats:p>Results: To align our large (&amp;gt;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 &amp;gt;50 in mapping speed, aligning to the human genome 550 million 2 × 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.</jats:p>\n                  <jats:p>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/.</jats:p>\n                  <jats:p>Contact:  dobin@cshl.edu.</jats:p>","journal":"Bioinformatics","year":2013,"id":12777,"datarank":23.266142259184896,"base_score":10.918772578614485,"endowment":10.918772578614485,"self_citation_contribution":1.637815886792173,"citation_network_contribution":21.628326372392724,"self_endowment_contribution":1.637815886792173,"citer_contribution":21.628326372392724,"corpus_percentile":99.5,"corpus_rank":55,"citation_count":55202,"citer_count":199,"citers_with_citation_signal":199,"citers_with_endowment":199,"datacite_reuse_total":0,"is_dataset":false,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2013-01-01","authors":[],"reference_count":22,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}