Using age as interger in model.matrix gives me an error
I am trying to do RNA-seq, the thing is that when I include the age variable in the design.matrix(), I get less row dimensions than the columns of the count matrix. This throws an error on running voom().
This problem does not appear if the age variable is not used (i.e all the model variables are factors)
Any ideas?
• 926 views
•
link
updated
by
Gordon Smyth
•
written
by
Omar Mohamed •
•
written
by
Omar Mohamed •
1 answer
Age as an integer should cause no problems. If your experiimental data is correctly specified, then the design matrix will always have the correct number of rows regardless of whether an age covariate is included or not.
You refer to a function design.matrix(), but there is no function by that name in limma or edgeR. The limma and edgeR workflows use model.matrix().
• 0 views
•
link
written
by
Gordon Smyth
Log in to answer this question.
More posts like this
-
Error when looping over multiple columns in a data frame in R
written by Mohamed Samir •
-
How to use limma to find differentially expressed genes in response to a continuous variable
written by pairedttest •
-
What exactly should and shouldn't go in Combat's model matrix?
written by n,n
-
SVA variable of interest in eQTL analysis
written by Colari19
-
Does anyone succeded clustering TCGA data?
written by Omar Mohamed •
-
Integration of microarray and RNA-seq data for machine learning model??
written by Mohamed Omar •
-
Converting FPKM values to raw read counts
written by Mohamed Omar •
-
Clustering of gene expression data with continuous clinical quantitative parameters of different ra…
written by svlachavas
-
JunctionSeq: using continuous covariates, is it possible?
written by dhibar •
-
how to return the componenets from PCA back to original variables?
written by M K
