7
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Where to access the WGCNA tutorial documents: Horvath lab site down
Apologies for the web site trouble, we are working with UCLA to restore the web pages. In the meantime, I uploaded the tutorials to Dropbox at https://www.dropbox.com/scl/fo/4vqfiysan6rlurfo2pbnk/h?...
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4
votes
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Question about Co-expression analysis and finding targets for lncRNAs
You have several options to approach this with WGCNA (weighted correlation network analysis). You can run a WGCNA on the combined set, identify modules and select those lncRNAs for further follow-up ...
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3
votes
How to improve this WGCNA analysis
I took a quick look and don't see anything wrong with the module merging. You could lower the merging threshold a bit - 0.95 is very high, I would use 0.9 or 0.85. Other than that though, really ...
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3
votes
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WGCNA co-expression network analysis with less than 20 samples
It's hard to say without knowing how different the subtypes are. If you do a common WGCNA, you may find modules related to the differences between A and B as well as to drivers of expression variation ...
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3
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How to find closely related genes for a specific gene from WGCNA modules?
The simplest way is to re-calculate (or load, if saved) the TOM matrix and find the genes with the highest TOM to MALAT1. If you have enough RAM to carry out WGCNA in a single block, you can use ...
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3
votes
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Coexpression network analysis
igraph is a serious general network theory framework for any given data science application. It permits full directionality and describes vertices (nodes), edges (...
M__♦
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2
votes
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Hierarchical clustering for outlier detection - single cell RNASeq & WGCNA
For outlier identification I suggest using the sample network approach developed by Oldham et al. It basically amounts to constructing a inter-sample connectivity (assuming ...
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2
votes
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Error Code in WGCNA: Dealing with large data sets: block-wise network construction andmodule detection
The problem is that blockwiseModules split your data into (probably 3) blocks, because the default maxBlockSize is 5000 and smaller than the number of genes in your data. If you have enough RAM (16GB ...
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2
votes
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WGCNA error codes in Network Construction & moduel detection
Looks like a bug in the code which I will try to hunt down and fix. In the meantime, I would suggest playing with maxBlockSize argument to blockwiseModules. Try increasing it as much as your available ...
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2
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Question about Co-expression analysis and finding targets for lncRNAs
A cursory search to bedtools documentation will reveal the bedtools closest feature - which might be exactly what you are looking in your third question. You can ...
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2
votes
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WGCNA module preservation analysis
Your question is not clear, you seem to mix the relevant terminology...
First, you cannot run WGCNA for individual samples, only for individual conditions (with or without WT, depending on what ...
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2
votes
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Tree cut issue in WGCNA
It is likely that the cut heights set in the code (80 and 100*ratio of sample numbers) are too low. Look at the sample trees plotted into a pdf file (SampleClustering.pdf) and note the merging heights....
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2
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Parallelizing WGCNA k-means clustering and merging smaller clusters
The bad news is that, indeed, projectiveKMeans is not parallelized and I am not sure how much of it is (easily) parallelizable. The good news is that with 15k features (genes) and 96GB RAM you don't ...
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2
votes
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WGCNA: Problem with selecting soft threshold
Don't worry about it too much. I would go with power 8 based on my general experience (also reflected in WGCNA FAQ) and on the mean connectivity around 50 and median around 20, which seems reasonable ...
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2
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Weighted Network Analysis Book by Steve Horvath, taking the power of a matrix
You CAN calculate M^b for b being float number, complex number or even another matrix.
As well as you can calculate exp(M), log(M), sin(M) whatever... That is very standard for math people.
Let me ...
2
votes
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Importing a WGCNA co-expression network into a networkX graph in Python
You can use exportNetworkToCytoscape or exportNetworkToVisANT to generate and egde list file with the two nodes at the ends and ...
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2
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Find enriched processes in modules obtained by WGCNA
Well, not all modules will have significant enrichment in gene sets such as GO terms or KEGG pathways. In my experience, the smaller modules are often not significantly enriched. They could be the ...
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2
votes
Accepted
Running GSEA or comparable analysis with multiple variable interaction?
I'm not sure I understand "I would like to run GSEA or a similar analysis to find WGCNCA clusters that differ based on the interaction between the two main variables". I would run an ...
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2
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Is it possible to integrate multiple gene expression datasets and use it for WGCNA?
Yes, if the expression datasets are from the same platform, you can merge all the datasets for common genes among them. However, if they are from different platforms then some batch correction needs ...
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1
vote
How to calculate module-trait relationship when trait data is in binary format?
Answer from @m, converted from comment:
Personally I'd build a tree. Whats your question patients or the relationship between RNAseq 'signatures'? Its not the definitive analysis, but its good mining.
...
1
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Which module to select for Pathway analysis based on Module trait correlation and pvalue?
If you can run pathway analysis programmatically on all modules, yes, do it on all modules. Otherwise, select the modules with strongest associations with each subtype, both positive and negative. I ...
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1
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WCGNA - Relate modules with Y features when the % of variance explained of each eigengen is low
Part 1 Just to clarify on the specific issue of using PC1 alone given the reported result ...
Without knowing the underlying ecology, which is important, 30% is too low to any draw conclusions in PCA-...
M__♦
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1
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How can to validate the presence of a certain type of cells in a single cell dataset?
I think the typical way to do this would be to identify a small number of marker genes whose presence and absence is specific for that cell type.
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Tutorial for the WGCNA: changes in heatmap colours
You can add a color palette to the plot.
e.g.
...
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1
vote
no expression for hub genes identified in wgcna
It could be that your modules group together genes (over)expressed in only certain small groups of samples that may be biologically relevant. You would need to check whether the samples in which the ...
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1
vote
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WGCNA hub genes error
The most likely culprit here is that your expression data (the datExpr input to chooseTopHubInEachModule) has no colnames. Check that your data do have appropriate column names. Also check that the ...
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1
vote
Accepted
Does module size decrease as the number of samples increase in WGCNA?
The biggest difference a large number of samples makes is that you can usually decrease the soft thresholding power. If you use power 6 (or 12 for a signed network), try decreasing it to 3 or even 2 (...
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1
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Identifying mutually **exclusive** gene sets
"Mutually exclusive" is not a precise statistical term because it could be seen as independence.
Anyway if truly mutually exclusive AND their behaviour follows periodicity, i.e. sine waves, which it ...
M__♦
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1
vote
Accepted
Module preservation and hub genes finding
Simply select the module(s) you are interested in and look for hub genes using the standard calculations. Having done a module preservation analysis does not change the procedure in the slightest.
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1
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Question about Co-expression analysis and finding targets for lncRNAs
2) If not WGCNA, if I use cor function in R with method Pearson, on
what cutoff I should select the target genes?
Good call, this is a nice approach. It is a good question because the central issue ...
M__♦
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