Hi David,
I'm sorry for a slow response. Relatively recently I solved a problem a bit like this and would be happy to share more information with you. If your genome is small I think it makes sense to map to a reference and identify variant sites. (In my opinion de novo assembly isn't needed - see below).

A basic approach is: groom FASTA file -> map with BWA -> filter SAM (uniquely mapped reads only) -> SAM-to-BAM -> Generate pileup -> Filter pileup

This gives you a position-by-position summary relative to the reference. And that last step is important and needs the most care: you can have it print out differences total numbers of non-reference bases. I can share some information about thresholding how many of these constitute significant evidence that a non-reference base is actually there at that position (basically I use a binomial distribution and ask whether the distribution of ref/non-ref would occur by chance). Given that coverage of small genomes tends to be high, your first question about determining the actual genome sequence (or the quasispecies consensus if you prefer!) can be answered by majority rules: i.e., a small script (or with tools under "Text Manipulation" heading) to read off the base with the most support at each position and then to test whether that base == base in reference nucleotide column.

It's probably also worth thinking about PCR duplicates (from library prep) as these could be a significant source of error, but they are also tricky when many reads will be identical anyway in the input DNA.

Feel free to get in touch with me if you need a bit more clarity and/or some more specifics...

cheers,
Ben

On Apr 4, 2011, at 9:55 PM, Anton Nekrutenko wrote:

From: David Matthews <D.A.Matthews@bristol.ac.uk>
Date: April 4, 2011 6:02:03 PM EDT
Subject: [galaxy-user] Assemble a consensus genome from NGS data

Hi,

Does anyone know how to get a consensus genome from NGS data indicating the percent variance at each nucleotide? I have a small virus genome with manyfold coverage from my transcriptomic run. I'd like to know what the transcriptome indicates is the actual genome plus get a feel for any hotspots where there appears to be significant varience from the reference sequence (i.e. because the reference is wrong or perhaps because of frequent errors in that region due to RNA pol II having a problem accurately transcribing the sequence).

Many thanks!

David


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Benjamin Dickins
Postdoctoral Researcher
Center for Comparative Genomics and Bioinformatics
The Pennsylvania State University
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