GMAP: A genomic mapping and alignment program for mRNA and EST sequences
Open accessAbstract
MOTIVATION: We introduce GMAP, a standalone program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing. RESULTS: On a set of human messenger RNAs with random mutations at a 1 and 3% rate, GMAP identified all splice sites accurately in over 99.3% of the sequences, which was one-tenth the error rate of existing programs. On a large set of human expressed sequence tags, GMAP provided higher-quality alignments more often than blat did. On a set of Arabidopsis cDNAs, GMAP performed comparably with GeneSeqer. In these experiments, GMAP demonstrated a several-fold increase in speed over existing programs. AVAILABILITY: Source code for gmap and associated programs is available at http://www.gene.com/share/gmap SUPPLEMENTARY INFORMATION: http://www.gene.com/share/gmap.
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GMAP uses hashing to index the genome, allowing efficient identification of splice junctions and exons for spliced alignments.
“GMAP uses hashing to index the genome [53], allowing efficient identification of splice junctions and exons (figure 11).”
From Whole-Genome Alignment: Methods, Challenges, and Future Directions (2024) · cites this paper as [53]
The Minimal sampling strategy section says GMAP tried a hashing scheme in its initial implementation, but subsequently adopted a more efficient double-lookup scheme. Thus, the paper does not describe hashing as the method GMAP uses to index the genome. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredGMAP's complexity is O(n), where n is the length of the reference sequence.
“GMAP's complexity is O ( n ), where n is the length of the reference sequence.”
From Whole-Genome Alignment: Methods, Challenges, and Future Directions (2024) · cites this paper as [53]
The Oligomer chaining section gives the approximate-alignment complexity as O(mg), where m is cDNA length and g is generally proportional to genomic-segment length. It does not give O(n) complexity in the length of the reference sequence; the stated bound depends on both sequences and concerns a genomic segment, not the whole reference. (LLM, conf=0.83)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredGMAP's capability to handle long reads makes it suitable for transcriptome studies where reads span multiple exons.
“Its capability to handle long reads makes it suitable for transcriptome studies where reads span multiple exons.”
From Whole-Genome Alignment: Methods, Challenges, and Future Directions (2024) · cites this paper as [53]
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- Authors
- Wu, T. D., & Watanabe, C. K.
- Affiliations
- Genentech (US)
- Corresponding author
- Wu, T. D.
- Venue
- Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-02-22
- Volume
- 21
- Issue
- 9
- Pages
- 1859-1875
- ISSN
- 0266-7061 (ISSN-L)
- 1367-4803
- 1460-2059
- OpenAlex
- W2106678197
- Cited by
- 2,354
- References
- 3
- Citations by year
- 2026: 104 · 2025: 132 · 2024: 139 · 2023: 150 · 2022: 213 · 2021: 281 · 2020: 223 · 2019: 182 · 2018: 161 · 2017: 145 · 2016: 112 · 2015: 95 · 2014: 87 · 2013: 67 · 2012: 55
- FWCI
- 8.75
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Computer applications in the biosciences (publishedVersion)
- PubMed (publishedVersion)
- 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 › Fractal and DNA sequence analysis
- Keywords
- GMAP, genome mapping, expressed sequence tags, gene structure prediction, splice site detection, sequence variation
- MeSH terms
- Algorithms, Chromosome Mapping, Humans, RNA, Messenger, Sequence Homology, Nucleic Acid, Software, Genome, Human, Sequence Alignment, Sequence Analysis, DNA, Sequence Analysis, RNA, Expressed Sequence Tags, RNA Splice Sites
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