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Application data

Created by Gerton Lunter, Martin Goodson
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.



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.


  • 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



  1. Lunter G, Goodson M.. 2010. Genome Research

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