Hi all,


I have RNAseq data of non-model organisms, which I'm planning to analyze by de novo assembly with Trinity and write a paper on.

The RNAseq paper contains basic statistics(for example, Total raw reads, Number of gene and Assembly N50 etc).
Are there any rules for these parameters?
I'm a beginner in bioinformatics, so I don't know what parameters are required. 
Can you please advise me?


Thank you very much for your much appreciated help on this!
I think there are no fixed rules for these numbers that would determine if you can or cannot publish. Transcriptomes are easier to assemble than genomes due to less repetitive regions, so, N50 is limited by the actual lengths of transcripts. If your organism has different developmental stages and tissues you should rather devise a good sampling strategy to distribute your funds in order to detect tissue and stage-specific transcripts, or make a good pool of everything. I would say, this is more important than just how many paired-end reads you can afford. I think you can already get something decent from >50M fragments per library which is at the lower end of what you get today.

Wrt. the number of transcripts after assembly, how many transcripts including isoforms do you expect from related species? If you get an absurd number of unigenes (100k+ genes) then you might have to sequence deeper.   

Here is an example of such a paper in Parasites & Vectors: https://parasitesandvectors.biomedcentral.com/articles/10.1186/s13071-020-04442-2#Sec9 (I noticed the authors report rather low % of database hits)

They have ~460M reads in total, that would mean a cost/effect-ratio of 1 Illumina 4000 lane per publication, but I think one can go with less in some journals, and of course you need to analyze the data properly and write something interesting after that.