Anchor is a python package to estimate modality of splicing, percent methylated, any data that is normalized between 0 and 1

## Project description

![Anchor logo](https://raw.githubusercontent.com/YeoLab/anchor/master/logo/v1/logo.png)

## What is anchor?

Anchor is a python package to find unimodal, bimodal, and multimodal features in any data that is normalized between 0 and 1, for example alternative splicing or other percent-based units.

* Documentation: https://YeoLab.github.io/anchor

## Installation

To install anchor, we recommend using the
[Anaconda Python Distribution](http://anaconda.org/) and creating an
environment, so the anchor code and dependencies don't interfere with
anything else. Here is the command to create an environment:


conda create -n anchor-env pandas scipy numpy matplotlib seaborn


### Stable (recommended)

To install this code from the Python Package Index, you'll need to specify anchor-bio (anchor was already taken - boo).


pip install anchor-bio


### Bleeding-edge (for the brave)

If you want the latest and greatest version, clone this github repository and use pip to install


git clone git@github.com:YeoLab/anchor
cd anchor
pip install . # The "." means "install *this*, the folder where I am now"


## Usage

anchor was structured like scikit-learn, where if you want the "final
answer" of your estimator, you use fit_transform(), but if you want to see the
intermediates, you use fit().

If you want the modality assignments for your data, first make sure that you
have a pandas.DataFrame, here it is called data, in the format (samples,
features). This uses a log2 Bayes Factor cutoff of 5, and the default Beta
distribution parameterizations (shown [here]())

python
import anchor

bm = anchor.BayesianModalities()
modalities = bm.fit_transform(data)


If you want to see all the intermediate Bayes factors, then you can do:

python
import anchor

bm = anchor.BayesianModalities()
bayes_factors = bm.fit(data)


## History

### 1.1.1 (2017-06-29)

- In infotheory.binify, round the decimal numbers before they are written as strings

### 1.0.1 (2017-06-28)

- Documentation and build fixes

### 1.0.0 (2017-06-28)

* Updated to Python 3.5, 3.6

### 0.1.0 (2015-07-08)

* First release on PyPI.

## Project details

Uploaded source