Document Type

Article

Publication Date

10-1-2024

Identifier

DOI: 10.1093/bioinformatics/btae587; PMCID: PMC11486499

Abstract

MOTIVATION: Integrative analysis of heterogeneous expression data remains challenging due to variations in platform, RNA quality, sample processing, and other unknown technical effects. Selecting the approach for removing unwanted batch effects can be a time-consuming and tedious process, especially for more biologically focused investigators.

RESULTS: Here, we present BatchFLEX, a Shiny app that can facilitate visualization and correction of batch effects using several established methods. BatchFLEX can visualize the variance contribution of a factor before and after correction. As an example, we have analyzed ImmGen microarray data and enhanced its expression signals that distinguishes each immune cell type. Moreover, our analysis revealed the impact of the batch correction in altering the gene expression rank and single-sample GSEA pathway scores in immune cell types, highlighting the importance of real-time assessment of the batch correction for optimal downstream analysis.

AVAILABILITY AND IMPLEMENTATION: Our tool is available through Github https://github.com/shawlab-moffitt/BATCH-FLEX-ShinyApp with an online example on Shiny.io https://shawlab-moffitt.shinyapps.io/batch_flex/.

Journal Title

Bioinformatics (Oxford, England)

Volume

40

Issue

10

MeSH Keywords

Software; Gene Expression Profiling; Humans; Computational Biology

Keywords

Software; Gene Expression Profiling; Computational Biology

Comments

Grants and funding

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Publisher's Link: https://doi.org/10.1093/bioinformatics/btae587

Download

Share

COinS