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


METHODS
MuMRescueLite is written in Python; executables and documentation are available from http://genome.gsc.riken.jp/osc/english/software/.
Hashimoto
Takehiro
T
Omics Science Center, RIKEN Yokohama Institute, 1-7-22 Suehiro-cho, Tsurumi, Yokohama 230-0045, Japan.
de Hoon
Michiel J L
MJ
Grimmond
Sean M
SM
Daub
Carsten O
CO
Hayashizaki
Yoshihide
Y
Faulkner
Geoffrey J
GJ
D019295:Computational Biology / Q000379:methods*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software