For a quick breakdown of a variant pipeline, this recent workshop has
slides. Basically you map (BWA is a good choice), choose a variant
caller (Freebayes or other), and look at associated annotation ( SnpEff):
Tools in the group "NGS: QC and manipulation" such as FastQC should be
able to help with quality checks and then others in same group with
manipulations. For the detailed steps of sorting out known SNPs,
synomymous vs non-synonymous, etc, you have a few choices. The tools in
the groups ' NGS: GATK Tools (beta)', ' Phenotype Association', and
'Genome Diversity' are the places to look. Tools have help on the forms,
including links to publications. Or you can look in the tool shed for
more choices to use in your local instance: http://toolshed.g2.bx.psu.edu/
If the data in the shared link is really patient data that is protection
sensitive, I would recommend unsharing the history and deleting the data
permanently from the public Main Galaxy instance.
Good luck with your thesis!
On 7/23/13 2:22 AM, Moritz Juchler wrote:
Hello Ladies and Gentlemen,
I am Moritz Juchler from University Heidelberg. For my Bachelor thesis
I have to setup Galaxy to find SNP's in genomes from hcc patients. I
have a 64-bit openSuse 11.3 server on which I installed Galaxy
locally, since we have a) very large files (>30GB per patient) and b)
the data is protection sensitive.
I have to run this pipeline:
from this paper:
I have in fact some data from exactly these patients, and I want to
reproduce the pipeline as similar as possible. I have this so far:
I would be glad to even do 2-3 steps, I wont need much more for my
thesis. But I find it so hard to find any information about what to do
in Galaxy in practice.
The first step in the workflow of the paper I included are the
statistics on page 1 of the supplements, but those aren't necessary (?).
So the first step I have to do after the alignment and the sam to bam
conversion and the dedupe is the first step on page 2 of the
supplements: "Variant calling Tumor"
Which tool in Galaxy do I have to use in order to do this and the
following steps? Any hints, links to papers or answers are welcome :)
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