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xinehc / args_oap

ARGs-OAP: Online Analysis Pipeline for Antibiotic Resistance Genes Detection from Metagenomic Data Using an Integrated Structured ARG Database
MIT License
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Metatranscriptomic Data #48

Open sh1ro-1 opened 7 months ago

sh1ro-1 commented 7 months ago

I have some metatranscriptomic data and I want to run it through ARGs-OAP, is this reasonable? If not, any other suggestions would be greatly appreciated. Thank you so much for taking the time to read this, looking forward to your reply!

xinehc commented 7 months ago

hi,

args-oap can only handle short reads so if your metatranscriptomic data are generated by e.g. Illumina data then ok, but the results may not be directly comparable with metagenomic data.

sh1ro-1 commented 6 months ago

My metatranscriptomic data are generated by Illumina data, so args-oap is available. I have analyzed the RPKM results that I obtained, but I am very confused about why the results may not be directly comparable with metagenomic data, probably because I do not understand the principle well enough. I do not know how to deal with this issue. If possible, I hope you can clear up my confusion, thank you very much.

xinehc commented 6 months ago

RPKM requires normalising against read counts. For metagenomic, reads are randomly distributed along the genomes; for metatranscriptomic, only genes that express will be sequenced. So the total number of reads (normalising constant) has different meaning in metagenomic/metatranscriptomic, which will lead to a difference.

jiaojiaoguan commented 1 month ago

RPKM requires normalising against read counts. For metagenomic, reads are randomly distributed along the genomes; for metatranscriptomic, only genes that express will be sequenced. So the total number of reads (normalising constant) has different meaning in metagenomic/metatranscriptomic, which will lead to a difference.

Hello, I have a question about the RPKM. I think the RPKM for metagenomic and metatranscriptomic are same. For example, in metagenomic,

ARG1 mapped reads number =10 length =1 ARG2 mapped reads number =20 length =2 Then, the RPKM for ARG1 is 101e9/130.

I think the number of the mapped reads for each arg is the same for metagenomic (30) and metatranscriptomic (30). So, the total number of the mapped reads is the same (the normalizing constant is the same).

what do you think of it? Thanks very much for your answer.

Best, jiaojiao