Disclaimer: I am not the author of this tool but appreciate it and the work behind it.
Most generally, we can think of genome equivalents as "the equivalent number of genomes" sequenced from your DNA library. In this tool's context, it's the average of the average sequencing depths of a set of prokaryotic single copy genes curated by Nayfach and Pollard, with the idea being that each of these genes usually occur at 1 copy / genome in most prokaryotic genomes. Thus, their sequencing depths ("coverage") are a good proxy for the number of (equivalent) genomes you've sequenced (but not to suggest that this number is discrete -- shotgun sequencing DNA libraries involves sequencing many fragmented genomes so 1 GEQ might actually be fragments from many different genomes [and in metagenomics, likely from many different populations]).
So it would be really erroneous to conflate this metric with the number of bacterial cells you sequenced, bacterial cells in the sample or microbial load, etc.
Disclaimer: I am not the author of this tool but appreciate it and the work behind it.
Most generally, we can think of genome equivalents as "the equivalent number of genomes" sequenced from your DNA library. In this tool's context, it's the average of the average sequencing depths of a set of prokaryotic single copy genes curated by Nayfach and Pollard, with the idea being that each of these genes usually occur at 1 copy / genome in most prokaryotic genomes. Thus, their sequencing depths ("coverage") are a good proxy for the number of (equivalent) genomes you've sequenced (but not to suggest that this number is discrete -- shotgun sequencing DNA libraries involves sequencing many fragmented genomes so 1 GEQ might actually be fragments from many different genomes [and in metagenomics, likely from many different populations]).
So it would be really erroneous to conflate this metric with the number of bacterial cells you sequenced, bacterial cells in the sample or microbial load, etc.