Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression.
Published online
Journal Article
BACKGROUND: Deep sequencing of transposon mutant libraries (or TnSeq) is a powerful method for probing essentiality of genomic loci under different environmental conditions. Various analytical methods have been described for identifying conditionally essential genes whose tolerance for insertions varies between two conditions. However, for large-scale experiments involving many conditions, a method is needed for identifying genes that exhibit significant variability in insertions across multiple conditions. RESULTS: In this paper, we introduce a novel statistical method for identifying genes with significant variability of insertion counts across multiple conditions based on Zero-Inflated Negative Binomial (ZINB) regression. Using likelihood ratio tests, we show that the ZINB distribution fits TnSeq data better than either ANOVA or a Negative Binomial (in a generalized linear model). We use ZINB regression to identify genes required for infection of M. tuberculosis H37Rv in C57BL/6 mice. We also use ZINB to perform a analysis of genes conditionally essential in H37Rv cultures exposed to multiple antibiotics. CONCLUSIONS: Our results show that, not only does ZINB generally identify most of the genes found by pairwise resampling (and vastly out-performs ANOVA), but it also identifies additional genes where variability is detectable only when the magnitudes of insertion counts are treated separately from local differences in saturation, as in the ZINB model.
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Duke Authors
Cited Authors
- Subramaniyam, S; DeJesus, MA; Zaveri, A; Smith, CM; Baker, RE; Ehrt, S; Schnappinger, D; Sassetti, CM; Ioerger, TR
Published Date
- November 21, 2019
Published In
Volume / Issue
- 20 / 1
Start / End Page
- 603 -
PubMed ID
- 31752678
Pubmed Central ID
- 31752678
Electronic International Standard Serial Number (EISSN)
- 1471-2105
Digital Object Identifier (DOI)
- 10.1186/s12859-019-3156-z
Language
- eng
Conference Location
- England