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Update copyright and version information
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4 changed files with 17 additions and 17 deletions
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@ -2,7 +2,7 @@
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# Main script for performing single-variate BLUP to find beef cattle
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# breeding values
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# Usage: julia beefblup.jl
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# (C) 2019 Thomas A. Christensen II
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# (C) 2020 Thomas A. Christensen II
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# Licensed under BSD-3-Clause License
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# Import the required packages
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@ -12,8 +12,8 @@ using Dates
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using Gtk
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# Display stuff
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println("beefblup v 0.0.0.1")
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println("(C) 2019 Thomas A. Christensen II")
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println("beefblup v 0.1")
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println("(C) 2020 Thomas A. Christensen II")
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println("https://github.com/millironx/beefblup")
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print("\n")
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@ -2,7 +2,7 @@
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# Prepares the Julia environment for using beefblup by installing the requisite
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# packages
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# Usage: julia install.jl
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# (C) 2019 Thomas A. Christensen II
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# (C) 2020 Thomas A. Christensen II
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# Licensed under BSD-3-Clause License
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# Import the package manager
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@ -1,6 +1,6 @@
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BSD 3-Clause License
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Copyright (c) 2018, Thomas A. Christensen II
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Copyright (c) 2020, Thomas A. Christensen II
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All rights reserved.
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Redistribution and use in source and binary forms, with or without
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@ -2,7 +2,7 @@
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% Main script for performing single-variate BLUP to find beef cattle
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% breeding values
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% Usage: beefblup
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% (C) 2018 Thomas A. Christensen II
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% (C) 2020 Thomas A. Christensen II
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% Licensed under BSD-3-Clause License
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% Prepare the workspace for computation
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@ -11,8 +11,8 @@ clc
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close all
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%% Display stuff
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disp('beefblup v. 0.0.0.1')
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disp('(C) 2018 Thomas A. Christensen II')
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disp('beefblup v. 0.1')
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disp('(C) 2020 Thomas A. Christensen II')
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disp('https://github.com/millironx/beefblup')
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disp(' ')
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@ -77,7 +77,7 @@ for i=1:numanimals
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dammatch = ismember(damids, ids(i,:), 'rows');
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damindexes = find(dammatch == 1);
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dam(damindexes) = i;
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% Find all animals that this animal sired
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sirematch = ismember(sireids, ids(i,:), 'rows');
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sireindexes = find(sirematch == 1);
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@ -91,7 +91,7 @@ colstodelete = 6;
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% Coerce each group to string format
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for i = 7:length(headers)
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data(:,i) = cellfun(@num2str, data(:,i), 'UniformOutput', false);
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data(:,i) = cellfun(@num2str, data(:,i), 'UniformOutput', false);
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end
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% Find any columns that need to be deleted
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@ -100,7 +100,7 @@ for i = 7:length(headers)
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colname = headers{i};
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disp(['Column "' colname '" does not have any unique animals and will be removed'])
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disp('from this analysis');
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colstodelete = [colstodelete i];
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colstodelete = [colstodelete i];
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end
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end
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@ -167,19 +167,19 @@ adjustedtraits = cell(1, sum(numgroups)-length(numgroups));
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for i = 1:length(normal)
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% Find the traits that are present in this trait
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traits = uniquecell(data(:,i+5));
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% Remove the "normal" version from the analysis
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normalindex = find(strcmp(traits, normal{i}));
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traits(normalindex) = [];
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% Iterate inside of the group
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for j = 1:length(traits)
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matchedindex = find(strcmp(data(:,i+5), traits{j}));
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X(matchedindex, I) = 1;
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% Add this trait to the string
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adjustedtraits(I - 1) = traits(j);
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% Increment the big counter
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I = I + 1;
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end
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@ -217,7 +217,7 @@ for i = 1:numanimals
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A(j,i) = 0.5*A(j,sire(i));
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A(i,j) = A(j,i);
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end
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A(i,i) = 1;
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A(i,i) = 1;
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else
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for j = 1:(i-1)
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A(j,i) = 0;
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@ -313,7 +313,7 @@ for i = 1:length(numgroups)
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fprintf(fileID, '\t');
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fprintf(fileID, num2str(reliability(I)));
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fprintf(fileID, '\n');
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I = I + 1;
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end
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fprintf(fileID, '\n');
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