What tools should I use for Dual RNA-SEQ?

Hi, I am looking into Dual RNA-SEQ. As far as I understand so far, I am gonna end up with FASTQ file(s) that contain(s) reads from both organisms.

It is plausible to think that I can separate the two by using some specific settings in HISAT2? Or other aligners? Or are there better tools for this job? I know is a complicated subject and there are many ways of approaching the situation. I can tell that there are not clear lines when it comes to Dual RNA-SEQ. However, I just want to know if I am going in the right direction.

Thank you.

Hi Sammy,

have you found a solution to your dual RNA seq analysis? I am about to start the same endeavour and was wondering if I can do the alignment of the FASTQ reads twice, first to the host and then to the pathogen genome?

I also came across CAFU: a Galaxy framework for exploring unmapped RNA-Seq data which might be helpful (https://academic.oup.com/bib/article/21/2/676/5349178).

Let me know how you proceeded :slight_smile:


Hi everybody,

I also haves questions related to dual RNAseq (I have samples with fungi A and fungi B growing together). I have got my clean reads fasta files and I am using the tutorial " Reference-based RNA-Seq data analysis" . I am mapping all reads to both reference genomes using START. However, lots of questions started popping up on my head. In my controls where each fungi is growing separately the uniquely mapped reads are over 90% , however in the samples when I have both fungi mappings are much less ( about 40% for fungi A and 20% for fungi B). I have less tissue of fungi B in the sample, so I expect to see less transcripts related to fungi B. In these dual samples, the percentage of transcripts that were not mapped are appearing as % of reads unmapped: too short (these are in some cases about 80% when mapping for fungi B). Are these sequences classified as “too short” because they are not aligning to the reference genome ? shouldnt it appear as mismatches instead? Also, is there a problem in Deseq2 if I use the fungi growing alone to normalize the other samples, since the % of mapped reads were so different?
anybody can help?