Contents
Why WGCNA?
The idea behind WGCNA is simply to view correlations between gene expression profiles as edge weigths of a graph. That is the correlation matrix is viewed as the adjacency matrix of a graph in which the nodes are genes and the edge weights are the correlations.
What is Wgcna RNA-seq?
WGCNA uses a series of correlations to identify sets of genes that are expressed together in your data set. This is a fairly intuitive approach to gene network analysis which can aid in interpretation of microarray & RNA-seq data.
What’s the difference between a hard threshold function and a soft threshold function?
Hard thresholding is the process of setting to zero the coefficients whose absolute values are lower than the threshold λ . Soft thresholding is another method by first setting to zero coefficients whose absolute values are lower than the threshold λ and then shrinking the nonzero coefficients toward zero.
What is soft thresholding in image processing?
The soft thresholding algorithm presented in this re- port is a greyscale transformation that can be used to visually enhance scanned document images.
How to choose a set of soft thresholding powers?
# Choose a set of soft thresholding powers powers = c(1:10) # in practice this should include powers up to 20. # choose power based on SFT criterion sft = pickSoftThreshold(datExprFemale, powerVector = powers)
What is the your code for soft thresholding?
The following R code illustrates the use of the R function pickSoftThreshold for calculating scale free topology fitting indices R^2corresponding to different soft thresholding powers beta.
What is soft threshold power for co-expression network?
The mean connectivity and scale independence of network modules were analyzed using the gradient test under different power values, which ranged from 1 to 20. The soft threshold power of 9 was chosen based on the scale-free topology criterion. The WGCNA algorithm further identified co-expression modules under these conditions.