VariantSpark
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aehrc
machine learning for genomic variants
From the JSON tree file extract pair-wise interacting features by making a pair-wise list and counting co-occurrence in the tree. Potentially weighting them by importance.
VariantSpark is currently optimised for reasonally small sample sizes (n=100-5000) and large numbers of variants (e.g. 42 million) , ie. 'wide' datasets. Working on phenotypes in UKBB, e.g. CAD we...
Currently the p-value calculation (using AIR method) is not available in the HAIL implementation of VariantSpark. In order to integrate VariantSpark with downstream annotation and visualisation tools (such as CTGVL,...
An option for VariantSpark to search for optimal parameters using a grid search where users can provide a search grid with parameters to test. There is an implementation in Python...
This is the remaining work from issue: #140 That is: - Add command line option for predicing class probabilities - Implementing command line predictions form JSON serialised model - Adding...
Refactor additive handling of paths like 'spark.jars` in hails configuration.
Align code style check for Scala, Java and Python with InteliJ formatting.
**FAQ for OSX users** Q: Do I need to download the entire source from GitHub to install VS on AWS EMR? A: No, but it's the simplest way to get...
