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loadGDSC.m
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loadGDSC.m
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function ds = loadGDSC()
% Loading and preprocessing GDSC data
% Loading from the Pan-cancer data set
disp('Processing CFE table...');
cfe = readtable('data/PANCAN_simple_MOBEM.rdata.txt', 'Delimiter', '\t');
gdsc_cells = readtable('data/GDSC_Cells_MappedTissue.csv');
cfe_mat = table2array(cfe(2:end, 2:end));
cfe_events = cfe.Var1(2:end);
cfe_cellids = cfe(1, 2:end);
cfe_cellids = table2array(cfe_cellids);
cfe_cellnameidx = arrayfun(@(x) find(gdsc_cells.CELL_ID==x), cfe_cellids);
cfe_cellnames = gdsc_cells.CELL_NAME(cfe_cellnameidx);
cfe_celltissues = gdsc_cells.MAPPEDTISS(cfe_cellnameidx);
cfe_oritissues = gdsc_cells.TISSUE2(cfe_cellnameidx);
mut_genes = {};
mut_idx = [];
cnvu_genes = {};
cnvu_idx = [];
cnvd_genes = {};
cnvd_idx = [];
meth_genes = {};
meth_idx = [];
for i=1:length(cfe_events)
if(strcmp(cfe_events{i}(end-3:end), '_mut'))
genename = cfe_events{i}(1:end-4);
mut_genes = [mut_genes; genename];
mut_idx = [mut_idx; i];
elseif(strcmp(cfe_events{i}(1:5), 'gain:'))
genenamesIdx = regexp(cfe_events{i}, '\(([^()]*)\)');
if(isempty(genenamesIdx))
continue;
end
genenames = cfe_events{i}(genenamesIdx + 1:end-1);
genenames = strtrim(strsplit(genenames, ','));
cnvu_genes = [cnvu_genes; genenames'];
cnvu_idx = [cnvu_idx; repmat(i, length(genenames), 1)];
elseif(strcmp(cfe_events{i}(1:5), 'loss:'))
genenamesIdx = regexp(cfe_events{i}, '\(([^()]*)\)');
if(isempty(genenamesIdx))
continue;
end
genenames = cfe_events{i}(genenamesIdx + 1:end-1);
genenames = strtrim(strsplit(genenames, ','));
cnvd_genes = [cnvd_genes; genenames'];
cnvd_idx = [cnvd_idx; repmat(i, length(genenames), 1)];
elseif(strcmp(cfe_events{i}(1:3), 'chr'))
genenamesIdx = regexp(cfe_events{i}, '\(([^()]*)\)');
if(isempty(genenamesIdx))
continue;
end
genenames = cfe_events{i}(genenamesIdx + 1:end-8);
genenames = strtrim(strsplit(genenames, ','));
meth_genes = [meth_genes; genenames'];
meth_idx = [meth_idx; repmat(i, length(genenames), 1)];
end
end
% Process MUT, CNV and MET matrices
mutmat = zeros(size(mut_genes, 1), length(cfe_cellids));
for i=1:size(mut_genes, 1)
mutmat(i, :) = cfe_mat(mut_idx(i), :);
end
cnv_genes = union(cnvu_genes, cnvd_genes);
cnvmat = zeros(size(cnv_genes, 1), length(cfe_cellids));
for i=1:size(cnv_genes, 1)
idxu = strcmp(cnvu_genes, cnv_genes{i});
idxd = strcmp(cnvd_genes, cnv_genes{i});
% Average out repeated gene data
if(sum(idxu)>0)
arru = double(mean(cfe_mat(cnvu_idx(idxu), :), 1)>0);
else
arru = zeros(1, length(cfe_cellids));
end
if(sum(idxd)>0)
arrd = double(mean(cfe_mat(cnvd_idx(idxd), :), 1)>0);
else
arrd = zeros(1, length(cfe_cellids));
end
cnvmat(i, :) = arru-arrd;
end
methmat = zeros(length(meth_genes), length(cfe_cellids));
for i=1:length(meth_genes)
idxu = strcmp(meth_genes, meth_genes{i});
% Max-out repeated gene data
if(sum(idxu)>1)
arru = max(cfe_mat(meth_idx(idxu), :));
else
arru = cfe_mat(meth_idx(idxu), :);
end
methmat(i, :) = arru;
end
% Consider only samples with minimum number of tissues
minsample = 10;
tt=tabulate(cfe_celltissues);
tisslow = tt(cell2mat(tt(:, 2))<minsample, 1);
idxlow = ismember(cfe_celltissues, tisslow);
% Delete tissues with low number of samples
cfe_cellnames(idxlow) = [];
cfe_celltissues(idxlow) = [];
cfe_oritissues(idxlow) = [];
mutmat(:, idxlow) = [];
cnvmat(:, idxlow) = [];
methmat(:, idxlow) = [];
% Read GEX data
disp('Reading gene expression data...');
genexpTab = readtable('data/Cell_line_RMA_proc_basalExp.txt', 'Delimiter', '\t');
genes_exp = genexpTab.GENE_SYMBOLS;
expmat = table2array(genexpTab(:, 3:end));
