Merge pull request #32 from compbiocore/develop

Rename VIVA to VariantVisualization and make small docs changes

Author: Fernando Gelin

LICENSE.md

@@ -1,4 +1,4 @@
-The ViVa.jl package is licensed under the MIT "Expat" License:
+The VariantVisualization.jl package is licensed under the MIT "Expat" License:
 
 > Copyright (c) 2018: Computational Biology Core - Data Science Practice - Brown University.
 >

Project.toml

@@ -1,4 +1,4 @@
-name = "VIVA"
+name = "VariantVisualization"
 uuid = "d7f9f8fa-e687-11e8-2c0b-eb4ab256ef6a"
 authors = ["George Tollefson <gatollefson@gmail.com>"]
 version = "0.3.1"

README.md

@@ -1,17 +1,22 @@
-# ViVa.jl
+# VariantVisualization.jl
 
 #### Visualization of Variants
 
 
 | MacOS / Linux | License | Test Coverage | Documentation | Lifecycle |
 | --- | ---- | ------ | ------ | ---- |
-|[![Travis](https://img.shields.io/travis/compbiocore/VIVA.jl/master.svg?style=flat-square)](https://travis-ci.org/compbiocore/VIVA.jl)| [![License](https://img.shields.io/badge/license-MIT-orange.svg?style=flat-square)](https://github.com/compbiocore/VIVA.jl/blob/clean-up/LICENSE.md)| [![Codecov](https://img.shields.io/codecov/c/github/compbiocore/VIVA.jl.svg?style=flat-square)](https://codecov.io/gh/compbiocore/VIVA.jl/branch/master) | [![Docs](https://img.shields.io/badge/docs-stable-blue.svg?style=flat-square)](https://compbiocore.github.io/VIVA.jl/stable) [![Docs](https://img.shields.io/badge/docs-latest-blue.svg?style=flat-square)](https://compbiocore.github.io/VIVA.jl/latest) | ![Lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg?style=flat-square) |
+|[![Travis](https://img.shields.io/travis/compbiocore/VariantVisualization.jl/master.svg?style=flat-square)](https://travis-ci.org/compbiocore/VariantVisualization.jl)| [![License](https://img.shields.io/badge/license-MIT-orange.svg?style=flat-square)](https://github.com/compbiocore/VariantVisualization.jl/blob/clean-up/LICENSE.md)| [![Codecov](https://img.shields.io/codecov/c/github/compbiocore/VariantVisualization.jl.svg?style=flat-square)](https://codecov.io/gh/compbiocore/VariantVisualization.jl/branch/master) | [![Docs](https://img.shields.io/badge/docs-stable-blue.svg?style=flat-square)](https://compbiocore.github.io/VariantVisualization.jl/stable) [![Docs](https://img.shields.io/badge/docs-latest-blue.svg?style=flat-square)](https://compbiocore.github.io/VariantVisualization.jl/latest) | ![Lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg?style=flat-square) |
 
 ## Overview
 
-VIVA.jl is a user-friendly command line tool for creating publication quality graphics from Variant Call Format (VCF) files and has been designed for clinicians and bioinformaticians to explore their VCF files visually. Users can quickly extract genotype or read depth information and plot trends in interactive categorical heatmaps and scatter plots of average read depth values. ViVa.jl offers a robust set of filters to select variants and samples of interest for analysis. ViVa.jl is especially useful in early data exploration for identifying batch effect and sources of poor read depth, as well as identifying distribution of disease causing variants in a set of clinical samples.
+VariantVisualization.jl is a package we built specifically to power the genetics visualization tool, *VIVA*.
 
-## Installation
+*VIVA* is a user-friendly command line tool for creating publication quality graphics from Variant Call Format (VCF) files and has been designed for clinicians and bioinformaticians to explore their VCF files visually. Users can quickly extract genotype or read depth information and plot trends in interactive categorical heatmaps and scatter plots of average read depth values. VIVA offers a robust set of filters to select variants and samples of interest for analysis. VIVA is especially useful in early data exploration for identifying batch effect and sources of poor read depth, as well as identifying distribution of disease causing variants in a set of clinical samples.
+
+To contribute to *VIVA*, developers may use the functions contained 
+
+
+## Getting Started: *Installation*
 
 ### Supported Operating Systems:
 
@@ -23,32 +28,36 @@ Windows 10, Windows 7
 
 ### Command Line Tool
 
-Add VIVA.jl in the Julia Pkg prompt.
+1. Add VariantVisualization.jl in the Julia Pkg prompt.
+2. Download the [VIVA](https://github.com/compbiocore/VariantVisualization.jl/tree/master/VIVA) tool script and save it to a working directory for your analysis.
+3. Navigate to your working directory and follow the [VIVA manual](https://compbiocore.github.io/VIVA.jl/latest) to generate your plots.
 
 ### Jupyer Notebook
 
-Install Jupyter and download the [VIVA Jupyter Notebook]().
+1. [Install Jupyter](https://jupyter.org/install)
+2. Download the [VIVA Jupyter Notebook](https://github.com/compbiocore/VariantVisualization.jl/tree/master/VIVA.ipynb).
+3. Follow the in-notebook instructions to generate your plots.
 
 ### Latest Features
 
-To stay up to date with cutting edge development features install VIVA.jl from the Master branch. 
+To stay up to date with cutting edge development features install VariantVisualization.jl from the Master branch. 
 
 Using git from the command line:
 
 ```
-git clone https://github.com/compbiocore/ViVa.jl
+git clone https://github.com/compbiocore/VariantVisualization.jl
 ```
 
 or from the Julia REPL (useful if using the PowerShell and don't have git installed):
 
 ```julia
 using Pkg
-Pkg.clone("https://github.com/compbiocore/ViVa.jl")
+Pkg.clone("https://github.com/compbiocore/VariantVisualization.jl")
 ```
 
 ## Contributing and Questions
 
 Contributions are welcome, as are feature requests and suggestions. Please open an
 [issue][issues-url] if you encounter any problems or would just like to ask a question.
 
-[issues-url]: https://github.com/compbiocore/VIVA.jl/issues
+[issues-url]: https://github.com/compbiocore/VariantVisualization.jl/issues