Evidence map›Paper›PMID 39422483›Full record

ArticlemSystems2024

E.PathDash, pathway activation analysis of publicly available pathogen gene expression data.

Lily Taub, Thomas H Hampton, Sharanya Sarkar, Georgia Doing, Samuel L Neff, Carson E Finger, Kiyoshi Ferreira Fukutani, Bruce A Stanton

Abstract read
In one paragraph

Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Bridging bench and bedside: translational omics ofEuropean respiratory review : an official journal of the European Respiratory Society · 2026
    Review
  2. 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

8 authors.

Lily TaubDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0009-0008-6625-6216
Thomas H HamptonDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0003-0543-402X
Sharanya SarkarDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0002-2459-8620
Georgia DoingThe Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, USA.ORCID 0000-0002-0835-6955
Samuel L NeffLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, USA.ORCID 0000-0002-5993-8445
Carson E FingerDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0002-0335-4547
Kiyoshi Ferreira FukutaniDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0003-2223-0918
Bruce A StantonDepartment of Microbiology and Immunology, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA.ORCID 0000-0002-1661-407X

Funding

Understanding the role of RNA-binding protein mutations in cancerP20GM113132 · NIGMS · DARTMOUTH COLLEGE · PI MADDEN, DEAN R · 2016 to 2025
$25.9M
Translational Research CoreP30DK117469 · NIDDK · DARTMOUTH COLLEGE · PI DEBORAH A HOGAN · 2018 to 2026
$13.9M
Retrieval, Reprocessing, Normalization and Sharing of Gene Expression and Lung Microbiome Data Sets to Facilitate AI/ML Analysis Studies of Bacterial Lung InfectionsR01HL151385 · NHLBI · DARTMOUTH COLLEGE · PI STANTON, BRUCE A. · 2021 to 2024
$2.4M
Transcriptomics compendia for the study of strain-level genetic diversity of the human skin microbiomeF32GM151856 · NIGMS · JACKSON LABORATORY · PI DOING, GEORGIA · 2023 to 2024
$143k
Cystic Fibrosis Foundation (CFF) STANTO19G0,STANTO20PO,STANTO19R0Flatley FoundationHHS | National Institutes of Health (NIH) P30-DK117469,R01HL151385,P20-GM113132NHLBI NIH HHS R01 HL151385NIAMS NIH HHS L70 AR084912NIDDK NIH HHS P30 DK117469NIGMS NIH HHS F32 GM151856NIGMS NIH HHS P20 GM113132
6 · The paper itself

Abstract

E.PathDash facilitates re-analysis of gene expression data from pathogens clinically relevant to chronic respiratory diseases, including a total of 48 studies, 548 samples, and 404 unique treatment comparisons. The application enables users to assess broad biological stress responses at the KEGG pathway or gene ontology level and also provides data for individual genes. E.PathDash reduces the time required to gain access to data from multiple hours per data set to seconds. Users can download high-quality images such as volcano plots and boxplots, differential gene expression results, and raw count data, making it fully interoperable with other tools. Importantly, users can rapidly toggle between experimental comparisons and different studies of the same phenomenon, enabling them to judge the extent to which observed responses are reproducible. As a proof of principle, we invited two cystic fibrosis scientists to use the application to explore scientific questions relevant to their specific research areas. Reassuringly, pathway activation analysis recapitulated results reported in original publications, but it also yielded new insights into pathogen responses to changes in their environments, validating the utility of the application. All software and data are freely accessible, and the application is available at scangeo.dartmouth.edu/EPathDash. IMPORTANCE: Chronic respiratory illnesses impose a high disease burden on our communities and people with respiratory diseases are susceptible to robust bacterial infections from pathogens, including

Indexed as

SoftwareComputational BiologyDatabases, GeneticGene Expression ProfilingHumansbioinformaticsgene expressionpathway analysisrespiratory pathogens

Identifiers

PMID39422483
PMCPMC11575265

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.