Surrogate variable analysis for paired RNA seq experiment
Hi all,
I have an RNAseq experiment with 1000s of samples. Each sample comes from a patient and was treated either with a drug or DMSO (as control). I am currently deciding between SVA and RUVseq to account for "hidden" technical variation. My question is, if I have identified surrogate variables (regardless of method) and include them in my model like this:
design = ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + ... + condition
Will the surrogate variables also account for the fact that I have a "paired" design (each sample has a control and a treated counterpart)?
Any insights are very much appreciated!
Cheers!
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
Batch Effect Correction in RNA-seq Data Using SVA and DESeq2
written by Nelo •
-
differential gene expression analysis when not all samples have an untreated counterpart
written by nhaus •
-
readTranscriptFeatures from genomation
written by Hwaterma •
-
How does bedtools bamtobed calculate end position
written by timing •
-
How to tidy data with more-than one header, while both headers in long format
written by WUSCHEL
-
R multiple parameters
written by sacha
-
Find surrogate variables with svaseq()
written by Tobias.Wohland
-
Extracting column value from csv file according to if else and & operator
written by shawin •
-
Batch effect in DESeq2 - multiple factor or SVA?
written by Chris Gene
-
Which Cluster Is The Appropriate Cluster For Analysis Of Similar Elements In The Matrix
written by grosy •
