Machine Learning for Genomic
Project description
GenoML-core
GenoML is an Automated Machine Learning (AutoML) for Genomic. This is the core package of GenoML. this repo is under development, please report any issues (bug, performance, documentation) on the GenoML issues page.
Here are some quick "get started" exmaples, please checkout the additional options and details in the Usage and CLI. In general, use linux or mac with python > 3.5 for best results.
Install
Run:
pip install genoml
Train the ML model
You can use the IPDGC (International Parkinson's Disease Genomics Consortium) test data. This data is a simulation of the genetic and clinical data used for Parkinson's diagnosis in previous publications. You can find it at IPDGC example data.
Download and unzip data:
wget https://github.com/ipdgc/GenoML-Brief-Intro/raw/master/exampleData.zip
unzip exampleData.zip
To train, run:
genoml-train --geno-prefix=./exampleData/training --pheno-file=./exampleData/training.pheno --model-dir=./exampleModel
Final tuned model and performance metrics are stored in the --model-dir
directory.
Using the trained ML model for inference
genoml-inference --model-dir=./exampleModel --valid-dir=./exampleData --valid-geno-prefix=./exampleData/validation --valid-pheno-file=./exampleData/validation.pheno
Valdiation results and model performance metrics are stored in the --valid-dir
directory.
For debugging purposes, include the
-v
or-vvv
flags at the end of a command.
Report issues
Please report any issue or suggestions on the GenoML issues page.
Project details
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