User: Peter Langfelder

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Posts by Peter Langfelder

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Answer: A: WGCNA parallelization multi thread for blockwiseModules and TOMsimilarity
... I'll try to explain this as best as I can. When calculating TOM from expression data, WGCNA package does some parallelization but this is only performed in correlation calculations, and even those lead to noticeable speedup only when there are many missing values in the expression data which is rare ...
written 9 days ago by Peter Langfelder2.3k
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Comment: C: WGCNA gene significance and module membership
... Your code uses "signed TOM" but an unsigned network. To construct a signed network, you should use argument networkType = "signed" I also recommend doubling the soft thresholding power; alternatively, you can use networkType = "signed hybrid" and keep the power as it is. The results wil ...
written 29 days ago by Peter Langfelder2.3k
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Answer: A: WGCNA gene significance and module membership
... With signed networks, you should not have genes with (strong) negative module membership. Weak negative MM can sometimes happen because topological overlap can connect nodes that have zero adjacencies but this is also not entirely common. Can you post your code (the call to blockwiseModules, if you ...
written 4 weeks ago by Peter Langfelder2.3k
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Comment: C: DeSeq2 Design (A-B)-(C-D)
... If I understand your aim correctly, you want something like pheno.ext = data.frame( AB.vs.CD = as.numeric(Experiment_Groups %in% c(A, B)), AC.vs.BD = as.numeric(Experiment_Groups %in% c(A, C))) Then run DESeq2 or limma on your data, the pheno.ext data frame as colDat ...
written 10 weeks ago by Peter Langfelder2.3k
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Answer: A: Subset WGCNA results for export to Cytoscape
... The simplest solution is to calculate TOM only for the module genes, as Andres suggested. A slight drawback is that the TOM within the module may be slightly different from TOM calculated from all data (or at least data from the relevant block). An alternative is to use the function vectorTOM which ...
written 10 weeks ago by Peter Langfelder2.3k
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Answer: A: WGCNA: 1) low soft thresholding power, 2) large modules, 3) best correlation for
... I'd go with 6 for unsigned or signed hybrid networks, and 12 for signed network. Power 3 is really too low with 55 samples. As Andres mentioned, check the sample clustering tree for large drivers (strong branches); large modules are often the result of having very strong global drivers of expression ...
written 12 weeks ago by Peter Langfelder2.3k
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Answer: A: WGCNA soft threshold with methylation data but no scale-free topology
... (duplicate post deleted, sorry) ...
written 3 months ago by Peter Langfelder2.3k
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Answer: A: WGCNA soft threshold with methylation data but no scale-free topology
... Mean connectivity in the several thousands is a bit too high; I would investigate whether the samples cluster in strong clusters and if so, would probably adjust for the cluster membership. You may also want to adjust for age and sex of the donors, if you have that information. If you don't see anyt ...
written 3 months ago by Peter Langfelder2.3k
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Answer: A: Using WGCNA for purposes other than RNA-SEQ/Microarray
... I'd try to filter on the counts, not on variance, i.e., filter out regions for which the proportion of measurements with number of activated cells bigger than a threshold (say 5) is smaller than a minimum acceptable proportion (e.g., 25%). If you're just log-transforming the data (without other tran ...
written 4 months ago by Peter Langfelder2.3k
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Answer: A: WGCNA sample size minimum: why?
... If you have strong signal and clean data, yes, WGCNA could be informative even with 12 samples. The worst that can happen (with few samples, strong signal and fairly clean data) is that WGCNA won't give you insights that you could not gain from a plain DE analysis. Many of the finer-grain results of ...
written 4 months ago by Peter Langfelder2.3k

Latest awards to Peter Langfelder

Scholar 4 months ago, created an answer that has been accepted. For A: WGCNA - signedKME function
Scholar 11 months ago, created an answer that has been accepted. For A: Question about WGCNA soft thresholding value
Scholar 11 months ago, created an answer that has been accepted. For A: WGCNA - signedKME function
Scholar 11 months ago, created an answer that has been accepted. For A: WGCNA distance measures, clustering with TOM based on adjacency matrix type = "d
Scholar 11 months ago, created an answer that has been accepted. For A: WGCNA blockwiseModules parallelisation question
Scholar 11 months ago, created an answer that has been accepted. For A: WGCNA - soft threshold
Scholar 11 months ago, created an answer that has been accepted. For A: WGCNA | pickSoftThreshold.fromSimilarity not working for input similarity matrix
Teacher 11 months ago, created an answer with at least 3 up-votes. For A: WGCNA: What is `soft thresholding`?
Teacher 11 months ago, created an answer with at least 3 up-votes. For A: WGCNA - Signed vs signed hybrid networks
Teacher 11 months ago, created an answer with at least 3 up-votes. For A: novice: building gene co-expression network using RNA-Seq data
Teacher 11 months ago, created an answer with at least 3 up-votes. For A: WGCNA with paired samples
Teacher 11 months ago, created an answer with at least 3 up-votes. For A: Theoretical WGCNA Question
Appreciated 11 months ago, created a post with more than 5 votes. For A: Theoretical WGCNA Question
Appreciated 11 months ago, created a post with more than 5 votes. For A: WGCNA - Signed vs signed hybrid networks
Good Answer 11 months ago, created an answer that was upvoted at least 5 times. For A: Theoretical WGCNA Question
Good Answer 11 months ago, created an answer that was upvoted at least 5 times. For A: WGCNA - Signed vs signed hybrid networks
Teacher 12 months ago, created an answer with at least 3 up-votes. For A: novice: building gene co-expression network using RNA-Seq data
Scholar 13 months ago, created an answer that has been accepted. For A: WGCNA - signedKME function
Teacher 15 months ago, created an answer with at least 3 up-votes. For A: novice: building gene co-expression network using RNA-Seq data
Guru 19 months ago, received more than 100 upvotes.
Teacher 19 months ago, created an answer with at least 3 up-votes. For A: novice: building gene co-expression network using RNA-Seq data
Teacher 2.5 years ago, created an answer with at least 3 up-votes. For A: WGCNA: overlapping colors in plotDendroAndColors?

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