Author:
Yan Jing,Zeng Qiuhong,Wang Xianlong
Funder
XW was supported by Fujian Medical University
the Natural Science Foundation of Fujian Province
Publisher
Springer Science and Business Media LLC
Reference58 articles.
1. Siavoshi A, Taghizadeh M, Dookhe E, et al. Gene expression profiles and pathway enrichment analysis to identification of differentially expressed gene and signaling pathways in epithelial ovarian cancer based on high-throughput RNA-seq data. Genomics. 2022;114(1):161–70.
2. Wang H, Nie X, Li X, et al. Bioinformatics analysis and high-throughput sequencing to identify differentially expressed genes in nebulin gene (NEB) mutations mice. Med Sci Monit. 2020;26: e922953.
3. Leek JT, Scharpf RB, Bravo HC, et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet. 2010;11(10):733–9.
4. Leek JT, Johnson WE, Parker HS, et al. The SVA package for removing batch effects and other unwanted variation in high-throughput experiments. Bioinformatics. 2012;28(6):882–3.
5. Leek JT. svaseq: removing batch effects and other unwanted noise from sequencing data. Nucleic Acids Res. 2014;42(21): e161.
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