My view is that this is highly problematic. cDNA generation (for RNA viruses) and other amplification steps during the various library prep methods for different platforms would surely completely obscure the viral load in the original specimen.
Yet in the attached paper they seem very confident about calculating HPV viral load from NGS data.
Matthew,
I agree that it is problematic, and semi-quantitative at best using standards for comparison.
Marcus
I suppose that the authors have calculated viral copy number from abundance of the reads. I agree with Marcus that this may give a semi-quantitative information.
SD
Thanks folks for answers. One metric I found that seems potentially useful for comparing 'relative' abundance of different microbe genomes is RPKM - Reads per Kilobase per Million mapped reads. It's usually used for genes, but I think it could be applied (maybe modified?) to genomes, to correct for both sample sequencing depth and genome length:
RPKM = number of reads mapped to genome/(Length of genome/1000)(total mapped reads/1,000,000)
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