User: bilcodygm

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bilcodygm0
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Posts by bilcodygm

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Limit on significant genes for TMM normalization
... I have done analysis on a dataset in which control samples were compared with treated samples. It is a small pilot which served to compare 2 technologies (Nanostring and Edgeseq). This is basically RNAseq data, so counts. What I have done is use TMM with quasi-likelihood testing and on the other han ...
normalization edger tmm quantile normalization written 20 months ago by bilcodygm0 • updated 20 months ago by Gordon Smyth38k
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Comment: C: quantile normalization takes into account library size?
... Thanks, Gordon! It was just, that with quantile normalization it is not so directly transparent from the normalized counts and library sizes how to arrive at the normalized counts.   ...
written 20 months ago by bilcodygm0
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quantile normalization takes into account library size?
... Hi all, I have been looking around for this in the already-asked questions, but I could not find it, so I am sorry, if this has been asked before. I would like to use quantile normalization. What I am doing is looking at 2 datasets in which treated samples are compared with control samples. The co ...
quantile normalization limma-voom written 20 months ago by bilcodygm0 • updated 20 months ago by Gordon Smyth38k
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Comment: A: upperquartile with voom
... Thank you for taking the time to reply! It was just my uncertainty of using the commands.  I am trying to compare different normalization methods with different statistical testings (basically TMM, upperquartile, quantile and DESeq2's default method across with RLT, QLF (both edgeR) and with voom- ...
written 21 months ago by bilcodygm0
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Comment: C: assess quality of data
... Thank you for your reply! I was a bit quick in adding limma and DESeq2 maybe. What I have done is a comparison of several normalization methods (TMM, upperquartile, quantile and DESeq2's default method) together with the tests (RLT, QLF in edgeR and voom-eBayes in limma) they all show this large va ...
written 21 months ago by bilcodygm0
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assess quality of data
... Dear all, Please help me. I have RNAseq data, which I normalized with TMM and then applied the likelihood ratio test (edgeR). when I look at the BCV plot I see this: The red dots, are the significant genes in the dataset. Is this OK? Are all the data points not too wide spread? Thank you for yo ...
rnaseq edger limma-voom written 21 months ago by bilcodygm0 • updated 21 months ago by Michael Love25k
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upperquartile with voom
... Hi all, I was just wondering whether it would make sense to combine the upperquartile normalization with limma-voom analysis of RNAseq data. this is just out of interest, not driven by the data or so. At first, I did uq <- DGEList(counts=initDGE, group=responseStatus) uq <- calcNormFactors( ...
rnaseq normalization limma-voom written 21 months ago by bilcodygm0

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