feat: carma outlier detection method

docs/python_api/method/carma.md

@@ -0,0 +1,20 @@
+---
+title: CARMA
+---
+
+CARMA is the method of the fine-mapping and outlier detection, originally implemented in R ([CARMA on GitHub](https://github.com/ZikunY/CARMA)).
+
+The full repository for the reimplementation of CARMA in Python can be found [here](https://github.com/hlnicholls/carmapy/tree/0.1.0).
+
+This is a simplified version of CARMA with the following features:
+
+1. It uses only Spike-slab effect size priors and Poisson model priors.
+2. C++ is re-implemented in Python.
+3. 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.
+4. Fixed bugs in PIP calculation.
+5. No credible models.
+6. No credible sets, only PIPs.
+7. No functional annotations.
+8. Removed unnecessary parameters.
+
+:::otg.method.carma.CARMA

pyproject.toml

@@ -31,6 +31,7 @@ google = "^3.0.0"
 omegaconf = "^2.3.0"
 typing-extensions = "^4.9.0"
 scikit-learn = "^1.3.2"
+pandas = "^2.1.4"
 
 [tool.poetry.dev-dependencies]
 pre-commit = "^3.6.0"