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SeroHet.m
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SeroHet.m
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% Usage :
% SeroHet('path_matrix','path_seroprotein','path_groupID','outdir');
% SeroHet(___,Name,Value);
%
% Arguments:
% path_matrix - The path to .txt file containing the concentrations of each seroprotein
% path_seroprotein - The path to .txt file containing the names of the seroprotein
% path_groupID - The path to .txt file containing group IDs
% outdir - An output directory where generated figures will be saved
%
% Optional Fields:
% 'Statistics' - Whether to draw volcano plot
% 'on' | 'off'
% 'ROC' - Whether to draw ROC curves
% 'on' | 'off'
% 'Metadata' - Whether to analyze relationship between SeroHet signatures and metadata
% 'path_metadata'
%
%
function SeroHet(path_matrix,path_seroprotein,path_groupID,outdir,field1_name,field1_value)
% SeroHet software version 1.2
% Copyright (c) 2021 Hanjun Lee, Seo Yihl Kim, Dong Wook Kim,
% Young Soo Park, Jin-Hyeok Hwang, Sukki Cho, and Je-Yoel Cho.
%
% See the accompanying file LICENSE.txt for licensing details.
version = '1.2';
% Determine necessary paths
install_path = regexprep(which('SeroHet'),'SeroHet\.m$','');
bin_path = [install_path 'bin/'];
addpath(bin_path);
% Check input arguments
if nargin<3
disp('Usage: SeroHet(path_matrix,path_seroprotein,path_groupID,outdir)');
disp('User must specify a path to each input file and output directory');
return;
elseif nargin==3
disp('No output directory specified... using:');
outdir = [install_path 'figure/'];
disp(outdir);
statistics_value = 'off';
roc_value = 'off';
metadata_value = 'off';
if ~ischar(path_matrix)||~ischar(path_seroprotein)||~ischar(path_groupID)
error('Inputs must be character arrays');
end
elseif nargin==4
statistics_value = 'off';
roc_value = 'off';
metadata_value = 'off';
if ~ischar(path_matrix)||~ischar(path_seroprotein)||~ischar(path_groupID)||~ischar(outdir)
error('Inputs must be character arrays');
end
elseif nargin==5
disp('Usage: SeroHet(path_matrix,path_seroprotein,path_groupID,outdir)');
disp('Usage: SeroHet(___, Name, Value)');
disp('User must specify optional field name and value');
return;
elseif nargin==6
if ~strcmpi(field1_name, 'Statistics')&&~strcmpi(field1_name, 'Statistic')&&~strcmpi(field1_name, 'ROC')&&~strcmpi(field1_name, 'Metadata')
disp('Invalid optional field name');
return;
end
if ~strcmpi(field1_value, 'on')&&~strcmpi(field1_value, 'off')&&~strcmpi(field1_value, 'true')&&~strcmpi(field1_value, 'false')&&~strcmpi(field1_value, 'T')&&~strcmpi(field1_value, 'F')&&~strcmpi(field1_name, 'Metadata')
disp('Invalid optional field value');
return;
elseif strcmpi(field1_value, 'on')||strcmpi(field1_value, 'true')||strcmpi(field1_value, 'T')
if strcmpi(field1_name, 'Statistics')||strcmpi(field1_name, 'Statistic')
statistics_value = 'on';
roc_value = 'off';
metadata_value = 'off';
elseif strcmpi(field1_name, 'ROC')
roc_value = 'on';
statistics_value = 'off';
metadata_value = 'off';
end
elseif strcmpi(field1_value, 'off')||strcmpi(field1_value, 'false')||strcmpi(field1_value, 'F')
if strcmpi(field1_name, 'Statistics')||strcmpi(field1_name, 'Statistic')
statistics_value = 'off';
roc_value = 'off';
metadata_value = 'off';
elseif strcmpi(field1_name, 'ROC')
roc_value = 'off';
statistics_value = 'off';
metadata_value = 'off';
end
elseif strcmpi(field1_name, 'Metadata')
statistics_value = 'off';
roc_value = 'off';
metadata_value = 'on';
path_metadata = field1_value;
end
