| Issue |
E3S Web Conf.
Volume 271, 2021
2021 2nd International Academic Conference on Energy Conservation, Environmental Protection and Energy Science (ICEPE 2021)
|
|
|---|---|---|
| Article Number | 03058 | |
| Number of page(s) | 4 | |
| Section | Research on Energy Chemistry and Chemical Simulation Performance | |
| DOI | https://doi.org/10.1051/e3sconf/202127103058 | |
| Published online | 15 June 2021 | |
The comparison of limma and DESeq2 in gene analysis
College of Innovation and Experiment, Northwest A&F University, China
* Corresponding author: tongyihan720@163.com
Gene expression is the process by which information from a gene is used in the synthesis of a functional gene product. With the development of techniques, many methods to analyze the differentially expressed (DE) genes have emerged, especially the downstream analysis approaches, such as limma, DESeq2, and edgeR. However, it is unclear whether using different methods leads to different results. This article has compared the results gained from DESeq2 and limma when conducting downstream analysis for RNA sequencing data. Evidently, the number of genes they found is different from each other. DESeq2 found more genes than limma. But more than 90% of the genes detected by the two methods are overlapped, which means both methods are reliable. If precise results are needed, limma has a better ability to find the accurate DE genes. In the end, we analyzed the reason of the difference and summarized when it is better to use limma than DESeq2.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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