Question: Meerkat for identification of somatic structural variations for paired samples
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gravatar for haiying.kong
4 days ago by
haiying.kong120
Germany
haiying.kong120 wrote:

Apparently, I did not read through the manual carefully.

somatic_sv.pl has some parameters that provide information for normal genome.


I am trying to identify somatic structural variations with WES from paired normal and tumor samples by using the software Meerkat. http://compbio.med.harvard.edu/Meerkat/

(1) I read through their manual, but cannot figure out how "somatic" is decided. My understanding is that the software pipleline runs on paired normal sample and tumor sample respectively with slightly different parameter settings and get 2 lists of structural variations. Somatic structural variations are decided by comparing these 2 lists, and this part is not included in the software. I am worrying that the list from tumor would not include all or at least the most of variations in the list from normal. Does any one have any experience with this software? How should I proceed to get somatic structural variations for paired samples?

(2) Could any one please give me the link to download repeat mask file? -R STR /path/to/repeat_mask_file, required, can be downloaded from UCSC

ADD COMMENTlink modified 4 days ago by gdavidson0 • written 4 days ago by haiying.kong120
0
gravatar for haiying.kong
4 days ago by
haiying.kong120
Germany
haiying.kong120 wrote:

I think the rmsk data is: rmsk.txt.gz on the link: http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/

ADD COMMENTlink written 4 days ago by haiying.kong120
0
gravatar for gdavidson
4 days ago by
gdavidson0
France
gdavidson0 wrote:

Hello,

I've used meerkat in the past. Somatic variations are indeed determined by comparing your tumor and normal samples. The script to do this called "somatic_sv.pl" is included in the software in the "scripts" directory. I seem to remember the usage is detailed in the pdf manual where they give examples to perform multiple filtering steps on variants called from your tumor sample.

From my notes they give 4 steps to filter somatic variants:

  • Discard events with breaking point within a certain distance of a breaking point from a variant called in the control sample.
  • Discard events that are supported by discordant read pairs that are also in the control sample.
  • Discard events that are supported by chimeric reads that are also in the control sample.
  • Discard events that are supported by non-uniquely mapped reads that are also in the control sample.

You have parameters you can tweak for all filtering steps. Hope this helps.

ADD COMMENTlink written 4 days ago by gdavidson0
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