Entering edit mode
6 months ago
Nicolas
•
0
Hello im having troubles with WGCNA generating the TOMfiles the code aappears to run correctly but whrn i check eh bwnet object it has a TOMfiles NULL value
This is the code im using
gsg <- goodSamplesGenes(t(mcounts))
summary(gsg)
gsg$allOK
table(gsg$goodGenes)
table(gsg$goodSamples)
Wdds <- DESeqDataSetFromMatrix(countData = mcounts,
colData = metadata,
design = ~ 1)
Wdds75 <- Wdds[rowSums(counts(Wdds) >= 15) >= 8,]
nrow(Wdds75)
Wdds_norm <- vst(Wdds75)
tcounts <- assay(Wdds_norm) %>%
t()
power <- c(c(1:10), seq(from = 12, to = 50, by = 2))
sft <- pickSoftThreshold(tcounts,
powerVector = power,
networkType = "signed",
verbose = 5)
sft_data <- sft$fitIndices
a1 <- ggplot(sft_data, aes(Power, SFT.R.sq, label = Power)) +
geom_point() +
geom_text(nudge_y = 0.1) +
geom_hline(yintercept = 0.8, color = "#C21807") +
labs(x = "Power", y = "Scale free topology model fit, signed R^2") +
theme_classic()
a2 <- ggplot(sft_data, aes(Power, mean.k., label = Power)) +
geom_point() +
geom_text(nudge_y = 0.1) +
labs(x = "Power", y = "Mean Conectivity") +
theme_classic()
grid.arrange(a1, a2, ncol = 2)
tcounts[] <- sapply(tcounts, as.numeric)
soft_power <- 16
temp_cor <- cor
cor <- WGCNA::cor
bwnet <- blockwiseModules(tcounts,
maxBlockSize = 15000,
TOMType = "signed",
power = soft_power,
mergeCutHeight = 0.25,
numericLabels = FALSE,
randomSeed = 1234,
verbose = 3)
cor <- temp_cor
module_eigengenes <- bwnet$MEs
head(module_eigengenes)
table(bwnet$colors)
plotDendroAndColors(bwnet$dendrograms[[1]], cbind(bwnet$unmergedColors, bwnet$colors),
c("unmerged", "merged"),
dendroLabels = FALSE,
addGuide = TRUE,
hang= 0.03,
guideHang = 0.05)
The output from blockwisemodules is this
Calculating module eigengenes block-wise from all genes
Flagging genes and samples with too many missing values...
..step 1
..Working on block 1 .
TOM calculation: adjacency..
..will not use multithreading.
Fraction of slow calculations: 0.000000
..connectivity..
..matrix multiplication (system BLAS)..
..normalization..
..done.
....clustering..
....detecting modules..
....calculating module eigengenes..
....checking kME in modules..
..removing 1 genes from module 14 because their KME is too low.
..reassigning 2 genes from module 1 to modules with higher KME.
..reassigning 1 genes from module 5 to modules with higher KME.
..merging modules that are too close..
mergeCloseModules: Merging modules whose distance is less than 0.25
Calculating new MEs...
The dimentions of my data are 10 14379
https://www.rdocumentation.org/packages/WGCNA/versions/1.72-5/topics/blockwiseModules
note the
saveTOMs
argument.