Comparing RNA-Seq and Ribo-Seq
Adding to what benn pointed out, at this line:

dds &lt;- DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~Genotype + Type + Genotype:Type)


You specified that the counts, can be a explained by Genotype (being Control or Viral) or Type (RNAseq or Ribo) or an interaction effect 

What you need is this coefficient, Genotype:Type. To use it, go

res &lt;- results(dds,name="GenotypeViral.TypeRNA")


Based on your setup, you are always comparing RNA to Ribo (see "Type_RNA_vs_Ribo" in resultsNames). If changes to the abundance of a mRNA is similar in RNAseq or Ribo, then the coefficient of the interaction term will be zero and it will be zero in the log2foldchange column in results(res). A positive fold change indicates the log2foldchange between RNA and Ribo is higher in Viral.

If you would like to compare ribo versus and rna-seq, then set RNA as the reference by:

coldata$Type = factor(coldata$Type,levels=c("RNA","Ribo"))
# run deseq again
dds &lt;- DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~Genotype + Type + Genotype:Type)
dds &lt;- DESeq(dds)


With this you will compare by default Ribo versus RNA, and the interaction term will tell you how much more enriched or depleted the ribo fraction is, in the Viral samples.

Would recommend checking the vignette out here:

http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#contrasts