I have seen some other posts on here but after going through them Im not finding a solution. I am using limma to do DE analysis on 763 patient microarrays, 4 groups total. My expression object is a matrix with rownames as genes and colnames as patient ID.
When I try to run the code I get the error:
> fit <- lmFit(as.numeric(Merge_DF_Avg2), design)
Error in lmFit(as.numeric(Merge_DF_Avg2), design) :
row dimension of design doesn't match column dimension of data object
The dimensions seem correct:
> dim(design)
[1] 763 4
> dim(Merge_DF_Avg2)
[1] 20341 763
> class(Merge_DF_Avg2)
[1] "matrix" "array"
Here is the code:
#Data wrangle for limma
>Merge_DF_Avg <-readRDS("C:/Users/12298/Desktop/Data_Analytics/Taylor_2017/Finalized_Expression_Array_avgs.rds")
>Merge_DF_Avg2 <- Merge_DF_Avg %>% na.omit() %>% pivot_wider(values_from=avg, names_from=Gene_Name) %>% t() %>% janitor::row_to_names(row_number = 1)
>Patient_Cat <- as.vector(as.numeric(Merge_DF_Avg2[1,]))
>Merge_DF_Avg2 <- Merge_DF_Avg2[-c(1,2),] #Taking out patient cat and unidentified gene rows
#limma design
>design <- model.matrix(~ 0 + factor(Patient_Cat))
>colnames(design) <- c("SHH", "Group3", "Group4", "WNT")
>fit <- lmFit(as.numeric(Merge_DF_Avg2), design)
I am using the example code provided by the limma package pdf to guide me.
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leonmcswain •
This worked perfectly! Thank you! You were also correct about the vector it doesn't matter if I state that because the vector goes into design matrix not directly into lmFit. -Leon
Edit
I'm rewriting my answer from yesterday because I've had a closer look at your data wrangling code. Initially, I was unclear why you would not just run lmFit in the usual way with:
fit <- lmFit(Merge_DF_Avg2, design)
On closer look, I see now that your Merge_DF_Avg2 object is almost certainly a data.frame where every column is a character vector and that presumably is why you're running as.numeric. My original answer was to point out that as.numeric returns a dimensionless vector, which obviously causes the dimension error.
If it was me, I would revisit your earlier code by which the expression data was stored and wrangled so that conversion to character didn't occur in the first place. That should be easy to avoid, for example by not making the column names the first row of the data.frame. Character strings are a really poor way to store numeric expression values. But it's up to you. The code from dariober will work, but to me it's repairing a problem that shouldn't have been introduced in the first place.
dariober was correct about this.
OK, my original answer was confusing because I wrote as.vector where I meant to write as.numeric. It was as.numeric(Merge_DF_Avg2) that I was refering to.
I am a Cancer Biologist by training so I still have a bit of work to do regarding R basics (re not introducing these issues to begin with)
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In general, please make it a habit in the future to provide the data using
dput(at least a small chunk of it) to allow reproduction of the problem.I already have an answer to the post but I would like to know more about this. When I post should I just copy and paste the output from dput? For this matrix its a bit chaotic since there are 763 columns. The output gets cut off in the console because its so long.
A small subset of the data is a good idea so one can actually run the code you provide. Yes, just copy paste the dput, one can then easily paste this back into R.