if ~ischar(path_matrix)||~ischar(path_seroprotein)||~ischar(path_groupID)||~ischar(outdir)||~ischar(field1_name)||~ischar(field1_value)
error('Inputs must be character arrays');
end
end
if ~strcmp(outdir(end),'/')
outdir = [outdir '/'];
end
% Get full paths for each input file
path_matrix = full_path(path_matrix, install_path);
path_seroprotein = full_path(path_seroprotein, install_path);
path_groupID = full_path(path_groupID, install_path);
% Read files
[matrix,seroprotein,groupID] = read_files(path_matrix,path_seroprotein,path_groupID);
spearman_matrix = matrix;
group = unique(groupID);
% Read classification
class = read_classification(install_path,version);
signature = unique(class(:,2));
signature = sort_signature(signature);
cmap = colormap([0.545098039215686,0.0235294117647059,0.0156862745098039;0.564705882352941,0.341176470588235,0.00392156862745098;0.478431372549020,0.498039215686275,0.0705882352941177;0.223529411764706,0.443137254901961,0.141176470588235;0.133333333333333,0.466666666666667,0.341176470588235;0.247058823529412,0.419607843137255,0.525490196078431;0.117647058823529,0.227450980392157,0.419607843137255;0.203921568627451,0.160784313725490,0.380392156862745;0.450980392156863,0.219607843137255,0.470588235294118;0.623529411764706,0.0509803921568627,0.376470588235294]);
cmap_class = cmap_seroprotein(cmap,signature,class);
num_signature = count_signature(signature,class);
% Filter only SeroHet proteins
[matrix,mismatch] = filter_proteins(matrix,seroprotein,class);
% Mean-centered normalization based on reference data
matrix = mean_centered(matrix,groupID);
roc_matrix = matrix;
spearman_matrix = mean_centered(spearman_matrix,groupID);
% Retrieve the logistic of z-score and set non-available values as zero
matrix = logistic_transformation(matrix,mismatch);
% Calculate group-wise SeroHet signature scores
[score,errhigh,errlow] = group_wise(matrix,groupID,group);
% Draw bar plots
for count = 1:1:size(group, 1)
figure('Visible','off');
barplot = bar(1:size(matrix,1),score(count,:));
hold on
er = errorbar(1:size(matrix,1),score(count,:),errlow(count,:),errhigh(count,:));
er.Color = [0 0 0];
er.LineStyle = 'none';
barplot.BaseValue = 0.5;
barplot.FaceColor = 'flat';
for signaturecount = 1:1:size(signature,1)
barplot.CData(strcmp(signature(signaturecount,1),class(:,2)),:) = repmat(cmap(signaturecount,:),sum(strcmp(signature(signaturecount,1),class(:,2))),1);
end
ylabel('logistic(z)');
xlabel('SeroHet signatures');
ylim([0 1]);
xlim([1-0.75 size(matrix,1)+0.75]);
set(gca,'LineWidth',3,'XTick',[]);
print_to_file([outdir char(group(count,1)) '.signatures.pdf'],1200);
hold off
end
% Classify novel seroproteins into SeroHet signatures
hmap = spearman_heatmap(spearman_matrix);
novel_seroprotein = [];
line_width = 1.5;
for count = 1:1:size(spearman_matrix,1)
if sum(strcmp(seroprotein(count,1), class(:,1))) == 0
spearman_vector = [];
signature_vector = [];
for spearmancount = 1:1:size(spearman_matrix,1)
if sum(strcmp(seroprotein(spearmancount,1), class(:,1))) > 0
spearman_vector = [spearman_vector; hmap(count, spearmancount)];
signature_vector = [signature_vector; class(strcmp(seroprotein(spearmancount,1), class(:,1)),2)];
end
end
[~,idx] = max(spearman_vector);
novel_seroprotein = [novel_seroprotein; [seroprotein(count,1), signature_vector(idx,1)]];
end
end
if size(novel_seroprotein,1) > 0
writematrix(novel_seroprotein, [outdir 'novel.seroprotein.signature.txt'], 'Delimiter', '\t', 'FileType', 'text');
disp(['Outputting figure to ' outdir 'novel.seroprotein.signature.txt']);
end
% Statistical anaylsis
alpha = 0.05/size(signature,1);
if strcmp(statistics_value,'on')
