README.Rmd

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# cocoreg

`cocoreg` is an R-package for extracting shared variation in collections of datasets using regression models. The current stable release is available in CRAN:

[http://cran.r-project.org/package=cocoreg](http://cran.r-project.org/package=cocoreg)

The algorithm is described in the paper:

Using regression makes extraction of shared variation in multiple datasets easy:
Jussi Korpela, Andreas Henelius, Lauri Ahonen, Arto Klami, Kai Puolamäki,
Data Mining and Knowledge Discovery, 2016. 
URL: [http://dx.doi.org/10.1007/s10618-016-0465-y](http://dx.doi.org/10.1007/s10618-016-0465-y)


The authors' version is available in this repository as [cocoreg_plain.pdf](./man/pdf/cocoreg_plain.pdf). The final publication will be available at link.springer.com.

## Usage
A minimal usage example:
```{r, message = FALSE}
library(cocoreg)
dc <- create_syn_data_toy()
ccr <- cocoreg(dc$data)
shared.by.all.df <- variation_shared_by(dc, 'all') #only on synthetic datasets
ggplot_dclst(list(observed = dc$data, shared = shared.by.all.df, cocoreg = ccr$data))

library(reshape) #importing from namespace does not work as expected
ggcompare_dclst(list(shared = shared.by.all.df, cocoreg = ccr$data))
```


## Overview

The most important functions in cocoreg are:

* `cocoreg()` which extracts shared variation from a collection of datasets

* Functions to visualize output such as `ggplot_dclst()` and `ggcompare_dclst()` for lists of data collections, `ggplot_dflst()` for lists of data.frames (i.e. one data collection) and `ggplot_df()` for a single data.frame (a dataset)

## Installation

Install the release version from CRAN:

```{r, eval = FALSE}
install.packages("cocoreg")
```

Or the development version from GitHub:

```{r, eval = FALSE}
# install.packages("devtools")
# library(devtools)
devtools::install_github("bwrc/cocoreg-r")
```