I am wanting to carry out differential expression analysis using the DESeq2 package on my rnaseq datasets however I am a novice with most coding related tasks so my ability to understand the jargon in most manuals is limited.

I have a count table for my rnaseq experiment (ReadsPerGene_out_merge_forR). In it are 7 columns:

1. The GeneIDs 2-4. 3x test arm 5-7. 3x control arm.

After reading the manual for DESeq2 I know I must also create a dataset which accounts for the experimental design. I have a table (ReadsPerGene_Meta) with 2 columns: 1. with the identifier for each sample 2. with the nature of the sample (a control or test).

I then do as follows (in the code section) and it produces an error.

I understand that this error states that the number of rows in the design table does not match the number of columns in the counts table. Of course this is true as the counts table has the geneIDs in them. I do not know how to troubleshoot this as I can't add extra rows to the design table.

My questions are therefore:

1. Is there an issue with my respective tables and their format causing the error?
2. Is there an issue with my code input causing the error?

Apologies for the lack of proper statistics/ informatics terms.

```r counts_matrix <- as.matrix(ReadsPerGene_out_merge_forR)

make DESeq2 object from these two:

ddsFullCountTable <- DESeqDataSetFromMatrix(

• countData = counts_matrix,
• colData = ReadsPerGene_Meta,
• design = ~ Test + Control) Error in DESeqDataSetFromMatrix(countData = counts_matrix, colData = ReadsPerGene_Meta, : ncol(countData) == nrow(colData) is not TRUE

You gene names should be row names of the count matrix, just like the vignette shows.