Hello,
I have a complex experimental setup.
What I've done:
countTable=read.table("HTSeq_Table.txt", header=T,row.names=1)
And I have a design like this, where the sample names are the row names.
> design
geno age libType
S1534 Ezh1 P14 single
S1536 Ezh1 P14 single
S8633 Ezh1 P14 single
S1532 Ezh12 P14 single
S8631 Ezh12 P14 single
S1141 Ezh12del P14 single
S1142 Ezh12del P14 single
S1541 Wt P14 single
S1547 Wt P14 single
S8Wrep1 Wt W8 paired
S8Wrep2 Wt W8 paired
SE18rep1 Wt E18 paired
SE18rep2 Wt E18 paired
P0.expt1.bio1 Wt P0 single
P0.expt1.bio2 Wt P0 single
P0.expt2.bio1 Wt P0 single
P0.expt2.bio2 Wt P0 single
So, I have multiple timepoint and single/paired-end sequencing, but only one timepoint has multiple genotypes.
To make a DESeqCountDataSet, I ran
> cds=DESeqDataSetFromMatrix(countData=countTable,colData=designnogroup, design=~geno+age+libType)
Error in DESeqDataSet(se, design = design, ignoreRank) :
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
1: I'm not sure how to deal with having a timecourse experiment where only one timepoint has multiple genotypes.
2. Do I need to include single/paired-end?
Thank you so much!
Addendum: I found the answer. In the manual of course.
3.12.1 Linear combinations
I have a complex experimental setup.
What I've done:
countTable=read.table("HTSeq_Table.txt", header=T,row.names=1)
And I have a design like this, where the sample names are the row names.
> design
geno age libType
S1534 Ezh1 P14 single
S1536 Ezh1 P14 single
S8633 Ezh1 P14 single
S1532 Ezh12 P14 single
S8631 Ezh12 P14 single
S1141 Ezh12del P14 single
S1142 Ezh12del P14 single
S1541 Wt P14 single
S1547 Wt P14 single
S8Wrep1 Wt W8 paired
S8Wrep2 Wt W8 paired
SE18rep1 Wt E18 paired
SE18rep2 Wt E18 paired
P0.expt1.bio1 Wt P0 single
P0.expt1.bio2 Wt P0 single
P0.expt2.bio1 Wt P0 single
P0.expt2.bio2 Wt P0 single
So, I have multiple timepoint and single/paired-end sequencing, but only one timepoint has multiple genotypes.
To make a DESeqCountDataSet, I ran
> cds=DESeqDataSetFromMatrix(countData=countTable,colData=designnogroup, design=~geno+age+libType)
Error in DESeqDataSet(se, design = design, ignoreRank) :
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
1: I'm not sure how to deal with having a timecourse experiment where only one timepoint has multiple genotypes.
2. Do I need to include single/paired-end?
Thank you so much!
Addendum: I found the answer. In the manual of course.
3.12.1 Linear combinations
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