morrislab / phylowgs

Application for inferring subclonal composition and evolution from whole-genome sequencing data.
GNU General Public License v3.0
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No trees shown in PhyloWGS Witness #123

Open SwaggerNiels opened 4 years ago

SwaggerNiels commented 4 years ago

After installing a fresh git clone and compiling the mh file, im able to succesfully run the program using:

python2 multievolve.py --num-chains 4 --ssms ssm_data.txt --cnvs cnv_data.txt --burnin-samples 1 --mcmc-samples 1

however, viewing the results gives me an empty window (whenever I open the index.html), while earlier I did see trees there, now somehow it does not work anymore.

after the above succesfull run I use:

mkdir run_name
/usr/bin/python2 write_results.py run_name [mypath]/phylowgs/chains/trees.zip run_name.summ.json.gz run_name.muts.json.gz run_name.mutass.zip
mv ./run_name.* run_name
mv run_name [mypath]/phylowgs/witness/data
cd [mypath]/phylowgs/witness/
gunzip data/run_name/*.gz
python2 index_data.py 

What am i doing wrong? (I am on a remote terminal, so cannot view the http://127.0.0.1:8000 using a server)

Is there another way of opening the visualized output?

serpei commented 3 years ago

Please, can you suggest how to interpret output files without opening the html file? I have the same problem. Thank you, S

SwaggerNiels commented 3 years ago

It has been quite a while, but I believe you can go into the results folder that you defined (in "data") and quite easily retrieve the output data from a json formatted file (ends in "summ.json" i believe).

if you are using python, this file can easily be converted to a dictionary, using the "json" module in python. Be careful and triple check the "negative log likelihood" values that have been defined for each tree, such that you pick the most accurate tree. All the information about the prevalences of the subpopulations and the connections should be in the data structure.

The structure of the json file is quite obvious if you have a look through it.

I hope that helps!

serpei commented 3 years ago

Thank you very much for the suggestion! I will go through the son file you mentioned. I have to select the inferred tree that has the minimum "negative log likelihood” as result right? Thank you again, Serena

On 23 Jul 2021, at 10:51, SwaggerNiels @.***> wrote:

It has been quite a while, but I believe you can go into the results folder that you defined (in "data") and quite easily retrieve the output data from a json formatted file (ends in "summ.json" i believe).

if you are using python, this file can easily be converted to a dictionary, using the "json" module in python. Be careful and triple check the "negative log likelihood" values that have been defined for each tree, such that you pick the most accurate tree. All the information about the prevalences of the subpopulations and the connections should be in the data structure.

The structure of the json file is quite obvious if you have a look through it.

I hope that helps!

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SwaggerNiels commented 3 years ago

Correct

serpei commented 3 years ago

Thank you. Have a nice weekend, Serena

Il ven 23 lug 2021, 22:19 SwaggerNiels @.***> ha scritto:

Correct

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