-
Notifications
You must be signed in to change notification settings - Fork 30
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Estimating the abundances of multiple viral genomes #210
Comments
I think probably easiest to use contig mode instead of genome. The only downside is that you cannot output relative abundance. However that is readily calculated from the ratio of the means, perhaps taking into account the number of reads that map. |
Thank you for the quick response! And regarding the output, as I am currently using both |
If you are just using the mean output, I think easiest is just to add the results of the two columns. More complicated for other outputs. |
In this case I am using RPKM |
Hi, Thank you for the amazing tool that has saved a lot of time in my analysis !!! I was following this question and I don't fully understand this: "However that is readily calculated from the ratio of the means, perhaps taking into account the number of reads that map." Does this means? Total mapped reads 10 out of 100 reads
contig_a 2 3.3 3.3 I am sorry if this is nonsense Best, Johan Sebastián |
Hi,
I am currently running
coverm genome
to estimate the abundance of multiple viral genomes in my samples. However I am not sure which is the best way to do this:Is it correct to specify with
--genome-fasta-files
a single FASTA file with all the viral genomes? Should I split this FASTA into files containing only one viral genome per file? (or these 2 options make no difference at all)Should I use the
--reference
option instead?Thank you,
Asier
The text was updated successfully, but these errors were encountered: