Probabilistic resolution of multi-mapping reads in massively parallel sequencing data using MuMRescueLite | Zendy

Takehiro Hashimoto | Zendy; Michiel de Hoon | Zendy; Sean M. Grimmond | Zendy; Carsten O. Daub | Zendy; Yoshihide Hayashizaki | Zendy; Geoffrey J. Faulkner | Zendy

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Probabilistic resolution of multi-mapping reads in massively parallel sequencing data using MuMRescueLite

Author(s) -

Takehiro Hashimoto,

Michiel de Hoon,

Sean M. Grimmond,

Carsten O. Daub,

Yoshihide Hayashizaki,

Geoffrey J. Faulkner

Publication year - 2009

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btp438

Subject(s) - python (programming language) , executable , computer science , software , documentation , massive parallel sequencing , probabilistic logic , massively parallel , dna sequencing , data mining , programming language , operating system , biology , artificial intelligence , genetics , dna

Multi-mapping sequence tags are a significant impediment to short-read sequencing platforms. These tags are routinely omitted from further analysis, leading to experimental bias and reduced coverage. Here, we present MuMRescueLite, a low-resource requirement version of the MuMRescue software that has been used by several next generation sequencing projects to probabilistically reincorporate multi-mapping tags into mapped short read data.

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