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Develop #61

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Jul 17, 2019
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Develop #61

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fix(fixedBugInPlottingSupportFunctions): fixed bug that caused extra …
gtollefson Jul 17, 2019
ba994ea
docs(replacedExampleFiguresInDocs):
gtollefson Jul 17, 2019
4f083b5
Merge branch 'master' into develop
fernandogelin Jul 17, 2019
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13 changes: 8 additions & 5 deletions README.md
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Expand Up @@ -18,7 +18,6 @@ VariantVisualization.jl is a package we built specifically to power the genetics

Note: Once you have set up VIVA, you can quickly run the command line tool [EXAMPLES](https://compbiocore.github.io/VariantVisualization.jl/latest/examples/) found in the documentation.


## Installation

### Supported Operating Systems:
Expand All @@ -33,18 +32,22 @@ Expected Time for Installation: Installation time depends on your network bandwi

### Command Line Tool

1. Add VariantVisualization.jl using Pkg in the Julia REPL:
a. Open the Julia REPL by typing `julia` into the command line
b. Enter the Pkg manager by entering ']' into the REPL
c. Enter `add VariantVisualization` in the Pkg manager. This will install all of VIVA's dependencies.
1. Add VariantVisualization.jl using Pkg in the Julia REPL

* Open the Julia REPL by typing `julia` into the command line
* Enter the Pkg manager by entering `]` into the REPL
* Enter `add VariantVisualization` in the Pkg manager. This will install all of VIVA's dependencies.

2. Download the [VIVA](https://github.com/compbiocore/VariantVisualization.jl/blob/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/VariantVisualization.jl/stable/) to generate your plots.

### Jupyter Notebook

1. [Install Jupyter](https://jupyter.org/install)
2. Install the VariantVisualization.jl Julia package following the Command Line Tool installation instructions above.
3. Download the [VIVA Jupyter Notebook](https://github.com/compbiocore/VariantVisualization.jl/blob/master/VIVA.ipynb).
4. Open the VIVA Jupyter Notebook following the instructions in the [manual](https://compbiocore.github.io/VariantVisualization.jl/latest/).
4. Follow the in-notebook instructions to generate your plots.

### Running VIVA with Docker or Docker Compose
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