i have some RNAseq data from influenza-infected mouse lungs, and i wanted to be able to quantify the viral reads in the samples.

i've been able to find the sequences for the influenza virus, and manually created a fasta file for it. I was then able to use kallisto to both make an index and perform a pseudoalignment for this, but i now have concerns about the normalization. I know that deseq2 uses inference of similarly distributed genes to normalize count values for genes, and i was thinking that the best way to normalize these values was to somehow create a reference transcriptome of the concatenated mouse transcriptome and influenza transcriptome, and then utilizing deseq2 to do the normalization for me. i would then pull out the normalized reads of the influenza virus to determine the viral titer in each sample.

so my problems that i have now are: (1) how do i concatenate the two fasta files? is it as simple as just adding the two files together? and (2) how do i prepare a reference for tximport to create a dataframe containing both the murine and viral reads at the same time?

presumably once i have (1) and (2) solved, i can just run deseq2 normally and pull out the viral reads individually to determine the titer.

thanks for your input!