Hi everyone,
I am new to bioinformatics.
I am trying to align my dual-RNA seq reads to a combined genome - "human and a pathogen" as suggested in a paper (https://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572019000500803&tlng=en ; The combined analysis as the best strategy for Dual RNA-Seq mapping), where the researchers suggested reads aligned to a combined genome is more accurate, so I am trying to copy their method. However, I do not own the bioinformatics tool as suggested in that paper, and I am using Galaxy to analyse my results.
I have aligned my reads to a combined genome (just by concatenating the fasta files) with HISAT2, and I am trying to annotate the reads with a combined gtf file (by concatenating the gtf files) but have failed.
The paper suggested I need to somehow extract my reads first (define which are human and which are fungus) before using the gtf files? But I am not sure what I should be using after HISAT2 if I don't have the bioinformatics tools as suggested in the paper, can anyone teach me what exactly I need to do?
Many thanks, James
The link is broken.
I don't understand why they'd align against each library when tools such as BBSplit and Xenome exist that split reads derived from a mix of cells from multiple organisms.
How did it fail?
I used featurecounts to count my reads and annotate them at the same time with the combined gtf file.
But somehow only human genes were counted and there were way less (only ~1000 genes), which is not possible because I have way more aligned reads when I did my HISAT2 alignment in sequential order separately (for both organism).
So I think somewhere in the annotation process went wrong, somehow the reads were not annotated correctly with the combined gtf file?
Did you try aligning to the two genomes separately to confirm that all your reference files work as expected before merging?
Hi u3005992
How did you perform the Analysis? Can you please explain it?
I have RNA Seq data for Host and parasite together and I want to map eliminate reads mapping to both genome to reduce over quantification.
Technically it's called dual RNA seq analysis. Here is a link from the reference paper I m the following.
https://stm.sciencemag.org/content/scitransmed/suppl/2018/06/25/10.447.eaar3619.DC1/aar3619_SM.pdf
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