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Updated: Dec 23, 2025
Three Differential Expression Analysis Methods for RNA Sequencing: limma, EdgeR, DESeq2
Published on: September 18, 2021
An effective analytic method for detecting tissue-specific genes in RNA-seq experiments
Guoqing Zhao1,2, Qiao Li2, I-Ming Wang3
1School of Mathematical Sciences, Peking University, Beijing 100871, China.
Aim:
To develop an analytic method for identifying tissue-specific (TS) genes from RNA-seq data.
Materials & Methods:
Based on a negative binomial distribution, we develop a statistical method containing consecutive procedures incorporating data variability from replicates in each tissue.
Results:
Simulations show that our approach can effectively identify at least 94% of the truly TS genes if the sample size is 3 and at least 84% of the TS genes detected by our method are truly TS genes. We illustrated the utility of our method in an in-house RNA-seq project and produced sensible results.
Conclusion:
Our approach not only directly works on discrete data but also naturally incorporates data variability. It works effectively for detecting TS genes.
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