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STAR: ultrafast universal RNA-seq aligner
Alexander Dobin, Carrie Davis, Felix Schlesinger, Jörg Drenkow, Chris Zaleski, Sonali Jha, Philippe J. Batut, Mark Chaisson, T Gingeras. Bioinformatics, 2012-10-25
Topic: Brain proteins, microglia and lab models
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 × 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/.
Why it matters
Describes STAR, free open-source software for aligning RNA sequencing data. The authors report it maps reads more than 50 times faster than other aligners while improving sensitivity and precision.
How this study scored 56/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on strength of evidence, so that was left out: it earned 53 of the 95 points we could judge it on, which is 56 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Bioinformatics) |
| Journal's citation record | 4 / 4 | Bioinformatics: journal h-index 560 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | — / 5 | No evidence rating recorded — left out of this score |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2012 — within 20 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 7 / 7 | Cited 51,973 times (OpenAlex, 2026-10-10) |
| Citations per year | 5 / 5 | 3,248.3 citations a year over 16 year(s) since 2012 |
| Impact for its field and year | 6 / 6 | Cited 73.9× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 4 / 4 | Cited 20,189 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author T Gingeras: h-index 96 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Cold Spring Harbor Laboratory: institution h-index 1,013 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 23104886) |
| Free to read | 2 / 2 | Free to read |
| Points | 53 / 95 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 53 of the 95 points we could judge it on is 56 out of 100. |
| Total | 56 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1093/bioinformatics/bts635
- PubMed: 23104886
- Original source →
- Free full text: PubMed Central →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record names 9 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Dobin, A., Davis, C., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., et al. (2012). STAR: ultrafast universal RNA-seq aligner. Bioinformatics. https://doi.org/10.1093/bioinformatics/bts635
Vancouver
Dobin A, Davis C, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2012. doi:10.1093/bioinformatics/bts635. PMID: 23104886.
BibTeX
@article{dobin2012-23104886,
author = {Dobin, Alexander and Davis, Carrie and Schlesinger, Felix and Drenkow, Jörg and Zaleski, Chris and Jha, Sonali and Batut, Philippe J. and Chaisson, Mark and Gingeras, T},
title = {{STAR: ultrafast universal RNA-seq aligner}},
journal = {Bioinformatics},
year = {2012},
doi = {10.1093/bioinformatics/bts635},
pmid = {23104886},
url = {https://doi.org/10.1093/bioinformatics/bts635}
}