A zero-inflated Poisson model for insertion tolerance analysis of genes based on Tn-seq data
Author(s) -
Fangfang Liu,
Chong Wang,
Zuowei Wu,
Qijing Zhang,
Peng Liu
Publication year - 2016
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/btw061
Subject(s) - transposable element , computer science , transposon mutagenesis , biology , computational biology , genetics , pseudogene , gene , algorithm , genome
Transposon insertion sequencing (Tn-seq) is an emerging technology that combines transposon mutagenesis with next-generation sequencing technologies for the identification of genes related to bacterial survival. The resulting data from Tn-seq experiments consist of sequence reads mapped to millions of potential transposon insertion sites and a large portion of insertion sites have zero mapped reads. Novel statistical method for Tn-seq data analysis is needed to infer functions of genes on bacterial growth.
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