Hi people, I want to use DESeq2 for differentially expression analysis of orthologous genes between two different species. I am not experienced at all using R and DESeq2, but I think at the moment I know most of the basics. I have already my data imported in R for one species and I am currently assemble the rest for the other one. Do you know what is the best way to compare the data between orthologs of two different species, with different gene and transcipt names? How should I import them and then compare them? What I have already tried below is just to visualize differentially expressed genes in one species with a heatmap or elase. Here is my code at the moment. Any ideas? Thank you!

sample_id <- dir('Kal_out') # Kall is the folder with every sample ID
kal_dirs <- sapply(sample_id, function(id) file.path('Kal_out', id))

s2c <- read.csv("samples1.csv") # samples? 
s2c <- dplyr::select(s2c, sample = sampleID, tissue)
s2c <- dplyr::mutate(s2c, path = kal_dirs)

files <- file.path(kal_dirs, "abundance.h5")
names(files) <- dplyr::pull(s2c, sample)

for (abundance in files)
{
  if (file.exists(abundance))
  {
    print(paste0(abundance, " exists!"))
  }else
  {
    print(paste0(abundance, " does not exist!"))
  }
}

tx2gene <- read.csv("transcript_to_gene.csv", header = T, sep = "," )
transcript2gene <-tx2gene[order(tx2gene$geneID),] 

txi <- tximport(files, type = "kallisto", tx2gene = transcript2gene, countsFromAbundance="lengthScaledTPM")
head(txi$counts)
#check txi 
output <- txi$counts

dds2 <- DESeqDataSetFromTximport(txi,
                                 colData = s2c,
                                 design = ~ tissue)
dds <- DESeq(dds2)

"Do you know what is the best way to compare the data between orthologs of two different species, with different gene and transcipt names? "

This has come up before on the support site, and I don't have a great answer. It's quite complicated to even match, let alone control for e.g. the relative abundance problem.