cellids = genexpTab.Properties.VariableNames(3:end);
expsids = cellfun(@(x) str2double(x(6:end)), cellids, 'UniformOutput', 0);
% Delete the sample ID's that cannot be converted to cell names
idxnanemp = cellfun(@(x) isempty(x)|isnan(x), expsids);
expmat(:, idxnanemp) = [];
expsids(idxnanemp) = [];
expsids = cell2mat(expsids);
% Map Cell IDs to standardized cell names
idxnav = ~ismember(expsids, gdsc_cells.CELL_ID);
expsids(idxnav) = [];
expmat(:, idxnav) = [];
idxcell = arrayfun(@(x) find(gdsc_cells.CELL_ID==x), expsids);
expcellnames = gdsc_cells.CELL_NAME(idxcell);
icl = intersect(cfe_cellnames, expcellnames);
idxc1 = ismember(cfe_cellnames, icl);
idxc2 = ismember(expcellnames, icl);
% Consider only cell lines in the intersection
mutmat(:, ~idxc1) = [];
cnvmat(:, ~idxc1) = [];
methmat(:, ~idxc1) = [];
cfe_cellnames(~idxc1) = [];
cfe_celltissues(~idxc1) = [];
cfe_oritissues(~idxc1) = [];
expmat(:, ~idxc2) = [];
expcellnames(~idxc2) = [];
% Rearrange sample labels according to the intersection
idxc1 = cellfun(@(x) find(strcmp(x, cfe_cellnames)), icl);
idxc2 = cellfun(@(x) find(strcmp(x, expcellnames)), icl);
mutmat = mutmat(:, idxc1);
cnvmat = cnvmat(:, idxc1);
methmat = methmat(:, idxc1);
cfe_cellnames = cfe_cellnames(idxc1);
cfe_celltissues = cfe_celltissues(idxc1);
cfe_oritissues = cfe_oritissues(idxc1);
expmat = expmat(:, idxc2);
% Save the data
ds.mutMat = mutmat;
ds.mutGenes = mut_genes;
ds.cnvMat = cnvmat;
ds.cnvGenes = cnv_genes;
ds.gexMat = expmat;
ds.gexGenes = genes_exp;
ds.cellNames = cfe_cellnames;
ds.cellTissues = cfe_celltissues;
ds.cellOriTissues = cfe_oritissues;
% Read drug response data
disp('Reading drug response data...');
drugIDmap = containers.Map('KeyType','int32', 'ValueType', 'char');
gdscdrugs = readtable('data/GDSC_DRUGS.csv');
for i=1:height(gdscdrugs)
drugIDmap(gdscdrugs.DRUG_ID(i)) = gdscdrugs.DRUG_NAME{i};
end
% drugIDmap(1060) = 'PD-0325901';
% drugIDmap(11) = 'Paclitaxel';
% drugIDmap(1) = 'Erlotinib';
% drugIDmap(119) = 'Lapatinib';
% drugIDmap(1013) = 'Nilotinib';
% drugIDmap(30) = 'Sorafenib';
% drugIDmap(6) = 'PHA-665752';
% drugIDmap(1026) = '17-AAG';
% drugIDmap(1054) = 'PD-0332991';
% drugIDmap(1047) = 'Nutlin-3';
% drugIDmap(35) = 'TAE684';
drugresponse = readtable('data/v17_fitted_dose_response.csv');
drugresponse = drugresponse(ismember(drugresponse.DRUG_ID, cell2mat(keys(drugIDmap))), :);
drugnames = values(drugIDmap, num2cell(drugresponse.DRUG_ID));
drugresponse.DRUG_NAME = upper(drugnames);
drugresponse.AA = 1 - drugresponse.AUC;
% Remove profiles for cell lines that cannot be matched with the cell
% line data
idxnav = ~ismember(drugresponse.COSMIC_ID, gdsc_cells.CELL_ID);
drugresponse(idxnav, :) = [];
% Translate CellLineName in Profile Table to standardized name
idxcells = arrayfun(@(x) find(gdsc_cells.CELL_ID==x), drugresponse.COSMIC_ID);
drugresponse.Cell_Name = gdsc_cells.CELL_NAME(idxcells);
% Remove profiles for cell lines without molecular data
idxnav = ~ismember(drugresponse.Cell_Name, ds.cellNames);
drugresponse(idxnav, :) = [];
idxcells = cell2mat(cellfun(@(x) find(strcmp(x, ds.cellNames)), drugresponse.Cell_Name, 'UniformOutput', 0));
alldrugs = unique(upper(drugresponse.DRUG_NAME));
IC50Mat = nan(length(alldrugs), length(ds.cellNames));
AAMat = nan(length(alldrugs), length(ds.cellNames));
for i=1:length(alldrugs)
drug = alldrugs{i};
ic50sel = drugresponse.LN_IC50(strcmpi(drugresponse.DRUG_NAME, drug));
aasel = drugresponse.AA(strcmpi(drugresponse.DRUG_NAME, drug));
idxcellsel = idxcells(strcmpi(drugresponse.DRUG_NAME, drug));
IC50Mat(i, idxcellsel) = ic50sel';
AAMat(i, idxcellsel) = aasel';
end
ds.allDrugs = alldrugs;
ds.IC50Mat = IC50Mat;
ds.AAMat = AAMat;
end