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Computational and Structural Biotechnology Journal, 2022 Weighted gene co-expression network analysis (WGCNA) is used to detect clusters with highly correlated genes. Measurements of correlation most typically rely on linear relationships.
Garry Wong, Tianjiao Zhang
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Identification of susceptibility modules and hub genes of osteoarthritis by WGCNA analysis
Frontiers in Genetics, 2022 Osteoarthritis (OA) is a major cause of pain, disability, and social burden in the elderly throughout the world. Although many studies focused on the molecular mechanism of OA, its etiology remains unclear. Therefore, more biomarkers need to be explored to help early diagnosis, clinical outcome measurement, and new therapeutic target development.
Yanchao Wang
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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.
Wu, Jemma X. +4 more
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Identification of key pathways and genes in the progression of silicosis based on WGCNA
Inhalation Toxicology, 2022Silicosis, induced by inhaling silica particles in workplaces, is one of the most common occupational diseases. The prognosis of silicosis and its consequent fibrosis is extremely poor due to limited treatment modalities and lack of understanding of the disease mechanisms.
Jiaqi Lv +18 more
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WGCNA Application to Proteomic and Metabolomic Data Analysis
2017Progresses in mass spectrometric instrumentation and bioinformatics identification algorithms made over the past decades allow quantitative measurements of relative or absolute protein/metabolite amounts in cells in a high-throughput manner, which has significantly expedited the exploration into functions and dynamics of complex biological systems ...
G, Pei, L, Chen, W, Zhang
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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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Identifying novel candidate biomarkers of RCC based on WGCNA analysis
Personalized Medicine, 2018Extracting differential expression genes (DEGs) is an effective approach to improve the accuracy of determining the candidate biomarker genes. However, the previous DEGs analysis methods ignore that the expression levels of genes in different pathology stages of cancers are complex and various.In our study, staging DEGs analysis and weighted gene co ...
Jin, Deng +4 more
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Identification of crucial genes in aortic dissection by WGCNA
Atherosclerosis, 2021H. Zhang +6 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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