On Fri, Apr 8, 2011 at 7:42 AM, Mike Dufault <dufau...@yahoo.com> wrote:

> Sean, Anton and Jen,
>
> Thanks for all of the suggestions (in separate replies) on how to better
> analyze my SelectSure captured Exome data. My original work-flow is below in
> the e-mail string.
>
> Based on the suggestions, I plan to change my work-flow by increasing my
> quality filter from 20 to 25-30 and increasing my minimum coverage from 3x
> to ~20x. I will use the Join function to compare the SNPs that are in common
> with the samples from two family members to filter (narrow down) what they
> have in common, since I am looking for a hereditary disease. Then i will use
> the Join function again with the SNPs from build (131) to characterize the
> SNPs.
>

Since you are looking only for variants in common, you can be more lenient
(allow more false-positives per sample), so I would not increase the
coverage that high and rely more on the snp quality filter.


>
> Sean suggested realignment around indels and potentially quality score
> recalibration. Is that even possible with Galaxy at the moment?
>
>

I do not think so.


> Where in the flow can I perform Indel analysis? Will I need to process my
> data separately for SNPs and Indel analysis, or can they be done
> sequentially in the same linear work-flow? I am still a little unsure of the
> best way to hand this.
>
>

This depends on the software being used.  Pileup can call both indels and
SNVs.


> Please let me know if you have any more suggestions or comments before I
> re-launch the analysis later this evening. Once I get a flow that works, I
> hope to be able to publish it for everyone to benefit from.
>
> Thanks to the Galaxy team for an outstanding platform and support!
>
> Mike
> --- On *Tue, 4/5/11, Sean Davis <sdav...@mail.nih.gov>* wrote:
>
>
> From: Sean Davis <sdav...@mail.nih.gov>
>
> Subject: Re: [galaxy-user] Analyzing Targeted Resequencing data with
> Galaxy
> To: "Mike Dufault" <dufau...@yahoo.com>
>
> Cc: "galaxy-user" <galaxy-user@lists.bx.psu.edu>
> Date: Tuesday, April 5, 2011, 4:39 PM
>
>
> Hi, Mike.  See my couple of comments below....
>
> Sean
>
> On Tue, Apr 5, 2011 at 2:22 PM, Mike Dufault 
> <dufau...@yahoo.com<http://us.mc1137.mail.yahoo.com/mc/compose?to=dufau...@yahoo.com>
> > wrote:
>
>   Hi all,
>
>
>
> Like many people on this e-mail chain, I have been looking for advice on
> how to process Exome data. Below, I have described in detail what I have
> done with the hope of getting some clarification. Hopefully it will be
> helpful to many of us!
>
>
>
> I have SureSelect Exome captured data. The data was delivered to me as two
> separate files (/1) & (/2). Each file has ~33 million reads; 7.2 GB each. I
> am looking for SNPs from a family with cancer. Eventually I plan to compare
> the date from multiple members of the same family to find a related disease
> SNP.
>
>
>
> Below is the workflow that I used to process my data. I adapted it from the
> Screencast titles: "Mapping Illumina Reads: Paired Ends Example." I used all
> of the same default parameters as in the screencast.
>
>
>
> At the end of step 13, I had ~4,700,000 SNPs. This seemed like a lot so in
> step 14, I filtered on column 7 (c7) which I believe is the Quality SNP
> value. I set the filter as C7>=1 to remove all of the 0 (zero) values for
> Quality SNP. I figured that if they have a value of zero, they must not be
> real SNPs. This left me with ~180,000 SNPs.
>
>
>
> 1: Get Data: Illumina 1.3+ file (/1)
>
> 2: Get Data: Illumina 1.3+ file (/2)
>
> 3: FASTQ Groomer on data 1
>
> 4: FASTQ Groomer on data 2
>
> 5: FASTQ Summary Statistics on data 3
>
> 6: FASTQ Summary Statistics on data 4
>
> 7: Box plot on data 5
>
> 8: Box plot on data 6
>
> 9: Map with Bowtie for Illumina on data 4 and data 3: mapped reads
>
>
> This might not be the best choice, as bowtie does not allow gapped
> alignment.  See here for a discussion of indels and SNV calling:
>
> http://bioinformatics.oxfordjournals.org/content/26/6/722.long
>
> You will probably also want to consider local realignment around indels and
> potentially quality score recalibration.
>
>
>    10: Filter Sam on data 9
>
> 11: SAM-to-BAM on data 10: converted to BAM
>
> 12: Generate pileup on data 11: converted pileup
>
> 13: Filter pileup on data 12
>
> 14: Filter data on 13 (c7>=1)
>
> 15: Sort on data 15 (C7; descending order)
>
>
>
> First, if anyone has ideas on how to improve the workflow, I would be open
> to suggestions; especially from people experienced with Galaxy.
>
>
>
> Second, I am concerned that many/most of the SNPs are known. Should I
> filter my data against the known SNPdb? If so, how can I do this in Galaxy
> (in Bowtie?)
>
>
> Keep in mind that, depending on the version of dbSNP, there are many
> cancer-associated SNPs contaminating the database.
>
>
>
> Third, as suggested in the screencast, I did not trim or filter my FASTQ
> Groomed data because I was interested in SNPs and I could filter on Quality
> later in the workflow. Would implementing a filtering step on phred quality
> (~20) at this step save me the step of filtering later on. Currently it
> takes multiple hours (~16) to process the data from start to finish, would
> filtering at this step reduce the amount of time that it takes to process my
> data? Presumably, there would be less data to process. I do this on the AWS
> Cloud and time is money!
>
>
>
>
> Adding a gapped alignment algorithm, indel realignment, and quality
> recalibration can easily increase this time to a couple of days per sample.
>
>
>    Fifth, when using Galaxy on the AWS cloud, does adding additional cores
> or adding High CPU ( or both) shorten the time to process the data? When I
> set up extra cores, it appeared that some of them are idle and I don't want
> to pay for idle cores. If anyone could share information on how best to
> manage the cloud, it would be appreciated.
>
>
>
> Finally, what is the difference between “stopping” an instance and
> “terminating” an instance on the cloud? Would I still get charged by AWS if
> I just stop an instance? Any clarification in this area would also be much
> appreciated. Again, time is money!
>
> I hope this helps many of us!
>
>
>
> Unfortunatly, I will not be in Pitt to ask these questions in person.
>
>
>
> Thanks in advance!!!
>
>
>
> Mike
>
>
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