User: apfelbapfel

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Posts by apfelbapfel

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Comment: C: FDR does not change between genes in edgeR
... My apologies for unclear terminology. You are absolutely correct, the number of genes goes down from around 46000 to 12000. I will work on your suggestions, but the experimentalists have now told me that they barely had any RNA to begin with, so I assume its really a problem of low quality data. T ...
written 13 days ago by apfelbapfel0
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Comment: C: FDR does not change between genes in edgeR
... Hey Gordon. sorry for the late reply, was traveling. i have to say that this comment of yours confuses me, will i test for DE if using design <- model.matrix(~ y$samples$group)? regarding filtering, library sizes changed for example from 7849976 to 7814960, which I would argue is not much.  ...
written 14 days ago by apfelbapfel0
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Comment: C: FDR does not change between genes in edgeR
... Good points. I am assuming its due to the heterogeneity in the treated individuals, the dont cluster at all. I had run it now in DEseq2, bc I am still learning and thought its good to practice. DEseq2 finds 26 DE genes, how is your experience with regards to trustworthiness of such diverging result ...
written 18 days ago by apfelbapfel0
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Comment: C: FDR does not change between genes in edgeR
... Many thanks to Aaron and Gordon. That mistake with the code was really important to know. Unfortunately still nothing significant to be found, the PI wont be happy. ...
written 18 days ago by apfelbapfel0 • updated 13 days ago by Gordon Smyth36k
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Comment: C: FDR does not change between genes in edgeR
... please just tell me if any further info would be helpful! ...
written 19 days ago by apfelbapfel0
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Comment: C: FDR does not change between genes in edgeR
... The following specs are relevant: After filtering (<1% was removed) group lib.size norm.factors 1 1 7814960 0.9844539 2 1 3638388 0.9664794 3 2 12624890 1.0205424 4 2 10289325 1.0223115 5 1 5545574 0.9718041 6 1 8192437 1.0549536 7 2 4185595 ...
written 19 days ago by apfelbapfel0
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FDR does not change between genes in edgeR
... HI all I am analyzing an RNAseq dataset to find DE genes using edgeR. Strangely I get no significantly differentially expressed genes, and the same FDR for every gene when summarizing the results. I ran the same code on  a public dataset and got fine results, so I guess it has something to do with ...
rnaseq edger written 20 days ago by apfelbapfel0 • updated 13 days ago by Gordon Smyth36k
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RNAseq analysis: what comes first, filtering or normalization
... Hi there please excuse my very basic questions, but I was not able to find appropriate answers using searchengines. I am trying to analyze a small dataset of the RNAseq of  3 vs 3 samples to identify differentially expressed genes and do some multivariate statistics. Due to the low sample size I c ...
rnaseq edger R written 24 days ago by apfelbapfel0 • updated 22 days ago by Aaron Lun22k
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Answer: A: choose between normalization techniques for OTU counts
... Thanks for the reply. Since i was on a very tight deadline i went with Deseq2 now, but will definitely check out your reply for next time! ...
written 10 months ago by apfelbapfel0
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(Closed) choose between normalization techniques for OTU counts
... Hello After having noticed some spurious results in my data set I wanted to contact this expert community here to get help with choosing the right normalization approach for my data. I have two groups, patients and healthy controls, where microbiota OTUs have been measured from biopsies: Quality f ...
normalization edger deseq2 R written 10 months ago by apfelbapfel0

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