Hello,

See my answers below.

On Mon, 2012-03-26 at 17:08 +0530, Sushmita Mookherjee wrote:
> Hi,
> 
> Earlier I used Ray-1.7 successfully for IonTorrent single end reads
> (Total no. of reads ~4 million). Now on another data of same
> sequencing technology I tried to use Ray-1.7 by using the command as
> follows, where the total no. of reads ~3 million:
> 
> mpiexec -n 25 Ray -k 21 -s ../denovo_assembly/GAT_104/
> GAT_104.fastq -o ../denovo_assembly/GAT_104/Ray_output
> 
> But no scaffolds or contigs generated and showed "Rank 0: to deal with
> the sequencing error rate, try to lower the k-mer length (-k)" as an
> error.


Do you have a lower amount of reads in in the unsuccessful run ?

This message has been removed altogether in the upcoming Ray 2.0,
meaning that no peak is required in the coverage depth distribution of
k-mers in your reads.

But usually, you will get a peak for bacterial genomes whereas you won't
for metagenomes or transcriptomes.


> Then, I changed the default k-mer length 21 to 15 and got the output.

I guess you mean the "same output."

>  Can anybody help me to get the answer, why default k-mer length
> didn't work for one data whereas in other it worked fine?
> 

Let me explain here:

Ray slices your reads in smaller sequences called k-mers. In your tests,
you used 15-mers and 21-mers (sequences of length 15 and 21,
respectively).

Then Ray builds a de Bruijn graph from these and indexes your reads in
order to find long paths called contigs.

Paired reads help a lot by the way in the process of constructing long
error-free contigs.

In your successful dataset, the k-mer are distributed in a way that it
is easy, from a global point of view, to say something like "any
position of your target genome is covered, on average, by X k-mer
observations."

In your unsuccessful dataset, there is no peak in the global
distribution, probably because you don't have that much reads.
However, with Ray 2.0 release candidate 5 this is not a problem.

We released 2.0-rc5 today !

http://permalink.gmane.org/gmane.science.biology.ray-genome-assembler/173



> Thanks and Regards,
> 
> Sushmita



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