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Edit icongems file #2361

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Update ICONGEMs.m
  • Loading branch information
ThummaratPaklao authored Nov 1, 2024
commit d9a3949569fa23623ac1f048ce3d742909a8b92a
10 changes: 7 additions & 3 deletions src/analysis/ICONGEMs/ICONGEMs.m
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
function [solICONGEMs, boundEf] = ICONGEMs(model, exp, genetxt, condition, threshold, alpha)
function [solICONGEMs, boundEf] = ICONGEMs(model, exp, genetxt, condition, threshold, alpha, numericFlag)
% Algorithm to Integrate a Gene Co-expression Network and Genome-scale Metabolic Model:
% This algorithm calculates the reaction flux distribution for each condition by applying
% quadratic programming.
@@ -14,6 +14,7 @@
% extract from gene expression profile file
% genetxt: list of gene names that extract from gene expression profile
% file
% numericFlag: 1 if using Human Recon (Default = 0).
%
% OPTIONAL INPUTS:
% threshold: The value of the correlation coefficient for constructing
@@ -47,6 +48,9 @@
if (nargin < 6 || isempty(alpha))
alpha = 0.99;
end
if (nargin < 7 || isempty(numericFlag))
numericFlag = 0;
end

% construct the template model

@@ -111,7 +115,7 @@

NameRxn={};
for i = 1:size(modelIrrev.genes)
[z1, NameRxn{i}] = findRxnsFromGenes(modelIrrev, modelIrrev.genes(i, 1), [], 1);
[z1, NameRxn{i}] = findRxnsFromGenes(modelIrrev, modelIrrev.genes(i, 1), numericFlag, 1);
end

% Find reactions that correspond to the gene
@@ -244,7 +248,7 @@
model2.A = sparse(Aeq);
model2.sense = [char('=' * ones(size(model2.A,1) - 1, 1)) ; char('>')];
model2.rhs = beq;
model2.modelsense = 'min';
model2.modelsense = 'max';
numrxn = [1:length(modelIrrev.rxns)];
j = 1;
for i = 1:length(model.rxns)