[khmer] diginorm on merged reads

[John Stanton-Geddes]

Hi Torsten,
Great to hear of similar results! As I'm still learning about this
transcriptome assembly business, can I ask how you came to choose k=61 for
the Oases assembly?


On Mon, Oct 7, 2013 at 8:00 PM, Torsten Seemann
<torsten.seemann at monash.edu>wrote:

>
>> Following up on my previous question - I ran a few different assemblies
>> exploring the effect of using khmer digital normalization and FLASH to
>> merge short reads. I compared the results of (1) running diginorm only, (2)
>> running diginorm than attempting to merge still-paired reads with FLASH,
>> and (3) first attempting to merge paired reads with FLASH followed by
>> diginorm. In all cases, I used trimmed-and-filtered reads and performed
>> assembly using velvet-oases with a kmer of 21. Below are some assembly
>> statistics.
>>
>
> I can confirm a similar result with a massive 200M read mouse-ish RNA-Seq
> data set.
>
> Using FLASH to overlap first giving ~280 bp SE reads, then doing Diginorm
> (k=??) then  using Oases (k=61)  gave the 'best' txome assembly compared to
> feeding read pairs. (and Trinity did 'worse' on everything, no matter what
> we did, and took 1 week for each run).
>
> It will eventually get published.
>
> --
> *--Dr Torsten Seemann
> --Scientific Director : Victorian Bioinformatics Consortium, Monash
> University, AUSTRALIA*
> *--Acting Head : Life Sciences Computation Centre, VLSCI, Parkville,
> AUSTRALIA
> --http://www.bioinformatics.net.au/*
>
>


-- 
Postdoctoral Research Associate
Department of Biology, University of Vermont
Room 211, Marsh Life Science Building
109 Carrigan Drive
Burlington, Vermont 05405
www.johnstantongeddes.org
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