Question

Timecourse RNASeq analysis

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Aurora • 0

@c2064d31

Last seen 6 months ago

Italy

Hi everyone,

I have an experiment designed as follows: 5 treatments (control included) at 3 timepoints in 3 cell lines in duplicates. I have a total of 90 samples and I am interested in knowing what happens to each cell line after each treatment over time (from 1 to 48 hrs). I am not sure which package I can use for the purpose. I've been googling around and ImpulseDE2 or moanin are suggested but I am not sure which one is better. In ImpulseDE2 I don't understand how to provide just one metadata that includes all the different treatments and analyse it so that I have control vs trmt1, control vs trmt2, etc...Do I have to refer to batch for it? Or with batch I am clustering the timepoints? About moanin, it seems easy to set the different conditions for the analysis (especially because one of the trmt has 2 controls) but I don't understand the results and how to select the threshold (pval and log2fc) for differential expression. Does anyone have suggestions on the best way/packages to analyse my data? I am new to bioinformatics, sorry if I am a bit naive.

Thanks!

DESeq2 ImpulseDE2 timecour timecoursedata moanin • 469 views

ADD COMMENT • link 6 months ago Aurora • 0

score 0 · Answer 1 · 2024-04-30

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Michael Love 42k

@mikelove

Last seen 3 days ago

United States

There are many choices for time course, and we have an example in our workflow (rnaseqGene).

Otherwise, I recommend to consult a local statistician who can guide your analysis design and model interpretation. There are many comparisons to make and analysis choices.

ADD COMMENT • link 6 months ago Michael Love 42k

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I managed to run ImpulseDE2 as I am interested in getting significant gene changes over time. Now I would like to run deseq as well and compare the results. I was thinking of running this:

dds <- DESeqDataSetFromMatrix(countData = countData, colData = sampleData, 
                             design = ~ Condition + Time + Condition:Time)

ddsLRT <- DESeq(dds, test="LRT", reduced= ~ Condition + Time)

conditions <- cbind(resultsNames(dds))

My conditions are: [1] Intercept, [2] Control vs Case, [3] Time1 vs Time 24, [4] Time 1 vs Time 24, [5] Conditioncontrol.Time24, [6] Conditioncontrol.Time48.

Am I correct in saying that [5] and [6] analyse the differences between control and case at t24 and t48?

Thanks.

ADD REPLY • link 6 months ago Aurora • 0