Related Experiment Video
Updated: May 23, 2025
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
mirrorCheck: an R package facilitating informed use of DESeq2's lfcShrink() function for differential gene expression
Katherine Elise Scull1, Kiarash Behrouzfar1, Daniella Brasacchio1
1Blood Cancer Biomarkers Lab, Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, 3168, Australia.
Motivation:
The sophisticated lfcShrink() function implemented in the DESeq2 package for differential gene expression analysis aims to reduce noise from low read count and/or highly variable genes in bulk RNA-sequencing data, thus circumventing the need for arbitrary filtering thresholds. However, difficulties can arise when analysing clinical data with multiple biologically-relevant groupings. In particular, changing the reference group can dramatically alter the ranking of differentially expressed genes, instead of merely 'mirroring' the up- and down-regulated genes in reciprocal comparisons.
Results:
Here, we present mirrorCheck, an R package to automate methodical lfcShrink() usage and data visualization for quality control and data-driven decision-making during analysis.
Availability And Implementation:
The source code, including documentation, is available on github at https://github.com/kescull/mirrorCheck.
