User: Assa Yeroslaviz
Assa Yeroslaviz • 1.4k
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... 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 ...
written 3 months ago by
Assa Yeroslaviz • 1.4k
• updated
3 months ago by
James W. MacDonald ♦ 50k
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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 6 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 6 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 6 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 6 months ago by
Assa Yeroslaviz • 1.4k
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... 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 ...
written 6 months ago by
Assa Yeroslaviz • 1.4k
• updated
6 months ago by
Aaron Lun • 23k
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... 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 14 months ago by
Assa Yeroslaviz • 1.4k
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... Thanks for the fast response. This is what i also thought. I still doubt though, that this is what they are looking for. Maybe a little more background information would help. The experiment is about dendrites in drosophila's brains. We are interested in a neural population which is responsible for ...
written 14 months ago by
Assa Yeroslaviz • 1.4k
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... this is a similar situation to our case with the mixture of samples (from the original post you mentioned).
I was wondering if it is possible to artificially add RNA from tissue X to the second batch of samples (tussues A or B) to create a base line for this changes. similar to Spike-Ins used in a ...
written 14 months ago by
Assa Yeroslaviz • 1.4k
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... I am having trouble understanding the workflow described in the paper. I have a data set of four fastq files from a crispr/cas9 screening experiment as well as a fasta file of the sgRNA used in the analysis (for an example see below). The experiment uses single-indexing strategy with two control sam ...
written 14 months ago by
Assa Yeroslaviz • 1.4k
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