Stampy
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Application data |
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| Created by | Gerton Lunter, Martin Goodson |
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| Principal bioinformatics method(s) | Read mapping |
| Technology | Illumina |
| Created at | University of Oxford |
| Maintained? | Yes |
| Input format(s) | FASTQ, FASTA, SAM, BAM |
| Output format(s) | SAM, Maq |
| Programming language(s) | Python |
| Licence | Commercial, Freeware |
| Operating system(s) | Linux |
Summary: Uses a hybrid mapping algorithm and a detailed statistical model to achieve both speed and sensitivity, particularly when reads include sequence variation.
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Contents
Description
Stampy aims at providing a sensitive read mapper that is still relatively fast. To this aim it uses a hash based algorithm and can be used in a so called hybrid mode where it relies on a BWA. By using a detailed statistical model, Stampy is indeed very sensitive according to the original publication. Whilst being nearly as good as Novoalign in terms of SNP recall and usually being better for large indels than novoalign it is reported to be several times faster than the latter tool.
Features
- Maps single, paired-end, mate pair Illumina reads to a reference
- Fast: about 10 (with BWA) or 15 hours (without) per Gbase
- Low memory footprint: 2.7 Gb shared memory for a 3Gbase genome
- High sensitivity for indels and divergent reads, up to 10-15%
- Low mapping bias for reads with SNPs or indels
- Well calibrated mapping quality scores
- Optionally calculates per-base alignment posteriors
- Optionally processes part of the input
- Handles reads up to 4500 bases
Links
References
To add a reference for Stampy, enter the PubMed ID in the field below and click 'Add'.
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