combi = nchoosek(group,2);
for count = 1:size(combi,1)
log2FC = zeros(size(class,1),1);
welch_p = ones(size(class,1),1);
for countclass = 1:1:size(class,1)
log2FC(countclass,1) = log(mean(matrix(countclass,strcmp(groupID,combi(count,2))).'))/log(2)-log(mean(matrix(countclass,strcmp(groupID,combi(count,1))).'))/log(2);
[~,welch_p(countclass,1)] = ttest2(matrix(countclass,strcmp(groupID,combi(count,2))).',matrix(countclass,strcmp(groupID,combi(count,1))).','VarType','unequal');
end
scatter_size = 25;
figure('Visible','off');
scatter(log2FC,-log10(welch_p),scatter_size,cmap_class,'filled');
hold on
box on
ylabel('-log10 p-value');
xlabel('log2 fold change');
if max(-log10(welch_p)) < 10
ymax = 10;
else
ymax = 20;
end
ylim([0 ymax]);
xlim([-1 1]);
line([-1 1],[-log10(alpha) -log10(alpha)],'Color',[0.5 0.5 0.5],'LineWidth',line_width);
set(gca,'LineWidth',3,'XTick',-1:1:1,'YTick',0:(ymax/2):ymax);
print_to_file([outdir char(combi(count,1)) '.vs.' char(combi(count,2)) '.volcano.pdf'],1200);
hold off
end
end
% ROC curve
if strcmp(roc_value,'on')
fold = 10;
maxiter = 1000;
if sum(strcmp(group, "Healthy Control")) == 0
error('Healthy Control is either mislabelled or absent');
end
for signaturecount = 1:1:size(signature)
alpha = 0.05/sum(strcmp(class(:,2),signature(signaturecount,1)));
for groupcount = 1:1:size(group)
if ~strcmp(group(groupcount,1),"Healthy Control")
matrix_include = (roc_matrix(strcmp(class(:,2),signature(signaturecount,1)),strcmp(group(groupcount,1),groupID)|strcmp("Healthy Control",groupID))).';
group_include = groupID(strcmp(group(groupcount,1),groupID)|strcmp("Healthy Control",groupID),1);
matrix_exclude = (roc_matrix(strcmp(class(:,2),signature(signaturecount,1)),~strcmp(group(groupcount,1),groupID)&~strcmp("Healthy Control",groupID))).';
group_exclude = groupID(~strcmp(group(groupcount,1),groupID)&~strcmp("Healthy Control",groupID),1);
fold_include = fold*size(matrix_include,1)/(size(matrix_include,1)+size(matrix_exclude,1));
roc_vector = [];
for iter = 1:1:maxiter
trainingidx = [randperm(sum(strcmp(groupID, "Healthy Control")),round(sum(strcmp(groupID, "Healthy Control"))*fold_include/(fold_include+1))),(randperm(sum(strcmp(groupID, group(groupcount,1))),round(sum(strcmp(groupID, group(groupcount,1)))*fold_include/(fold_include+1)))+sum(strcmp(groupID, "Healthy Control"))-1)];
validationidx = ~ismember(1:sum(strcmp(groupID, "Healthy Control")|strcmp(groupID, group(groupcount,1))),trainingidx);
trainingmatrix = [matrix_include(trainingidx,:);matrix_exclude];
traininggroup = [group_include(trainingidx,1);group_exclude];
validationmatrix = matrix_include(validationidx,:);
validationgroup = group_include(validationidx,1);
mdl = fitglm(trainingmatrix, ~strcmp(traininggroup, "Healthy Control"), 'Distribution', 'binomial', 'Link', 'logit');
prediction = [predict(mdl, validationmatrix),~strcmp(validationgroup, "Healthy Control")];
roc_vector = [roc_vector; prediction];
end
writematrix(roc_vector, [outdir 'Healthy Control vs ' char(group(groupcount,1)) '.' char(signature(signaturecount,1)) '.ROC.txt'], 'Delimiter', '\t', 'FileType', 'text');
disp(['Outputting datafile to ' outdir 'Healthy Control vs ' char(group(groupcount,1)) '.' char(signature(signaturecount,1)) '.ROC.txt']);
end
end
mdl = fitglm([matrix_include;matrix_exclude], ~strcmp([group_include;group_exclude], "Healthy Control"), 'Distribution', 'binomial', 'Link', 'logit');
p_value = mdl.Coefficients.pValue;
p_value = p_value(2:end,1);
log2cDOR = mdl.Coefficients.Estimate/log(2);
log2cDOR = log2cDOR(2:end,1);
scatter_size = 25;
figure('Visible','off');
