Entering edit mode
10 months ago
Gail
•
0
I am trying to do module preservation to two data sets-- healthy and flare.
My input has data expression and module list for each group. But I got an error when i used the module preservation function. Here's my code and the error:
datHealthy <-read.csv("R:/Medicine/Rheumatology/Jawaheer_Lab/Gail/Postpartum/New_project/output/WGCNA/output/T3_PP3-1162024/Healthy_DataExpression.txt", sep="\t", header=T)
datFlare <-read.csv("R:/Medicine/Rheumatology/Jawaheer_Lab/Gail/Postpartum/New_project/output/WGCNA/output/T3_PP3-1162024/Flare_DataExpression.txt", sep="\t", header=T)
# Expression data files for two treatments
# columns = genes, rows = samples
multiExpr = multiData(Set1 = datHealthy, Set2 = datFlare)
# Input module files
# one column for geneID, one for assigned module
Healthymodule=read.csv("R:/Medicine/Rheumatology/Jawaheer_Lab/Gail/Postpartum/New_project/output/WGCNA/output/T3_PP3-1162024/Healthy-modulelist.tsv",sep="\t", header=TRUE)
Flaremodule=read.csv("R:/Medicine/Rheumatology/Jawaheer_Lab/Gail/Postpartum/New_project/output/WGCNA/output/T3_PP3-1162024/Flare/Flare-modulelist.tsv",sep="\t", header=TRUE)
# Create list holding module labels for each set
colorList = list(Set1 = Healthymodule, Set2 = Flaremodule)
# Calculate module preservation statistics
mp = modulePreservation(multiExpr, colorList, referenceNetworks=1,
nPermutations = 1000,
networkType = "signed",
randomSeed = 2905,
quickCor=0,
verbose = 4,
indent = 0)
..checking data for excessive amounts of missing data..
Flagging genes and samples with too many missing values...
..step 1
Flagging genes and samples with too many missing values...
..step 1
..unassigned 'module' name: grey
..all network sample 'module' name: gold
Error in modulePreservation(multiExpr, colorList, referenceNetworks = 1, :
Color vector for set 1 does not have the correct number of entries.