How to eliminate abnormal samples by WGCNA

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WGCNA removes abnormal samples

To do WGCNA analysis, it is necessary to screen genes and samples. In general, the following screening scheme is used:

1. Screen out the genes with abundant and low expression and little change in each sample.

two。 Filter out abnormal samples

Gene screening is easier to deal with. However, exception samples are difficult to handle. You can refer to a code in WGCNA and the following code:

# calculate the similarity matrix A=adjacency (t (datExpr), type= "signed") # calculate the connectivity of the network k=as.numeric (apply (A signed 2))-standardize the connectivity Z.k=scale (k) # set the connectivity screening threshold, this part is the key, filter out the abnormal samples thresholdZ.k=-2.5# and label the abnormal samples outlierColor=ifelse (Z.k)