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Updated: Aug 7, 2025

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2

Published on: September 18, 2021

DELongSeq for efficient detection of differential isoform expression from long-read RNA-seq data.

Yu Hu¹, Anagha Gouru¹, Kai Wang^1,2

¹Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.

NAR Genomics and Bioinformatics

|March 7, 2023

Summary

DELongSeq quantifies isoform expression uncertainty from long-read RNA sequencing data. This method improves differential expression analysis efficiency and power, enabling precise comparisons in precision medicine.

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Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Conventional gene expression quantification methods exhibit uniform estimation variance.
Next-generation sequencing offers wider dynamic ranges but requires robust expression level estimation.
Estimation efficiency, reflecting uncertainty, is crucial for downstream analyses.

Purpose of the Study:

To introduce DELongSeq, a novel method for quantifying isoform expression uncertainty.
To enhance estimation efficiency in long-read RNA sequencing data analysis.
To enable sensitive differential expression analysis, including single-case comparisons.

Main Methods:

Utilizes the information matrix of the EM algorithm to quantify estimation uncertainty.
Employs a random-effect regression model for differential isoform expression analysis.
Incorporates within-study and between-study variation for robust analysis.

Main Results:

DELongSeq demonstrates computational reliability through simulations and real data analysis.
The uncertainty quantification approach significantly improves the power of differential expression analysis for isoforms and genes.
The method facilitates 1 versus 1 case comparisons, valuable for precision medicine.

Conclusions:

DELongSeq provides an efficient and reliable approach for detecting differential gene and isoform expression from long-read RNA-Seq data.
The method enhances analytical power by accounting for estimation uncertainty.
DELongSeq has direct applications in precision medicine, particularly for personalized treatment response assessment.