This repository contains the Python code for the outlier detection and PIPs calualtion algorithm of CARMA, originally implemented in R (CARMA on GitHub).
The full repository for the reimplementation of CARMA in Python can be found here.
This is a simplified version of CARMA with the following features:
- It uses only Spike-slab effect size priors and Poisson model priors.
- C++ is re-implemented in Python.
- The way of storing the configuration list is changed. It uses a string with the list of indexes for causal SNPs instead of a sparse matrix.
- Fixed bugs in PIP calculation.
- No credible models.
- No credible sets, only PIPs.
- No functional annotations.
- Removed unnecessary parameters.
Use:
No installation is required; it only has Python code (no C++ code).
See tests for examples.
Notes:
If you want to use it for outlier detection, you can specify the number of iterations to 1 (all_iter=1
); it will be enough.
There are issues when using an LD matrix with a determinant equal to 0. This problem is inherited from the original version and requires investigation.