dear Daniel,

I would suggest to create a consensus of your seqs in order to create a
"dummy genome", I don't know the design of your experiment. Did you sequence
the whole-genome? what is your sequencing depth? if you have sequencing
depth >30x I would use velvet, but check other software for assembly, maybe
there are others more recent and which not require that much sequencing
depth. That I know, there are no Bioconductor tools for this, but you have
tools to do sequence filtering in Bioconductor and after than you make the
assmbly. Then after creating your dummy genome I would align the reads to
this dummy genome using MAQ. MAQ maps the reads to your ref genome and then
you can also use it to identify SNPs. The creators of MAQ have developed
another aligner called BWA, which I haven't used but comparing studies have
shown that is very good and is faster then MAQ I think. These two aligners
allow you to map reads to your dummy genome and take into account the
quality scores. Other aligners like Bowtie are possible but don't use
quality scores. Then in Bioconductor there are packages to take in the
output and make some statistcs from it.
Regards,
Andreia

On Tue, Nov 16, 2010 at 8:11 AM, <Daniel.Berner@unibas.ch> wrote:

> Dear list
> 1) I have illumina short reads from which I want to call SNPs WITHOUT using
> a reference genome. That is, I want to align the reads among themselves, and
> then screen each alignment for polymorph positions (SNPs) by taking into
> account base call quality. Is there a program that would allow building such
> alignments without reference genome, and that produces output that can be
> input to R/bioconductor?
>  2) Generally, are there R/Bioc implementations for SNP-detection using
> base-call quality?
> Daniel Berner
>
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-- 
--------------------------------------------
Andreia J. Amaral
Unidade de Imunologia Clínica
Instituto de Medicina Molecular
Universidade de Lisboa
email: andreiaamaral@fm.ul.pt
          andreia.fonseca@gmail.com

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