Evidence map›Paper›PMID 26447887›Full record

ArticlePLoS computational biology2015

TRANSIT--A Software Tool for Himar1 TnSeq Analysis.

Michael A DeJesus, Chaitra Ambadipudi, Richard Baker, Christopher Sassetti, Thomas R Ioerger

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 180 papers.

0numbers the graph read from it
0cells of the map it votes in
180citing 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

180 citing papers in PubMed.

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  17. Non-canonical peptidoglycan cross-linking is essential forbioRxiv : the preprint server for biology · 2026
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  18. Article
  19. Article
  20. Article

120 more citing papers are in PubMed but not listed here.

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.

Michael A DeJesusDepartment of Computer Science, Texas A&M University, College Station, Texas, United States of America.
Chaitra AmbadipudiDepartment of Computer Science, Texas A&M University, College Station, Texas, United States of America.
Richard BakerDepartment of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.
Christopher SassettiDepartment of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, Massachusetts, United States of America.
Thomas R IoergerDepartment of Computer Science, Texas A&M University, College Station, Texas, United States of America.

Funding

The roles of genes critical for growth under defined conditions in vitro or duriU19AI107774 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI CARR, STEVEN A, FORTUNE, SARAH · 2013 to 2017
$13.2M
NIAID NIH HHS U19 AI107774
6 · The paper itself

Abstract

TnSeq has become a popular technique for determining the essentiality of genomic regions in bacterial organisms. Several methods have been developed to analyze the wealth of data that has been obtained through TnSeq experiments. We developed a tool for analyzing Himar1 TnSeq data called TRANSIT. TRANSIT provides a graphical interface to three different statistical methods for analyzing TnSeq data. These methods cover a variety of approaches capable of identifying essential genes in individual datasets as well as comparative analysis between conditions. We demonstrate the utility of this software by analyzing TnSeq datasets of M. tuberculosis grown on glycerol and cholesterol. We show that TRANSIT can be used to discover genes which have been previously implicated for growth on these carbon sources. TRANSIT is written in Python, and thus can be run on Windows, OSX and Linux platforms. The source code is distributed under the GNU GPL v3 license and can be obtained from the following GitHub repository: https://github.com/mad-lab/transit.

Indexed as

AlgorithmsSoftwareBase SequenceChromosome MappingDNA Transposable ElementsGenome, BacterialMolecular Sequence DataPattern Recognition, AutomatedProgramming LanguagesSequence Analysis, DNADNA Transposable Elements

Identifiers

PMID26447887
PMCPMC4598096

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.