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morrislab / phylowgs

Application for inferring subclonal composition and evolution from whole-genome sequencing data.
GNU General Public License v3.0
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High number of populations #115

Closed Rashesh7 closed 8 months ago

Rashesh7 commented 5 years ago

Hi,

I am running phyloWGS on multi-sample data from the same patient. These are multiple sections of the tissue. PhyloWGS is giving me 11 subclonal populations. I have 11 samples with total 210 ssms and 30 cnvs.

Is there any parameter to make the subclonal classifications a bit more strict? Or can you suggest what I can do to get more appropriate results.

Many Thanks, Rashesh

quaidmorris commented 5 years ago

Why do you think that there are too many subpopulations?

Quaid Morris, PhD Professor, The Donnelly Centre, University of Toronto Departments of Molecular Genetics and Computer Science Associate Investigator, Ontario Institute for Cancer Research CIFAR AI Chair, Vector Institute Faculty http://morrislab.ca cell: (416) 220 5796

On Wed, Oct 2, 2019 at 5:32 AM Rashesh notifications@github.com wrote:

Hi,

I am running phyloWGS on multi-sample data from the same patient. These are multiple sections of the tissue. PhyloWGS is giving me 11 subclonal populations. I have 11 samples with total 210 ssms and 30 cnvs.

Is there any parameter to make the subclonal classifications a bit more strict? Or can you suggest what I can do to get more appropriate results.

Many Thanks, Rashesh

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Rashesh7 commented 5 years ago

Hello Quaid,

Sorry that was my misunderstanding. 11 populations are not high in this case. Also singularly each samples have about 2-3 populations represented. Please disregard this issue.

On the other hand, I do have another question, do you have a suggestion for any post script/tool, that would take this subclonal cluster information and estimate the evolution pattern for these multiple samples?

Many thanks for your quick replies.

quaidmorris commented 5 years ago

What would hope to see in an "evolution pattern" that the PhyloWGS clone trees don't provide?

Quaid Morris, PhD Professor, The Donnelly Centre, University of Toronto Departments of Molecular Genetics and Computer Science Associate Investigator, Ontario Institute for Cancer Research CIFAR AI Chair, Vector Institute Faculty http://morrislab.ca cell: (416) 220 5796

On Thu, Oct 3, 2019 at 7:25 AM Rashesh notifications@github.com wrote:

Hello Quaid,

Sorry that was my misunderstanding. 11 populations are not high in this case. Also singularly each samples have about 2-3 populations represented. Please disregard this issue.

On the other hand, I do have another question, do you have a suggestion for any post script/tool, that would take this subclonal cluster information and estimate the evolution pattern for these multiple samples?

Many thanks for your quick replies.

— You are receiving this because you commented. Reply to this email directly, view it on GitHub https://github.com/morrislab/phylowgs/issues/115?email_source=notifications&email_token=ABIZI5TPZ6HZEYXSI2MZMHDQMXJDRA5CNFSM4I4T7SL2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOEAH4KOI#issuecomment-537904441, or mute the thread https://github.com/notifications/unsubscribe-auth/ABIZI5TJYVI75ZQV42SLWWDQMXJDRANCNFSM4I4T7SLQ .

Rashesh7 commented 5 years ago

Hi,

I was looking for something that would covert the tree into sample-based as well as infer some chronological frame of these samples.

Thank you, Rashesh

quaidmorris commented 5 years ago

Hi Rashesh, Sorry, that’s not what PhyloWGS does

On Mon, Oct 7, 2019 at 5:13 AM Rashesh notifications@github.com wrote:

Hi,

I was looking for something that would covert the tree into sample-based as well as infer some chronological frame of these samples.

Thank you, Rashesh

— You are receiving this because you commented.

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-- Quaid Morris, PhD Professor, The Donnelly Centre, University of Toronto Departments of Molecular Genetics and Computer Science Associate Investigator, Ontario Institute for Cancer Research CIFAR AI Chair, Vector Institute Faculty http://morrislab.ca cell: (416) 220 5796