scatter(log2cDOR,-log10(p_value),scatter_size,cmap(signaturecount,:),'filled');
hold on
box on
ylabel('-log10 p-value');
xlabel('log2 conditional DOR');
xmax = round(max(abs(log2cDOR)) * 1.5)+1;
ymax = round(max(-log10(p_value)) * 1.5)+1;
ylim([0 ymax]);
xlim([-xmax xmax]);
line([-xmax xmax],[-log10(alpha) -log10(alpha)],'Color',[0.5 0.5 0.5],'LineWidth',line_width);
set(gca,'LineWidth',3,'XTick',-xmax:xmax:xmax,'YTick',0:(ymax/2):ymax);
print_to_file([outdir 'Healthy Control vs Cancer.' char(signature(signaturecount,1)) '.volcano.pdf'],1200);
hold off
end
end
% Metdata analysis
if strcmp(metadata_value,'on')
path_metadata = full_path(path_metadata, install_path);
metadata = read_metadata(path_metadata);
if size(metadata,1) ~= size(matrix.',1)
error('Number of rows in the metadata does not match sample number');
else
metadata_group1 = cell(1,size(metadata,2));
metadata_group2 = cell(1,size(metadata,2));
metadata_log2FC = [];
metadata_welch_p = [];
for count = 1:1:size(metadata,2)
metadata_group = unique(metadata(:,count));
metadata_char_determinant = char(metadata_group(2,1));
if strcmpi(metadata_char_determinant,'Lean')||strcmpi(metadata_char_determinant,'Female')||strcmpi(metadata_char_determinant(1),'N')
metadata_group = metadata_group(end:-1:1,1);
end
metadata_group1(1,count) = {char(metadata_group(1,1))};
metadata_group2(1,count) = {char(metadata_group(2,1))};
log2FC = zeros(1,size(signature,1));
welch_p = zeros(1,size(signature,1));
for signaturecount = 1:1:size(signature,1)
log2FC(1,signaturecount) = log(mean(mean(matrix(strcmp(class(:,2),signature(signaturecount,1)),strcmp(metadata(:,count),metadata_group(2,1))).').'))/log(2)-log(mean(mean(matrix(strcmp(class(:,2),signature(signaturecount,1)),strcmp(metadata(:,count),metadata_group(1,1))).').'))/log(2);
[~,welch_p(1,signaturecount)] = ttest2(mean(matrix(strcmp(class(:,2),signature(signaturecount,1)),strcmp(metadata(:,count),metadata_group(2,1))).'),mean(matrix(strcmp(class(:,2),signature(signaturecount,1)),strcmp(metadata(:,count),metadata_group(1,1))).'),'VarType','unequal');
end
metadata_log2FC = [metadata_log2FC; log2FC];
metadata_welch_p = [metadata_welch_p; welch_p];
end
scatter_size = 75;
figure('Visible','off');
for count = 1:1:size(metadata,2)
if count == 1
scatter(metadata_log2FC(count,:).',repmat(1+size(metadata,2)-count,size(signature,1),1),scatter_size,cmap,'filled');
line([-1 1],[1+size(metadata,2)-count 1+size(metadata,2)-count],'Color',[0.5 0.5 0.5],'LineWidth',line_width);
hold on
else
scatter(metadata_log2FC(count,:).',repmat(1+size(metadata,2)-count,size(signature,1),1),scatter_size,cmap,'filled');
line([-1 1],[1+size(metadata,2)-count 1+size(metadata,2)-count],'Color',[0.5 0.5 0.5],'LineWidth',line_width);
end
end
box on
ymax = size(metadata,2)+1;
xlim([-1 1]);
xlabel('log2 fold change');
yyaxis left
ylim([0 ymax]);
yticks(1:1:size(metadata,2));
yticklabels(metadata_group1(1,end:-1:1));
yyaxis right
ylim([0 ymax]);
yticks(1:1:size(metadata,2));
yticklabels(metadata_group2(1,end:-1:1));
set(gca,'LineWidth',3,'XTick',-1:1:1,'ycolor','w');
print_to_file([outdir 'Metadata.log2FC.pdf'],1200);
hold off
description = ["Column1","Column2"];
description = [description,signature.'];
below_description = [string(metadata_group1).',string(metadata_group2).'];
for signaturecount = 1:1:size(signature,1)
below_description = [below_description,num2str(-log10(metadata_welch_p(:,signaturecount)))];
end
writematrix([description;below_description],[outdir 'Metadata.-log10P.txt'],'FileType','text','Delimiter','\t');
disp(['Outputting figure to ' outdir 'Metadata.-log10P.txt']);
end
end