Key driver analysis wgcna

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August undefined, 2024

Although integration of our peanut gene analysis with WGCNA provided strong evidence for a link between acute peanut allergic reactions and the peanut response module, this type of analysis is associative and thus cannot on its own reveal causal relationships among genes in the implicated module. … Meer weergeven Twenty-one children with suspected peanut allergy completed randomized, double-blind, placebo-controlled oral food challenges to peanut, performed according to a modified AAAAI/EAACI PRACTALL protocol8, 9. … Meer weergeven The primary aims of this study were to characterize gene expression signatures, functional processes, and causal key drivers of acute peanut allergic reactions. To do this, during each peanut and placebo … Meer weergeven Given that the allergic response involves the activation, differentiation, and recruitment of various immune cell types, we tested for … Meer weergeven To assess the robustness of the changes in gene expression and leukocyte fractions observed, we sought to replicate our findings in an independent replication cohort of 21 peanut allergic children, with clinical … Meer weergeven Web2 dagen geleden · Download Citation Identification of key genes in bovine muscle development by co-expression analysis Background Skeletal muscle is not only an important tissue involved in exercise and ...

Weighted correlation network analysis - Wikipedia

Web3 nov. 2024 · The weighted gene co-expression network analysis (WGCNA) has been used to explore gene expression datasets by constructing biological networks based on the likelihood expression profile among genes. Web5 mei 2024 · The present study aimed at identifying key genes with differential correlations between normal and tumor status.MethodsWeighted gene co-expression network analysis (WGCNA) was employed to build a gene interaction network using the expression profile of LUAD from The Cancer Genome Atlas (TCGA). dr connie brooks fayetteville nc

Genes Free Full-Text Molecular Network-Based Identification of ...

Web27 mei 2024 · A key driver analysis is a statistical technique you can use to determine the importance between potential factors — like product quality or price — and customer … Web5 jun. 2024 · In this study, we identified the key regulatory genes and pathways involved in NAFLD using the integrated method of bioinformatics, including WGCNA, functional … Web21 sep. 2024 · Weighted correlation network analysis (WGCNA) can be used for finding clusters ... Multitissue key drivers (SPIB and TNFRSF13C) and tissue-specific key drivers (eg, EBF1) were identified. energy conservation adl

Genes Free Full-Text Molecular Network-Based Identification of ...

Web27 jan. 2024 · We performed key driver analysis of up- and downexpressed genes separately. 24 key drivers were found in the upregulated gene set, and 81 key drivers … Web(WGCNA) was used to screen the key micro‐RNA modules. The centrality of key genes were determined by module membership (mm) and gene significance(GS). The key … energy conservation code 2015WebMethods: Weighted gene correlation network analysis (WGCNA) was performed on gene expression profiles from healthy controls, individuals with diabetes mellitus, and individuals with diabetes mellitus-associated coronary artery disease (DMCAD). Phenotypically related module genes were analyzed for enrichment in Gene Ontology (GO) terms and Kyoto ... dr connie smith md

"Web11 feb. 2024 · In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the key genes that were highly associated with RA phenotypes based on multiple microarray datasets of RA blood samples, after which they were used as features in machine … " - Key driver analysis wgcna

Key driver analysis wgcna

RUNX1 in diabetes mellitus-related coronary artery disease IJGM

Web26 nov. 2024 · We sought to perform a weighted gene co-expression network analysis (WGCNA) to identify key modules, hub genes, and possible regulatory targets involved … Web11 feb. 2024 · In the present study, we used weighted gene co-expression network analysis (WGCNA) in conjunction with differentially expressed gene (DEG) analysis to select the …

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WebUsing this approach, we identified modules of coexpressed genes involved in phenotypic divergence and their key drivers, and further identified a module part specifically rewired in the backcross progeny. Functional analysis of transcriptomic data can significantly contribute to the understanding of the mechanisms underlying ecological speciation. Web12 jun. 2024 · After analyzing the differentially expressed genes (DEGs) in significantly correlated WGCNA modules, we found that genes related to heavy metal transportation had higher expression levels in node ...

Web28 jan. 2024 · After identifying the hub pathogenic module by weighted gene coexpression network analysis (WGCNA), the genes in the hub module were evaluated for functional enrichment. Finally, we constructed … Web5 jun. 2024 · To determine key genes and pathways in the pathogenesis of NAFLD, we performed WGCNA and identified fifteen “true” hub genes that are shared in both the coexpression and PPI networks. Furthermore, KEGG pathway analysis of these “true” hub genes revealed that three genes NDUFB8, NDUFA9, and UQCRQ were enriched in …

Web13 mei 2024 · Gene co-expression network analysis by WGCNA (weighted gene co-expression network analysis) identified 7 modules that were significantly associated with different infection stages, and 110 hub genes of these modules. These key regulators mainly participate in the biosynthesis of fatty acid and antibiotics. Web17 jan. 2024 · DESeq2, key driver analysis and weighted gene correlation network analysis (WGCNA) were conducted to identify differentially expressed genes (DEGs), …

Web19 jan. 2024 · We then obtained eight key driver miRNAs, among which hsa-mir-221 and hsa-mir-222 were key driver RNAs identified by both miRNA–mRNA–lncRNA and WGCNA network. In addition, hsa-mir-375 was inferred to be significant for patients’ survival with 34 associated ceRNAs, among which RUNX2, DUSP6 and SEMA3D are known oncogenes …

Web6 apr. 2024 · WGCNA: Weighted Correlation Network Analysis Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally … energy conservation for patientsWebThe weighted key driver analysis (wKDA) in Mergeomics was used to identify the hub genes of each GCM, and the results were visualized by the Cytoscape software [ 32 ]. The above analyses were performed using the R software (version 3.5.2). 3. Results 3.1. A Total of 16 GCMs Were Identified for AD and Epilepsy Samples energy conservation fund thailandWebThe weighted key driver analysis (wKDA) in Mergeomics was used to identify the hub genes of each GCM, and the results were visualized by the Cytoscape software . The … energy conservation and storageWeb3 dec. 2024 · In the present study, weighted gene co‑expression network analysis (WGCNA) was conducted to identify key modules and hub genes to determine their potential associations with AF. WGCNA was performed in an AF dataset GSE79768 obtained from the Gene Expression Omnibus, which contained data from paired left and … energy conservation during eatingWeb4 sep. 2024 · Here, we profiled the metabolome and transcriptome of 11 tea cultivars, and then illustrated a weighted gene coexpression network analysis (WGCNA)-based system … dr conning psychologistWeb12 apr. 2024 · Background: Bladder cancer (BCa) is the leading reason for death among genitourinary malignancies. RNA modifications in tumors closely link to the immune microenvironment. Our study aimed to propose a promising model associated with the “writer” enzymes of five primary RNA adenosine modifications (including m6A, m6Am, … energy conservation handout osuWeb25 nov. 2024 · In this study, we presented an improved driver gene identification and analysis pipeline that comprises the four most widely focused analyses for driver genes: … dr. connie wang seattle