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Application of WGCNA and PloGO2 in the Analysis of Complex Proteomic Data
2021In this protocol we describe our workflow for analyzing complex, multi-condition quantitative proteomic experiments, with the aim to extract biological insights. The tool we use is an R package, PloGO2, contributed to Bioconductor, which we can optionally precede by running correlation network analysis with WGCNA.
Jemma X, Wu +4 more
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[WGCNA screening of prognostic markers in medulloblastoma].
Zhonghua yi xue za zhi, 2020Objective: In this study, we used the Weighted gene co-expression network analysis (WGCNA) analysis to find the gene module that are specifically expressed in Medulloblastoma and screened the marker genes that may diagnose and treat Medulloblastoma. Methods: WGCNA was used to identify the gene modules that are specifically associated with suvival in ...
B S, Du, L, Yuan, L G, Sun, Z Y, Zhang
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Identification of susceptibility modules and characteristic genes to osteoarthritis by WGCNA
Annales de Biologie CliniqueThe susceptibility modules and characteristic genes of patients with osteoarthritis (OA) were determined by weighted gene co-expression network analysis (WGCNA), and the role of immune cells in OA related microenvironment was analyzed. GSE98918 and GSE117999 data sets are from GEO database. R language was used to conduct difference analysis for the new
He-Jun, Hu +5 more
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Organic Rankine Cycle Performance Analysis Based on WGCNA
2023 China Automation Congress (CAC), 2023Fan Chen +4 more
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Identification of crucial genes in aortic dissection by WGCNA
Atherosclerosis, 2021H. Zhang +6 more
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Transcriptome Sequencing and WGCNA Reveal Key Genes in Response to Leaf Blight in Poplar
International Journal of Molecular Sciences, 2023Ruiqi Wang, Wenjing Yao
exaly