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A data browsing application for accessing gene and module-level blood transcriptome profiles of healthy pregnant women from high- and low-resource settings.

Authors :
Rinchai D
Brummaier T
A Marr A
Habib T
Toufiq M
Kino T
Nosten F
Al Khodor S
Terranegra A
McGready R
Kabeer BSA
Chaussabel D
Source :
Database : the journal of biological databases and curation [Database (Oxford)] 2024 Apr 02; Vol. 2024.
Publication Year :
2024

Abstract

Transcriptome profiling data, generated via RNA sequencing, are commonly deposited in public repositories. However, these data may not be easily accessible or usable by many researchers. To enhance data reuse, we present well-annotated, partially analyzed data via a user-friendly web application. This project involved transcriptome profiling of blood samples from 15 healthy pregnant women in a low-resource setting, taken at 6 consecutive time points beginning from the first trimester. Additional blood transcriptome profiles were retrieved from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public repository, representing a cohort of healthy pregnant women from a high-resource setting. We analyzed these datasets using the fixed BloodGen3 module repertoire. We deployed a web application, accessible at https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/which displays the module-level analysis results from both original and public pregnancy blood transcriptome datasets. Users can create custom fingerprint grid and heatmap representations via various navigation options, useful for reports and manuscript preparation. The web application serves as a standalone resource for exploring blood transcript abundance changes during pregnancy. Alternatively, users can integrate it with similar applications developed for earlier publications to analyze transcript abundance changes of a given BloodGen3 signature across a range of disease cohorts. Database URL: https://thejacksonlaboratory.shinyapps.io/BloodGen3_Pregnancy/.<br /> (© The Author(s) 2024. Published by Oxford University Press.)

Details

Language :
English
ISSN :
1758-0463
Volume :
2024
Database :
MEDLINE
Journal :
Database : the journal of biological databases and curation
Publication Type :
Academic Journal
Accession number :
38564425
Full Text :
https://doi.org/10.1093/database/baae021