Incorporating RUVg results into ImpulseDE2 model
1
0
Entering edit mode
Mallory ▴ 10
@071d71ad
Last seen 3.1 years ago
United States

Hi all,

I have generated factors of unwanted variation (W_1) via RUVseq/RUVg (with spike-ins), but am having trouble incorporating them into ImpulseDE2. The reason I would like to use ImpulseDE2 because the literature suggests it is a good model for impulse-like treatment conditions and many time points, which our experiment had: we treated trees with a hormone once at the beginning of the timecourse and harvested them every day for 16 days.

In DESeq2, incorporating W_1 would be fairly straightforward, as I would run a LRT with a full model: ~W_1 + time + treatment + treatment:time and a reduced: ~W_1 + time + treatment. However, I am not sure how to incorporate W_1 appropriately into ImpulseDE2. Two options would be to add them as size factors or confounding variables, but I'm not convinced either are appropriate, as my understanding is that W_1 accounts for more than just library size variation and DESeq2 treats W_1 as a covariate, not a confounder. However, I'm not sure if there is a difference here, or if I am misunderstanding.

Any suggestions or clarity would be much appreciated! Thanks for reading.

ImpulseDE2 ImpulseDE ERCC RUVSeq • 1.0k views
ADD COMMENT
1
Entering edit mode
Mallory ▴ 10
@071d71ad
Last seen 3.1 years ago
United States

In case anyone is interested or has this issue, incorporating W_1 into the vecConfounders argument effectively works as a "+" in the model, as verified by the developer.

ADD COMMENT

Login before adding your answer.

Traffic: 459 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6