Hi! I am trying to perform differential expression analysis comparing multiple groups at the same time. My sampleTable is the following:
Name Condition Differentiation
AF_MSCs_1 AF_MSCs_1 AF_MSCs low
AF_MSCs_2 AF_MSCs_2 AF_MSCs low
AF_MSCs_3 AF_MSCs_3 AF_MSCs low
F_MSCs_1 F_MSCs_1 F_MSCs medium
F_MSCs_2 F_MSCs_2 F_MSCs medium
F_MSCs_3 F_MSCs_3 F_MSCs medium
M_MSCs_1 M_MSCs_1 M_MSCs medium
M_MSCs_2 M_MSCs_2 M_MSCs medium
M_MSCs_3 M_MSCs_3 M_MSCs medium
NHLF_1 NHLF_1 NHLF high
NHLF_2 NHLF_2 NHLF high
NHLF_3 NHLF_3 NHLF high
When I performed the multivariate analysis to identify differentially expressed genes in the condition taking into account the level of differentiation. I got the following message.
dds <- DESeqDataSetFromMatrix(countData = mymatrix_select,
+ colData = sampleTable,
+ design = ~ Condition + Differentiation)
converting counts to integer mode
Error in checkFullRank(modelMatrix) :
the model matrix is not full rank, so the model cannot be fit as specified.
One or more variables or interaction terms in the design formula are linear
combinations of the others and must be removed.
Please read the vignette section 'Model matrix not full rank':
vignette('DESeq2')
How can I fix this problems?
In addition I would like to compare one condition against all the others condition at once. I tried two approaches: in the first approach I used the LRT function as following:
dds <- DESeq(dds, test="LRT", reduced = ~ 1)
However, I did non understand how to extract the result.
In addition I tried with contrast function applying this command:
res_M_MSCs <- results(dds, contrast=list(c("ConditionAF_MSCs", "ConditionF_MSCs", "ConditionNHLF"), "ConditionM_MSCs"), listValues=c(1/2, -1))
I am not sure how to set the 1/2 parameter to average over the three groups. Should I leave 1/2?
I was wondering which is the best approach to compare multiple groups at the same time.
Thank you!
Concetta
