Merge branch 'master' into master

Author: gtollefson

Project.toml

@@ -1,7 +1,7 @@
 name = "VariantVisualization"
 uuid = "7f8bf45c-0ad5-53b5-97e6-33c1305e0aa4"
 authors = ["George Tollefson <gatollefson@gmail.com>"]
-version = "0.4.2"
+version = "0.4.1"
 
 [deps]
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"

README.md

@@ -35,9 +35,9 @@ Add the path to the Julia binaries (C:\Program Files\Julia\bin) to the PATH foll
 
 To add Julia to the PATH on Mac run the following line in the Terminal:
 
-> sudo ln -s /Applications/Julia-1.1.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia
+> sudo ln -s /Applications/Julia-1.2.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia
 
-Be sure to replace "/Applications/Julia-1.1.app/..." to reflect the version of Julia you've downloaded.
+Be sure to replace "/Applications/Julia-1.2.app/..." to reflect the version of Julia you've downloaded.
 
 
 *Linux Note*: To run on remote compute clusters, you may need to load the opengl and julia modules.

docs/src/installation.md

@@ -16,9 +16,9 @@ Add the path to the Julia binaries (C:\Program Files\Julia\bin) to the PATH foll
 
 To add Julia to the PATH on Mac run the following line in the Terminal:
 
-> sudo ln -s /Applications/Julia-1.1.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia
+> sudo ln -s /Applications/Julia-1.2.app/Contents/Resources/julia/bin/julia /usr/local/bin/julia
 
-Be sure to replace "/Applications/Julia-1.1.app/..." to reflect the version of Julia you've downloaded.
+Be sure to replace "/Applications/Julia-1.2.app/..." to reflect the version of Julia you've downloaded.
 
 
 *Linux Note*: To run on remote compute clusters, you may need to load the opengl and julia modules.
@@ -102,7 +102,7 @@ The ***VIVA Jupyter notebook*** is powered by a [main function](https://github.c
 
 ### Running VIVA with Docker or Docker Compose
 
-You can run VIVA using the Docker images we've provided if you don't want to install Julia and the VariantVisualization.jl Julia package. 
+You can run VIVA using the Docker images we've provided if you don't want to install Julia and the VariantVisualization.jl Julia package.
 
 To run VIVA from a Docker image, first [install Docker](https://docs.docker.com/install/).
 

src/plot_utils.jl

@@ -120,8 +120,8 @@ function genotype_heatmap_with_groups(input::Array{Int64,2},title::String,chrom_
                        transpose=true,
 
                                     colorscale = [
-                                                  [0, "rgb(151, 154, 154)"], #dark grey
-                                                  [0.2, "rgb(208, 211, 212)"], #light grey
+                                                  [0, "rgb(208, 211, 212)"], #light grey
+                                                  [0.2, "rgb(151, 154, 154)"], #dark grey
                                                   [0.4, "rgb(255,255,255)"], #white
                                                   #[0.4, "rgb(56,25,90)"], #dark blue
                                                   [0.6, "rgb(51,106,145)"], #blue
@@ -352,8 +352,8 @@ function dp_heatmap2_with_groups(input::Array{Int64,2},title::String,chrom_label
         transpose=true,
 
                      colorscale = [
-                                      [0, "rgb(151, 154, 154)"], #dark grey
-                                      [0.125, "rgb(208, 211, 212)"], #light grey
+                                      [0, "rgb(208, 211, 212)"], #light grey
+                                      [0.125, "rgb(151, 154, 154)"], #dark grey
                                       [0.25, "rgb(255, 255, 255)"],
                                       [0.4, "rgb(153,231,255)"],
                                       [0.5, "rgb(79,146,255)"],

viva

@@ -10,6 +10,7 @@ using VariantVisualization
 println("...")
 
 using Pkg
+
 try
     using GeneticVariation
 catch