Merge pull request #142 from jbteves/master

Documentation update for installation and environments in miniconda

README.md

@@ -1,5 +1,4 @@
-tedana: TE Dependent ANAlysis
-=============================
+# tedana: TE Dependent ANAlysis
 
 The ``tedana`` package is part of the ME-ICA pipeline, performing TE-dependent
 analysis of multi-echo functional magnetic resonance imaging (fMRI) data.
@@ -15,41 +14,57 @@ multi-echo functional magnetic resonance imaging (fMRI) data.
 [![Codecov](https://codecov.io/gh/me-ica/tedana/branch/master/graph/badge.svg)](https://codecov.io/gh/me-ica/tedana)
 [![Join the chat at https://gitter.im/ME-ICA/tedana](https://badges.gitter.im/ME-ICA/tedana.svg)](https://gitter.im/ME-ICA/tedana?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
 
-About
------
+## About
 
 ``tedana`` originally came about as a part of the [ME-ICA](https://github.com/me-ica/me-ica) pipeline.
 The ME-ICA pipeline originally performed both pre-processing and TE-dependent
 analysis of multi-echo fMRI data; however, ``tedana`` now assumes that you're
 working with data which has been previously preprocessed.
-If you're in need of a preprocessing pipeline, we recommend
-[fmriprep](https://github.com/poldracklab/fmriprep/), which has been tested
-for compatibility with multi-echo fMRI data and ``tedana``.
 
 ![http://tedana.readthedocs.io/](https://user-images.githubusercontent.com/7406227/40031156-57b7cbb8-57bc-11e8-8c51-5b29f2e86a48.png)
 
-Installation
-------------
+More information and documentation can be found at https://tedana.readthedocs.io/.
 
-You'll need to set up a working development environment to use ``tedana``.
-To set up a local environment, you will need Python >=3.6 and the following
-packages will need to be installed:
+## Installation
 
-- mdp
-- nilearn
-- nibabel>=2.1.0
-- numpy
-- scikit-learn
-- scipy
+You'll need to set up a working development environment to use `tedana`.
+To set up a local environment, you will need Python >=3.6 and the following packages will need to be installed:
 
-You can then install ``tedana`` with:
+[mdp](https://pypi.org/project/MDP/)  
+[numpy](http://www.numpy.org/)   
+[scikit-learn](http://scikit-learn.org/stable/)   
+[scipy](https://www.scipy.org/)    
+[nilearn](https://nilearn.github.io/)     
+[nibabel>=2.1.0](http://nipy.org/nibabel/)      
+
+You can then install `tedana` with
+
+```bash
+pip install tedana
+```
+
+### Creating a miniconda environment for use with `tedana`
+In using `tedana`, you can optionally configure [a conda environment](https://conda.io/docs/user-guide/tasks/manage-environments.html).
+
+We recommend using [miniconda3](https://conda.io/miniconda.html).
+After installation, you can use the following commands to create an environment for `tedana`:
 
 ```bash
+conda create -n ENVIRONMENT_NAME python=3 pip mdp numpy scikit-learn scipy nilearn nibabel
+source activate ENVIRONMENT_NAME
 pip install tedana
 ```
 
-Getting involved
-----------------
+`tedana` will then be available in your path.
+This will also allow any previously existing tedana installations to remain untouched.
+
+To exit this conda environment, use
+
+```bash
+source deactivate
+```
+
+## Getting involved
 
 We :yellow_heart: new contributors!
 To get started, check out [our contributing guidelines](https://github.com/ME-ICA/tedana/blob/master/CONTRIBUTING.md).