Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/yeolab/flotilla

Reproducible machine learning analysis of gene expression and alternative splicing data
https://github.com/yeolab/flotilla

Last synced: 7 days ago
JSON representation

Reproducible machine learning analysis of gene expression and alternative splicing data

Lists

README 

        
[![Stories in Ready](https://badge.waffle.io/yeolab/flotilla.png?label=ready&title=Ready)](https://waffle.io/yeolab/flotilla)

[![Build Status](https://travis-ci.org/YeoLab/flotilla.svg?branch=master)](https://travis-ci.org/YeoLab/flotilla)

[![Coverage Status](https://img.shields.io/coveralls/YeoLab/flotilla.svg?style=flat)](https://coveralls.io/r/YeoLab/flotilla?branch=master)

[![License](https://img.shields.io/pypi/l/flotilla.svg?style=flat)](https://pypi.python.org/pypi/flotilla/)

[![Downloads](https://img.shields.io/pypi/dm/flotilla.svg?style=flat)](https://pypi.python.org/pypi/flotilla/)

[![Latest Version](https://img.shields.io/pypi/v/flotilla.svg?style=flat)](https://pypi.python.org/pypi/flotilla/)

[![DOI](https://img.shields.io/badge/DOI-10.5281%20%2F%20zenodo.12230-blue.svg)](http://dx.doi.org/10.5281/zenodo.12230)

[![Binder](http://mybinder.org/badge.svg)](http://mybinder.org/repo/YeoLab/flotilla)



flotilla

========



[![Gitter](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/YeoLab/flotilla?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)



![flotilla Logo](flotilla.png)



What is flotilla?

=================



`flotilla` is a Python package for visualizing transcriptome (RNA expression) data from hundreds of

samples. We include utilities to perform common tasks on these large data matrices, including:

 

  * Dimensionality reduction

  * Classification and Regression

  * Outlier detection

  * Network graphs from covariance

  * Hierarchical clustering  

  

And common tasks for biological data including:



  * Renaming database features to gene symbols

  * Coloring/marking samples based on experimental phenotype

  * Removing poor-quality samples (technical outliers)

  

  

Finally, `flotilla` is a platform for active collaboration between bioinformatics scientists and 

traditional "wet lab" scientists. Leveraging [interactive widgets](https://github.com/ipython/ipython/tree/master/examples/Interactive%20Widgets) 

in the [iPython Notebook](http://ipython.org/notebook.html), 

we have created tools for simple and streamlined data exploration including:



  * Subsetting sample groups and feature (genes/splicing events) groups

  * Dynamically adjusting parameters for analysis

  * Integrating external lists of features from the web or local files



These empower the "wet lab" scientists to ask questions on their own and gives bioniformatics

scientists a platform and share their analysis tools.



What flotilla is **not**

========================



`flotilla` is not a genomics pipeline. We expect that you have already generated

data tables for gene expression, isoform expression and metadata. `flotilla` only makes 

it easy to integrate all those data parts together once you have the pieces.



Learn how to use flotilla

=========================

Please refer to our [talks](talks.md) to learn more

 about how you can

apply our tools to your data.



Installation

============



Docker Installation Instructions

--------------------------------



[Docker](https://www.docker.com/whatisdocker/) is the preferred method to obtain the most up-to-date

version of `flotilla`. Every change we make to the source code triggers a new build of a virtual

 machine that contains flotilla and all its dependencies.

 

Please follow instructions [here](docker/docker_instructions.md) to get, install, and run the `flotilla` image.



Local install (on your computer)

--------------------------------



To install, first install the 

[Anaconda Python Distribution](http://continuum.io/downloads), which comes

pre-packaged with a bunch of the scientific packages we use all the time, 

pre-installed.



### Create a Flotilla sandbox

    

We recommend creating a "sandbox" where you can install any and all packages

without disturbing the rest of the Python distribution. You can do this with



    conda create --yes --name flotilla_env --file conda_requirements.txt



You've now just created a "virtual environment" called `flotilla_env` (the first

argument). Now activate that environment with,



    source activate flotilla_env



Now at the beginning of your terminal prompt, you should see:



    (flotilla_env)



Which indicates that you are now in the `flotilla_env` virtual environment. Now

 that you're in the environment, follow along with the non-sandbox

installation instructions.



### Install and update all packages in your environment



To make sure you have the latest packages, on the command line in your 

terminal, enter this command:



    conda install --yes --file conda_requirements.txt



Not all packages are available using `conda`, so we'll install the rest using

`pip`, which is a Python package installer and installs from 

[PyPI](https://pypi.python.org/), the Python Package Index.



    pip install -r requirements.txt

    

Next, to install the latest release of `flotilla`, do



    pip install flotilla

    

If you want the bleeding-edge master version (that we work really hard to make

sure it's always working but could be buggy!), then install the `git` master

with,



    pip install git+git://github.com/yeolab/flotilla.git



Test dataset

============



We have prepared a slice of the full dataset for testing and demonstration purposes.



Run each of the following code lines in its own IPython notebook cell for an interactive feature.



```python

import flotilla

study = flotilla.embark(flotilla._shalek2013)



study.interactive_pca()



study.interactive_graph()



study.interactive_classifier()



study.interactive_lavalamp_pooled_inconsistent()

```



IMPORTANT NOTE: for this test,several failures are expected since the test set is small.

Adjust parameters to explore valid parameter spaces.

For example, you can manually select `all_genes` as the `feature_subset`

from the drop-down menu that appears after running these interactive functions.



Problems? Questions?

====================



We invite your input! Please leave any feedback on our [issues page](https://github.com/YeoLab/flotilla/issues).



![NumFOCUS logo](https://www.continuum.io/sites/default/files/numfocus_logo.png)



Proudly sponsored by a NumFOCUS John Hunter Technical Fellowship to Olga

Botvinnik.