Hello,

Just out of curiosity, what kind of metagenomes are you dealing with ?


As of Ray v2.0.0-rc8, these 3 parameters no longer exists.
However, the values are still written to the Analysis file because
they are useful for single-genome assemblies.

For a single-genome assembly, you should see a peak.

For a metagenome or transcriptome assembly, these values will not be 
informative.
Usually, the value is not significative because the code that computes 
it needs a peak.


The méta-Ray engine, which is utilised for all assemblies in the 2.0.0 
series, does not rely on these
values.


In this engine, everything is computed locally because you don't usually see
any peak for metagenomes (let's
say gut microbiomes) or transcriptome.
This works well for metagenomes, transcriptomes and single genomes. I 
don't know if it works
for alternative splicing.


In fact, these global values make no sense for metagenomes or transcriptomes
because they are computed on all the de Bruijn graph.

In a metagenome or a transcriptome, the abundance levels follow usually 
something like
a power law, which is really not uniform.

Basically, the technology behind the 2.0.0 series of Ray computes 
coverage distributions
for local discrete objects.

I am submitting my paper tomorrow (finally !) about that, somehow.


Keith Robison a écrit :
> Hello!
>
> Could you comment on when one might want to toy with the coverage 
> options to Ray, and what sort of expected effects these would have
>
> Assembly options (defaults work well)
>
>         -minimumCoverage minimumCoverage
>                Sets manually the minimum coverage.
>                If not provided, it is computed by Ray automatically.
>
>         -peakCoverage peakCoverage
>                Sets manually the peak coverage.
>                If not provided, it is computed by Ray automatically.
>
>         -repeatCoverage repeatCoverage
>                Sets manually the repeat coverage.
>                If not provided, it is computed by Ray automatically.
>
> For a single genome dataset, the CoverageDistribution file:
>
> k-mer length:   21
> Lowest coverage observed:       2
> MinimumCoverage:        14
> PeakCoverage:   58
> RepeatCoverage: 102
> Number of k-mers with at least MinimumCoverage: 17633562 k-mers
> Percentage of vertices with coverage 2: 29.714 %
>
>
> For a large metagenomic dataset, the CoverageDistribution file:
> k-mer length:   21
> Lowest coverage observed:       2
> MinimumCoverage:        240
> PeakCoverage:   241
> RepeatCoverage: 242
> Number of k-mers with at least MinimumCoverage: 11446138 k-mers
> Percentage of vertices with coverage 2: 17.4967 %
>
> Looking at these, I'm now confused by the MinimumCoverage value -- in 
> my metagenomic example it is quite high.  Is this setting the minimum 
> coverage to be included in a contig?


------------------------------------------------------------------------------
Live Security Virtual Conference
Exclusive live event will cover all the ways today's security and 
threat landscape has changed and how IT managers can respond. Discussions 
will include endpoint security, mobile security and the latest in malware 
threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
_______________________________________________
Denovoassembler-users mailing list
[email protected]
https://lists.sourceforge.net/lists/listinfo/denovoassembler-users

Reply via email to