millironx/beefblup
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Update copyright and version information

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This commit is contained in:
Thomas A. Christensen II 2020-02-16 15:58:57 -08:00
parent 692a499147
commit b8b8f755d6
Signed by: millironx
GPG key ID: 139C07724802BC5D
4 changed files with 17 additions and 17 deletions
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6
Julia/beefblup.jl
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@ -2,7 +2,7 @@
# Main script for performing single-variate BLUP to find beef cattle # Main script for performing single-variate BLUP to find beef cattle
# breeding values # breeding values
# Usage: julia beefblup.jl # Usage: julia beefblup.jl
# (C) 2019 Thomas A. Christensen II # (C) 2020 Thomas A. Christensen II
# Licensed under BSD-3-Clause License # Licensed under BSD-3-Clause License
# Import the required packages # Import the required packages
@ -12,8 +12,8 @@ using Dates
using Gtk using Gtk
# Display stuff # Display stuff
println("beefblup v 0.0.0.1") println("beefblup v 0.1")
println("(C) 2019 Thomas A. Christensen II") println("(C) 2020 Thomas A. Christensen II")
println("https://github.com/millironx/beefblup") println("https://github.com/millironx/beefblup")
print("\n") print("\n")

2
Julia/install.jl
View file

@ -2,7 +2,7 @@
# Prepares the Julia environment for using beefblup by installing the requisite # Prepares the Julia environment for using beefblup by installing the requisite
# packages # packages
# Usage: julia install.jl # Usage: julia install.jl
# (C) 2019 Thomas A. Christensen II # (C) 2020 Thomas A. Christensen II
# Licensed under BSD-3-Clause License # Licensed under BSD-3-Clause License
# Import the package manager # Import the package manager

2
LICENSE.md
View file

@ -1,6 +1,6 @@
BSD 3-Clause License BSD 3-Clause License
Copyright (c) 2018, Thomas A. Christensen II Copyright (c) 2020, Thomas A. Christensen II
All rights reserved. All rights reserved.
Redistribution and use in source and binary forms, with or without Redistribution and use in source and binary forms, with or without

24
MATLAB/beefblup.m
View file

@ -2,7 +2,7 @@
% Main script for performing single-variate BLUP to find beef cattle % Main script for performing single-variate BLUP to find beef cattle
% breeding values % breeding values
% Usage: beefblup % Usage: beefblup
% (C) 2018 Thomas A. Christensen II % (C) 2020 Thomas A. Christensen II
% Licensed under BSD-3-Clause License % Licensed under BSD-3-Clause License
% Prepare the workspace for computation % Prepare the workspace for computation
@ -11,8 +11,8 @@ clc
close all close all
%% Display stuff %% Display stuff
disp('beefblup v. 0.0.0.1') disp('beefblup v. 0.1')
disp('(C) 2018 Thomas A. Christensen II') disp('(C) 2020 Thomas A. Christensen II')
disp('https://github.com/millironx/beefblup') disp('https://github.com/millironx/beefblup')
disp(' ') disp(' ')
@ -77,7 +77,7 @@ for i=1:numanimals
dammatch = ismember(damids, ids(i,:), 'rows'); dammatch = ismember(damids, ids(i,:), 'rows');
damindexes = find(dammatch == 1); damindexes = find(dammatch == 1);
dam(damindexes) = i; dam(damindexes) = i;
% Find all animals that this animal sired % Find all animals that this animal sired
sirematch = ismember(sireids, ids(i,:), 'rows'); sirematch = ismember(sireids, ids(i,:), 'rows');
sireindexes = find(sirematch == 1); sireindexes = find(sirematch == 1);
@ -91,7 +91,7 @@ colstodelete = 6;
% Coerce each group to string format % Coerce each group to string format
for i = 7:length(headers) for i = 7:length(headers)
data(:,i) = cellfun(@num2str, data(:,i), 'UniformOutput', false); data(:,i) = cellfun(@num2str, data(:,i), 'UniformOutput', false);
end end
% Find any columns that need to be deleted % Find any columns that need to be deleted
@ -100,7 +100,7 @@ for i = 7:length(headers)
colname = headers{i}; colname = headers{i};
disp(['Column "' colname '" does not have any unique animals and will be removed']) disp(['Column "' colname '" does not have any unique animals and will be removed'])
disp('from this analysis'); disp('from this analysis');
colstodelete = [colstodelete i]; colstodelete = [colstodelete i];
end end
end end
@ -167,19 +167,19 @@ adjustedtraits = cell(1, sum(numgroups)-length(numgroups));
for i = 1:length(normal) for i = 1:length(normal)
% Find the traits that are present in this trait % Find the traits that are present in this trait
traits = uniquecell(data(:,i+5)); traits = uniquecell(data(:,i+5));
% Remove the "normal" version from the analysis % Remove the "normal" version from the analysis
normalindex = find(strcmp(traits, normal{i})); normalindex = find(strcmp(traits, normal{i}));
traits(normalindex) = []; traits(normalindex) = [];
% Iterate inside of the group % Iterate inside of the group
for j = 1:length(traits) for j = 1:length(traits)
matchedindex = find(strcmp(data(:,i+5), traits{j})); matchedindex = find(strcmp(data(:,i+5), traits{j}));
X(matchedindex, I) = 1; X(matchedindex, I) = 1;
% Add this trait to the string % Add this trait to the string
adjustedtraits(I - 1) = traits(j); adjustedtraits(I - 1) = traits(j);
% Increment the big counter % Increment the big counter
I = I + 1; I = I + 1;
end end
@ -217,7 +217,7 @@ for i = 1:numanimals
A(j,i) = 0.5*A(j,sire(i)); A(j,i) = 0.5*A(j,sire(i));
A(i,j) = A(j,i); A(i,j) = A(j,i);
end end
A(i,i) = 1; A(i,i) = 1;
else else
for j = 1:(i-1) for j = 1:(i-1)
A(j,i) = 0; A(j,i) = 0;
@ -313,7 +313,7 @@ for i = 1:length(numgroups)
fprintf(fileID, '\t'); fprintf(fileID, '\t');
fprintf(fileID, num2str(reliability(I))); fprintf(fileID, num2str(reliability(I)));
fprintf(fileID, '\n'); fprintf(fileID, '\n');
I = I + 1; I = I + 1;
end end
fprintf(fileID, '\n'); fprintf(fileID, '\n');