WGCNA analysis of GSE21374.

WGCNA analysis of GSE21374.

<p><b>A.</b> Cluster Dendrogram: Hierarchical clustering of genes, with branches representing gene modules, color-coded below the dendrogram. These modules reflect co-expressed genes potentially involved in transplant rejection. <b>B.</b> Scale Independence and Mean Con...

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Bibliographic Details
Main Author: Xihao Shen (20347942) (author)
Other Authors: Jiyue Wu (3814717) (author), Feilong Zhang (420300) (author), Qing Bi (3864823) (author), Zejia Sun (10031646) (author), Wei Wang (17594) (author)
Published: 2024
Subjects:
Cell Biology
Genetics
Molecular Biology
Neuroscience
Biotechnology
Developmental Biology
Marine Biology
Cancer
Virology
Computational Biology
weighted gene co
two clusters underscored
multiple established databases
machine learning algorithms
integrative machine learning
gene expression omnibus
demographic shift towards
consensus clustering algorithm
b >(</ b
aged donor kidneys
term graft outcomes
expression network analysis
differential expression analysis
comprehensive analysis underscores
worse graft survival
reduced graft survival
predicting graft survival
two rejection clusters
rejection remains elusive
optimal acute rejection
delayed graft function
ktx rejection poses
ktx rejection occurrence
identify predictive srgs
invasive diagnostic model
kidney transplant rejection
graft survival
ktx rejection
kidney graft
diagnostic model
kidney rejection
gsva analysis
cluster analysis
allograft function
rejection samples
diagnosing rejection
prognostic model
kidney transplantation
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wgcna ),
significant threat
related genes
provided microarray
positive correlation
level landscape
ischemic damage
detailed cellular
conducted using
conclusions drawn
cluster c1
c2 ).
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Summary:<p><b>A.</b> Cluster Dendrogram: Hierarchical clustering of genes, with branches representing gene modules, color-coded below the dendrogram. These modules reflect co-expressed genes potentially involved in transplant rejection. <b>B.</b> Scale Independence and Mean Connectivity: Left: Scale-free topology model fit (R^2) versus soft-thresholding power, ensuring network adherence to a scale-free topology. Right: Mean connectivity as a function of soft-thresholding power, used to determine the optimal network parameters. <b>C.</b> Network Heatmap: Topological overlap matrix (TOM) heatmap showing the strength of connections between genes, with dendrograms and module colors corresponding to (<b>A</b>).</p> <p>(TIF)</p>

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