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README.md

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@@ -82,3 +82,59 @@ How to develop on the project locally.
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10. Use `python app.py` to run the Flask service app in debug mode. Service will be available at http://localhost:8080/
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11. Use `make docker-build` to build a docker image using the current `Dockerfile`.
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12. `make docker` will build and run the docker image with the service. Service will be available at http://localhost:8080/
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# Runing a minimal configuration example
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From the main directory of the repo run:
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```
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scripts//build-imputation-validation.sh
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```
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This will pepare and load frequency data into the graph and run imputation on a sample set of subjects.
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The execution is driven by the configuration file:
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`conf/minimal-configuration.json`
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It takes input from this file:
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```
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data/subjects/donor.csv
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```
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And genrates an `output` directory with these contents:
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```
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output
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├── don.miss
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├── don.pmug
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├── don.pmug.pops
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├── don.problem
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├── don.umug
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└── don.umug.pops
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```
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The .miss and .problem files are cases contain cases that failed due to errors.
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The .pmug file contains the Phased Multi-locus Unambiguous Genotypes.
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The .umug file contains the Unphased Multi-locus Unambiguous Genotypes.
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The format of both files is (csv):
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* id
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* genotype - in glstring format
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* frequency
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* rank
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The .pmug.pops and .umug.pops contain the corresponding population assignments.
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The format of the .pops files is (csv):
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* id
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* pop1
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* pop2
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* frequency
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* rank

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