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Thread | Thread Starter | Forum | Replies | Last Post |
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#1 |
Junior Member
Location: UK Join Date: Sep 2015
Posts: 2
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Hello all,
I am using DESeq2 for the following analysis: I have RNA-Seq data from 2 tissues and 4 time points, with 4 replicates for each condition. I have two tissues (liver and scn) and four timepoints (3,9,15,21). I'm trying to test for genes where time is a factor, so my full model is Code:
~ tissue + time + tissue:time Code:
~ tissue Code:
> resultsNames(dds) [1] "Intercept" "tissue_scn_vs_liver" "time_9_vs_3" "time_15_vs_3" "time_21_vs_3" [6] "tissuescn.time9" "tissuescn.time15" "tissuescn.time21" I'm thinking pairwise comparisons across time points might be better, even though the number of points is small (4). I'd appreciate any help in building my model better. Thanks! -John Last edited by jaw_bio; 09-17-2015 at 06:56 AM. |
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#2 |
Devon Ryan
Location: Freiburg, Germany Join Date: Jul 2011
Posts: 3,478
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I would suggest using an LRT with a reduced model of "~tissue+tissue:time". That would directly answer the question, "After accounting for tissue-specific differences and interactions, what genes vary with time?" It seems that that's what you're asking. This should expose the typical genes, such as core clock members used in both the SCN and liver.
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#3 | |
Junior Member
Location: UK Join Date: Sep 2015
Posts: 2
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Tags |
circadian, deseq, deseq2, time series |
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