I am trying to analyze data that has three different timepoints (0, 6, and 12 hr) and two conditions (treated and control), but every attempt I make to carry this out with DESeq2 is met with error.
The latest is below, which is an attempt I made using this brief tutorial
counts<-read.csv("E:/Mac_data/macs_counts_11_3_21.csv", header=TRUE)
head(counts)
X Merged_KO_0hr.bam Merged_KO_12hr.bam Merged_KO_6hr.bam Merged_WT_0hr.bam
1 0610005C13Rik 4 3 2 6
2 0610006L08Rik 0 0 0 0
3 0610009B22Rik 1040 509 663 1082
4 0610009E02Rik 14 9 10 8
5 0610009L18Rik 151 62 99 125
6 0610010F05Rik 2524 699 1604 2121
Merged_WT_12hr.bam Merged_WT_6hr.bam
1 1 2
2 0 0
3 540 644
4 15 8
5 45 50
6 683 1318
counts_matrix <- data.matrix(counts)
head(counts_matrix)
X Merged_KO_0hr.bam Merged_KO_12hr.bam Merged_KO_6hr.bam Merged_WT_0hr.bam
[1,] 1 4 3 2 6
[2,] 2 0 0 0 0
[3,] 3 1040 509 663 1082
[4,] 4 14 9 10 8
[5,] 5 151 62 99 125
[6,] 6 2524 699 1604 2121
Merged_WT_12hr.bam Merged_WT_6hr.bam
[1,] 1 2
[2,] 0 0
[3,] 540 644
[4,] 15 8
[5,] 45 50
[6,] 683 1318
#set exp design and coldata
exp_design_file <- file.path("mac_exp_design_11_3.csv")
exp_design <- read.csv(exp_design_file, stringsAsFactors = FALSE)
head(exp_design)
sample Condition Timepoint
1 Merged_WT_0hr.bam treated 0h
2 Merged_WT_6hr.bam treated 6h
3 Merged_WT_12hr.bam treated 12h
4 Merged_KO_0hr.bam control 0h
5 Merged_KO_6hr.bam control 6h
6 Merged_KO_12hr.bam control 12h
head(coldata)
DataFrame with 6 rows and 3 columns
sample Condition Timepoint
<character> <character> <character>
1 Merged_WT_0hr.bam treated 0h
2 Merged_WT_6hr.bam treated 6h
3 Merged_WT_12hr.bam treated 12h
4 Merged_KO_0hr.bam control 0h
5 Merged_KO_6hr.bam control 6h
6 Merged_KO_12hr.bam control 12h
#DESeq2
full_model <- ~ sample + Condition + Timepoint + Condition:Timepoint
reduced_model <- ~ sample + Condition + Timepoint
dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata,
+ design = ~ sample + Condition +
+ Timepoint + Condition:Timepoint)
Error in DESeqDataSetFromMatrix(countData = counts, colData = coldata, :
ncol(countData) == nrow(colData) is not TRUE
I would appreciate any help. I understand WHAT the error message is saying, but I don't know how to fix it.
Additionally, if there is a better way to handle this kind of data I would also appreciate feedback in that regard. I'm here to learn!
•
written
by
cdeantoneo31 •
Look at your data. What is dim(counts)? And why?
I strongly recommend that you put down your own data and go through some sample data from the vignette or a tutorial before you try to analyze your own data. After you've done that, you can do your data side by side, so you can catch when your data isn't looking like it should.
fair enough. do you think this is a good place to start?
http://master.bioconductor.org/packages/release/workflows/html/rnaseqGene.html
I figured it out :) Ty for reminding me to slow down and start with the basics instead of jumping right in with my own data
Hi,
In your case that error message is due to the colnames(counts) do not match, in number or names, the rownames(coldata). For this, I highly recommend you to inspect the number and order of your rownames in the coldata object and verify whether it is the same in the colnames of your counts. If not, use a text plain editor (if you are not familiar with R) to match them and make sure that you have the same number of samples in both objects.
Best regards,
Well, I had the same problem a few months ago and found this tutorial. It solved everything;
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