User: mrigaya.mehra

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Posts by mrigaya.mehra

<prev • 5 results • page 1 of 1 • next >
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Comment: A: RNA-seq analysis across different experiments
... Hi Michael, Sorry for a confusing question. I need to identify genes which show differences in all groups. Like a set of common DE genes between a) antibiotic sensitive and antibiotic resistant strains DE(a) b) different motility adaptations DE(b) c) stress related adaptations DE(c) So I want s ...
written 7 weeks ago by mrigaya.mehra10
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RNA-seq analysis across different experiments
... Hi all, This is a very general question about an analysis I have been trying to do for quite sometime, but I still do not know how to proceed. I have a series of experiments performed on a single organism which include experiments like: comparing antibiotic sensitive and antibiotic resistant strain ...
normalization limma deseq2 design and contrast matrix degenes written 7 weeks ago by mrigaya.mehra10 • updated 6 weeks ago by rrcutler30
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resultnames(dds) not giving correct output
... Hi, I am using DESeq2 to form a contrast between three different conditions as below: shortname    condition Center1    center Center2    center Center3    center Edge1    edge Edge2    edge Edge3    edge Swim1    swim Swim2    swim Swim3    swim   My design is as follows coldata = with(samples ...
deseq2 resultsnames written 9 weeks ago by mrigaya.mehra10 • updated 9 weeks ago by Michael Love13k
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Comment: A: Designing a contrast in DESEQ
... Dear Michael, Thanks for your reply, I have 40 samples from 10 patients. I did follow the example mentioned in the link. I created a group like this dds$group <- factor(paste0(dds$treatment, dds$tissue)) dds$group <- relevel(dds$group, "control_tissue1") design(dds) <- ~ group dds <- ...
written 7 months ago by mrigaya.mehra10
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Designing a contrast in DESEQ
... Hello, I am new to R and DeSEq. I am using DeSeq to identify DE genes in my experiment. The experiment consists of a 2x2 matrix with treatment and control administered in specific tissues. Thus creating 4 different combinations as below 1. treatment_tissue1 2. treatment_tissue2 3. control_tissue ...

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