Evidence map›Paper›PMID 28683752›Full record

ArticleBMC bioinformatics2017

TnseqDiff: identification of conditionally essential genes in transposon sequencing studies.

Lili Zhao, Mark T Anderson, Weisheng Wu, Harry L T Mobley, Michael A Bachman

Abstract read
In one paragraph

Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed.

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  13. Analysis of Gene Essentiality from TnSeq Data Using Transit.Methods in molecular biology (Clifton, N.J.) · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lili ZhaoDepartment of Biostatistics, University of Michigan, 1415 Washington Heights, Ann Arbor, USA. zhaolili@umich.edu.ORCID http://orcid.org/0000-0002-6366-8206
Mark T AndersonDepartment of Microbiology and Immunology, School of medicine, University of Michigan, Ann Arbor, USA.
Weisheng WuBRCF Bioinformatics Core, University of Michigan, Ann Arbor, USA.
Harry L T MobleyDepartment of Microbiology and Immunology, School of medicine, University of Michigan, Ann Arbor, USA.
Michael A BachmanDepartment of Pathology, School of medicine, University of Michigan, Ann Arbor, USA.

Funding

XenograftP30CA046592 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THEODORE S LAWRENCE · 1988 to 2026
$178.2M
Reciprocal Control of Motility and Adherence in UTIR01AI059722 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI PEARSON, MELANIE M. · 2005 to 2024
$7.4M
Vaccine to prevent E. coli urinary tract infectionR01AI116791 · NIAID · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MOBLEY, HARRY L. · 2016 to 2020
$2.0M
NCI NIH HHS P30 CA046592NIAID NIH HHS R01 AI059722NIAID NIH HHS R01 AI116791
6 · The paper itself

Abstract

backgroundTn-Seq is a high throughput technique for analysis of transposon mutant libraries to determine conditional essentiality of a gene under an experimental condition. A special feature of the Tn-seq data is that multiple mutants in a gene provides independent evidence to prioritize that gene as being essential. The existing methods do not account for this feature or rely on a high-density transposon library. Moreover, these methods are unable to accommodate complex designs.

resultsThe method proposed here is specifically designed for the analysis of Tn-Seq data. It utilizes two steps to estimate the conditional essentiality for each gene in the genome. First, it collects evidence of conditional essentiality for each insertion by comparing read counts of that insertion between conditions. Second, it combines insertion-level evidence for the corresponding gene. It deals with data from both low- and high-density transposon libraries and accommodates complex designs. Moreover, it is very fast to implement. The performance of the proposed method was tested on simulated data and experimental Tn-Seq data from Serratia marcescens transposon mutant library used to identify genes that contribute to fitness in a murine model of infection.

conclusionWe describe a new, efficient method for identifying conditionally essential genes in Tn-Seq experiments with high detection sensitivity and specificity. It is implemented as TnseqDiff function in R package Tnseq and can be installed from the Comprehensive R Archive Network, CRAN.

Indexed as

Genes, EssentialArea Under CurveDNA Transposable ElementsGenome, BacterialGenomicsMutagenesis, InsertionalROC CurveSerratia marcescensDNA Transposable ElementsCD functionDifferential testEssential geneInSeqTn-SeqTransposon sequencing

Identifiers

PMID28683752
PMCPMC5500955

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.