User: Assa Yeroslaviz

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Assa Yeroslaviz • 1.4k
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Posts by Assa Yeroslaviz

<prev • 299 results • page 2 of 30 • next >
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Comment: C: Time-series analysis with DESeq2
... thanks Michael for the fast response. so transferring it from the workflow, something like this should do it for me? ddsTC <- DESeqDataSet(counts, ~ strain + time + strain:time) ddsTC <- DESeq(ddsTC, test="LRT", reduced = ~ strain + time) Does this apply only for cases where I have ...
written 9 months ago by Assa Yeroslaviz • 1.4k
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clarification of time-series analysis
... In [a great post previously answered by @Michael Love][1] I have found his response as such > "strainmut.minute15" is the difference between Mut vs WT at minute 15, **controlling for baseline**. If you add "strain_mut_vs_wt" to this, you get the LFC for Mutant vs WT at minute 15, not controlling ...
deseq2 lrt baseline written 9 months ago by Assa Yeroslaviz • 1.4k • updated 9 months ago by Michael Love ♦ 26k
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Time-series analysis with DESeq2
... I was wondering how one can do a deseq2 analysis of multiple time points when trying to test for a WT vs TREAT difference at any of the given times. Let's say I have three time points (1h,2h,3h) and two conditions (WT, TREAT) In edgeR one can create a contrast matrix and pass the complete matrix t ...
edger deseq2 design matrix time-series written 9 months ago by Assa Yeroslaviz • 1.4k • updated 9 months ago by Michael Love ♦ 26k
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differentail expression analysis with interaction terms
... Hi, I'm working with a data set with three time points (1d, 5d, 10d and four treatments + ctrl treat1, treat2, treat3, treat4). For each of the 15 combinations I have triplicates (in total 45) If I understood it correctly both edger and deseq2 works with this interactions terms to combine multipl ...
edger deseq2 design matrix interaction written 9 months ago by Assa Yeroslaviz • 1.4k • updated 9 months ago by James W. MacDonald ♦ 52k
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Comment: C: shRNA-Seq analysis using edgeR
... Just for the sake of testing I have tried to analyse only the first group of samples from WT (the first 10 samples).  I have created a new DEGList object using only this subset x.WT = new("DGEList") x.WT$counts = as.matrix(WT.table) x.WT$samples$sample <- as.factor(x.WT$samples$sample) x.WT$sa ...
written 12 months ago by Assa Yeroslaviz • 1.4k
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Comment: C: shRNA-Seq analysis using edgeR
... yes I was thinking the same thing. I have already done the QC plots and they do not look like I have expected it to look like: plotBCV: plotMDS and the Smear plots plotSmear(lrtMUT, de.tags = de.genes, main = "MUT smear plot") plotSmear(lrtWT, de.tags = de.genes, , main="WT Smear plot" ...
written 12 months ago by Assa Yeroslaviz • 1.4k
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Comment: C: shRNA-Seq analysis using edgeR
... The contrasts matrix I have seen the problem already and changed it beforehand. the QL-function I haven't so thanks for that remark. But i am not really happy with the results of the differential analysis. I don't get really good results neither for the MUT comparison before against after > t ...
written 12 months ago by Assa Yeroslaviz • 1.4k
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Comment: C: shRNA-Seq analysis using edgeR
... Thanks for the reply and sorry for the late response. when using the makeContrast function for the genotype-specific columns I took contmat = makeContrasts(DiffGentypes = genotypeMut.selectionSelected - genotypeWT.selectionSelected, levels = design) Does this mean that shRNAs with positive value ...
written 12 months ago by Assa Yeroslaviz • 1.4k
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shRNA-Seq analysis using edgeR
... We are doing a loss-of-function shRNA-Seq experiment with 185 shRNA for 37 different genes. We have two conditions (WT and MUT) with each two groups (before and after selection). For each we have five replicate (one only with four0. we have the following sample data: sample condition group A1 WT ...
edger experimental design model.matrix shrnaseq written 12 months ago by Assa Yeroslaviz • 1.4k • updated 12 months ago by Aaron Lun • 25k
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Comment: C: differential expression analysis of cell subtypes mixture
... Thanks Michael for this suggestion. This is one function I haven't seen before. Looking at the `?unmix` information, I was wondering if I understand it correctly.  Using this would mean that in `x` are my samples with the mixed population and `pure` are the samples withe only one subtype. Is this c ...
written 20 months ago by Assa Yeroslaviz • 1.4k

Latest awards to Assa Yeroslaviz

Student 10 months ago, asked a question with at least 3 up-votes. For deseq2 correcting for batch effects
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Voter 2.5 years ago, voted more than 100 times.
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