Hello,
I'm currently trying to use Deseq2 but I'm getting confused with some of the conditions. I have multiple individuals that are either Sick or Healthy (that is the main condition I want to use for comparison)
However, those individuals can be also classified into families. For example, Individual 1, 2, 3 and 4 are part of family 1 while individual 5,6,7 and are part of family 2.
Additionally, I sometimes have biological replicates for my individuals. The experiment was based on 3 visits but of course due to experimental issues, not all visit are available for all sample. In summary, my metadata table looks like this:
sample condition family individual
M05-01-V1 Sick M05 M05-01
M05-02-V1 Healthy M05 M05-02
M05-02-V2 Healthy M05 M05-02
M05-02-V3 Healthy M05 M05-02
M05-03-V1 Healthy M05 M05-03
M05-03-V2 Healthy M05 M05-03
M05-03-V3 Healthy M05 M05-03
M05-04-V1 Sick M05 M05-04
M05-04-V2 Sick M05 M05-04
M05-04-V3 Sick M05 M05-04
M06-01-V1 Healthy M06 M06-01
M06-01-V2 Healthy M06 M06-01
M06-02-V1 Sick M06 M06-02
M06-02-V3 Sick M06 M06-02
M06-03-V1 Sick M06 M06-03
M06-04-V2 Healthy M06 M06-04
M06-04-V3 Healthy M06 M06-04
M08-01-V1 Sick M08 M08-01
M08-01-V2 Sick M08 M08-01
M08-01-V3 Sick M08 M08-01
M08-02-V1 Healthy M08 M08-02
M08-02-V2 Healthy M08 M08-02
M08-02-V3 Healthy M08 M08-02
M08-03-V1 Healthy M08 M08-03
My question would be, how could I compare what changes in term of expression between my conditions using both family belonging and biological replicate information as confunder? I did it already for the family level using that piece of code:
ddsMF <- dds
design(ddsMF) <- formula(~ family + condition)
print('Running DESeq on multi-factor data.')
ddsMF <- DESeq(ddsMF)
resultsNames(ddsMF)
resMF <- results(ddsMF, contrast=c("condition", "Sick", "Healthy"))
summary(resMF)
But I wondered how I could also include the biological replicate information. I thought to use ~ family + individual + condition but then I have an error saying:full model matrix is less than full rank since individual information is nested into family.
I've also been linked to solution like this one: http://bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#group-specific-condition-effects-individuals-nested-within-groups But it confuses me a lot since in my case, one individual doesn't have 2 conditions. The sample is either sick or healthy and sometime have replicate and is always part of a family.
What would be the solution then? I'm getting very confused :/ Thanks a lot for your help,
Ben
Thanks a lot for your answer.
But then, if I understand properly, I cannot compare neither across my conditions (sick/healthy) and controlling for the belonging to particular family like I was doing until now with:
Thanks a lot, Ben
You can control for family just by including a blocking term as you have, but not for the replicate measurements per individual. Once you add individual it will be confounded with family, and you won't be able to estimate fixed effects due to the confounding.