TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions.
Open accessAbstract
TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat .
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Spliced read aligners Tophat, STAR and HISAT2 have successfully been used for allele-specific alignments in conjunction with SNPsplit.
“Spliced read aligners that have successfully been used for allele-specific alignments in conjunction with SNPsplit include Tophat 18, STAR 14 (Spliced Transcripts Alignment to a Reference) and HISAT2 13.”
From SNPsplit: Allele-specific splitting of alignments between genomes with known SNP genotypes (2016) · cites this paper as [18]
The Background describes TopHat2 as a spliced-read aligner, and the Results and discussion report successful spliced-read alignments. The cited paper does not establish that TopHat was used for allele-specific alignment in conjunction with SNPsplit; the citation attached to TopHat therefore supports the aligner identification but not that specific use. (LLM, conf=0.84)
Experimental — accuracy not yet measuredSpecific primer selection and protocol calibration for qPCR are challenging in their own right.
“Although qPCR based methods have traditionally been used as a reference 'gold' standard owing to their high sensitivity and dynamic range, it is noteworthy in this context that specific primer selection and protocol calibration are challenging in their own right. 20”
From A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium (2014) · cites this paper as [20]
The Background discusses challenges in aligning RNA-seq reads, and the Results and discussion evaluates RNA-seq alignment methods. Searches for qPCR primer selection, primer design, and protocol calibration found no passage addressing those challenges. (LLM, conf=0.75)
Experimental — accuracy not yet measured
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- Authors
- Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L.
- Affiliations
- Johns Hopkins University (US)
- Broad Institute (US)
- University of California, Berkeley (US)
- Illumina (United States) (US)
- Corresponding author
- Kim, Daehwan
- Venue
- Genome Biology
- Published
- 2013-04-25
- Volume
- 14
- Issue
- 4
- Pages
- R36-R36
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC4053844
- OpenAlex
- W2140729960
- Cited by
- 12,668
- References
- 7
- Citations by year
- 2026: 212 · 2025: 393 · 2024: 659 · 2023: 771 · 2022: 1009 · 2021: 1317 · 2020: 1554 · 2019: 1524 · 2018: 1517 · 2017: 1440 · 2016: 1103 · 2015: 729 · 2014: 352 · 2013: 68 · 2012: 3
- FWCI
- 336.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- University Libraries (University of Maryland) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Digital Repository at the University of Maryland (University of Maryland College Park)
- Funders
- Harvard University
- Johns Hopkins University
- Broad Institute
- National Institutes of Health (HG006677)
- Johns Hopkins Bloomberg School of Public Health
- National Human Genome Research Institute (R01HG006102, R01HG006677)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- RNA-seq alignment, spliced alignment, transcriptome alignment, indels, gene fusion, pseudogenes, repetitive genomes
- MeSH terms
- Humans, Sensitivity and Specificity, Software, Mutagenesis, Insertional, Sequence Alignment, Sequence Analysis, RNA, Gene Duplication, Gene Fusion, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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