User: ysdel

ysdel30
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Posts by ysdel

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... I'm sorry, I wasn't clear in what the problem is. Suppose I have results res1, res2, res3 from correlated tests. And I am interested in genes that satisfy the alternative hypothesis for all of these tests. So I will have to do hits = (res1$padj<0.05) & (res2$padj<0.05) & (res3$padj< ... written 2.3 years ago by ysdel30 2 answers 6.7k views 2 answers ... I am interested in genes that are DE at each time point (i.e. ALL time points) with respect to 0. I ran some simulations for the lm model at http://rpubs.com/ysdel/corpvals and it seems that the tests are correlated. I don't know how to think about this correctly to find the significance levels. ... written 2.3 years ago by ysdel30 2 answers 6.7k views 2 answers ... So if we do results(dds, contrast=list(c("strain_mut_vs_wt","strainmut.minute15"))) and then results(dds, contrast=list(c("strain_mut_vs_wt","strainmut.minute30"))) and on and on and then just select the genes that have an adjusted pvalue less than some threshold for all these tests, would thi ... written 2.3 years ago by ysdel30 1 answer 563 views 1 answer ... I am using DESeq2 for RNAseq analysis. I have 3 conditions (Control, Treatment 1, and Treatment 2). I gave the design matrix formula as ~ replicate + condition. And I get two sets of results as res1 <- results(dds, contrast=c('condition','control','t1')) res2 <- results(dds, contrast=c('con ... written 2.3 years ago by ysdel30 3 answers 14k views 3 answers Comment: C: Batch correction in DESeq2 ... Thank you. Well, plotCounts plots the counts for a single gene, so yes, you can see the batch effects and the treatment effect in the counts. But I was thinking of a way to look at the (all/top) genes like plotPCA does and conclude aha! DESeq2 correctly modeled/removed the batch effects so the log2f ... written 2.3 years ago by ysdel30 1 answer 3.6k views 1 answers ... Thank you very much for explaining this! You're right, there are more up-regulated genes even after considering the Loess line, and there is plausible biological reason for this. I'm still curious though - the MA plot is supposed to detect some artifacts. When do those artifacts arise? ... written 2.3 years ago by ysdel30 1 answer 3.6k views 1 answer ... I have an RNASeq experiment, and I am using DESeq2. After I get the results, I plot the MA plot. This is the output of plotMA: And this is my attempt at the MA plot: res$significant = (res$padj < .05) res$significant = as.factor(res$significant) res$significant[is.na(res\$signific ...
written 2.3 years ago by ysdel30 • updated 2.3 years ago by Ryan C. Thompson7.3k
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Comment: C: Batch correction in DESeq2
... I agree, that is the way DESeq handles batch effects. Is there a way to visualize or diagnose how the batch effects were modeled? For example, I can do plotPCA(rlog(dds)) to plot the PCA showing the batch effects. I model the effects as ~ condition + replicate and compute the results. Now I'd like s ...
written 2.3 years ago by ysdel30
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... If I remove all multi-mapped reads, are the estimates of differential expression still valid. If certain regions of a gene are copies, then all reads mapping exlcusively to them will be ignored. Since this will affect all condtions equally, I am assuming that the estimate of log fold change should b ...
written 4.0 years ago by ysdel30
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... What about http://deweylab.biostat.wisc.edu/rsem/ ? ...
written 4.0 years ago by ysdel30

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Popular Question 4.0 years ago, created a question with more than 1,000 views. For Multiple alignments (multi-mapped reads) and DESeq/edgeR pipeline

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