Evidence map›Paper›PMID 26847232›Full record

ArticleBMC bioinformatics2016

SPARTA: Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis.

Benjamin K Johnson, Matthew B Scholz, Tracy K Teal, Robert B Abramovitch

Abstract read
In one paragraph

Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. CrpH ofFrontiers in microbiology · 2026
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  3. Carbon dioxide regulatesInfection and immunity · 2025
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  10. AC2P20 selectively killsRSC advances · 2021
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  11. Article
  12. Time-Course Transcriptome ofInternational journal of molecular sciences · 2020
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  13. Article
  14. InhibitingACS chemical biology · 2020
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  15. Article
  16. Article
  17. Article
  18. Article
  19. WhiB6 regulation of ESX-1 gene expression is controlled by a negative feedback loop inProceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  20. Article
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

4 authors.

Benjamin K JohnsonDepartment of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA. john3434@msu.edu.
Matthew B ScholzVANTAGE, Vanderbilt University, Nashville, TN, 37235, USA. matthew.b.scholz@vanderbilt.edu.
Tracy K TealData Carpentry, ᅟ, ᅟ. tkteal@datacarpentry.org.
Robert B AbramovitchDepartment of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, 48824, USA. abramov5@msu.edu.

Funding

Screening for inhibitors of M. tuberculosis persistence-related lipid metabolismR21AI105867 · NIAID · MICHIGAN STATE UNIVERSITY · PI ABRAMOVITCH, ROBERT B · 2013 to 2014
$392k
NIAID NIH HHS R21 AI105867NIAID NIH HHS R21AI105867
6 · The paper itself

Abstract

backgroundMany tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow includes quality control of reads, mapping to a reference, counting transcript abundance, and statistical tests for differentially expressed genes. In spite of the numerous tools developed for each component of an RNA-seq analysis workflow, easy-to-use bacterially oriented workflow applications to combine multiple tools and automate the process are lacking. With many tools to choose from for each step, the task of identifying a specific tool, adapting the input/output options to the specific use-case, and integrating the tools into a coherent analysis pipeline is not a trivial endeavor, particularly for microbiologists with limited bioinformatics experience.

resultsTo make bacterial RNA-seq data analysis more accessible, we developed a Simple Program for Automated reference-based bacterial RNA-seq Transcriptome Analysis (SPARTA). SPARTA is a reference-based bacterial RNA-seq analysis workflow application for single-end Illumina reads. SPARTA is turnkey software that simplifies the process of analyzing RNA-seq data sets, making bacterial RNA-seq analysis a routine process that can be undertaken on a personal computer or in the classroom. The easy-to-install, complete workflow processes whole transcriptome shotgun sequencing data files by trimming reads and removing adapters, mapping reads to a reference, counting gene features, calculating differential gene expression, and, importantly, checking for potential batch effects within the data set. SPARTA outputs quality analysis reports, gene feature counts and differential gene expression tables and scatterplots.

conclusionsSPARTA provides an easy-to-use bacterial RNA-seq transcriptional profiling workflow to identify differentially expressed genes between experimental conditions. This software will enable microbiologists with limited bioinformatics experience to analyze their data and integrate next generation sequencing (NGS) technologies into the classroom. The SPARTA software and tutorial are available at sparta.readthedocs.org.

Indexed as

SoftwareAutomationComputational BiologyGene Expression ProfilingHigh-Throughput Nucleotide SequencingReference StandardsRNA, BacterialSequence Analysis, RNATranscriptomeRNA, Bacterial

Identifiers

PMID26847232
PMCPMC4743240

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.