cABCanalysis
=============

R and python implementation of the computed ABC Analysis for rational selection of the most informative variables. Features calculation using monotonic splines, edge-case handling (see details [here](https://github.com/AndreHDev/cABC_Analysis/blob/main/R/cABC_special_cases.R)), base R plots as well as GGPLots.

<img width="1072" height="602" alt="cABCExample" src="https://github.com/user-attachments/assets/9612fb9b-6ba9-487d-8235-f6dfb4c6791f" />

Install R package
-----------------
The package can be installed from CRAN:

```r
install.packages("cABCanalysis")
```

from this github repository using the remotes package:

```r
remotes::install_github("AndreHDev/cABC_Analysis")
```

or manually by cloning this repository and running

```r
devtools::install("path/to/cABC_Analysis")
```

Reference
-----------------
If you use this tool in your research, please cite the original publication:

Ultsch A, Lötsch J (2015) "Computed ABC Analysis for Rational Selection of Most Informative Variables in Multivariate Data". PLoS ONE 10(6): e0129767.

[doi:10.1371/journal.pone.0129767](https://doi.org/10.1371/journal.pone.0129767)
