Deep-Cloud: A Deep Neural Network-Based Approach for Analyzing Differentially Expressed Genes of RNA-seq Data
Author:
Affiliation:
1. State Key Laboratory of Bioelectronics, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
2. School of Medicine, Southeast University, Nanjing 210097, China
Funder
Natural Science Foundation of Jiangsu Province
National Natural Science Foundation of China
Excellence Postdoctoral Program of Jiangsu Province
Publisher
American Chemical Society (ACS)
Subject
Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00766
Reference32 articles.
1. How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?
2. A comparison of methods for differential expression analysis of RNA-seq data
3. Differential expression in RNA-seq: A matter of depth
4. Differential expression analysis for sequence count data
5. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data
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