selectKcatValue
From a kcatList with predicted or suggested kcat values, where each
reaction may have multiple entries, one kcat value is selected and
written to model.ec.kcat. Zero values are discarded from the start. By
default, the maximum value is chosen, but alternatives are available.
The kcatList structure is an output of e.g. readDLKcatOutput,
readGotEnzymesOutput, readManualKcatList.
Input:
model an ecModel in GECKO 3 format (with ecModel.ec structure)
kcatList structure array with separate entries for each kcat value
source e.g. 'DLKcat' or 'gotenzymes'
rxns reaction identifiers, matching model.rxns
genes gene identifiers, matching model.genes
substrate substrates, matching model.mets
kcat predicted kcat value in /sec
criteria which kcat value should be selected if multiple values are
provided. Options: 'max', 'min', 'median', 'mean'. (Opt,
default 'max')
overwrite whether existing kcat values should be overwritten.
Options: 'true', 'false', 'ifHigher'. The last option will
overwrite only if the new kcat value is higher. (Opt,
default 'true')
Output:
model ecModel with updated model.ec.kcat and model.ec.source
rxnIdx list of reaction indices (matching model.ec.rxns), to
indicate which kcat values have been changed.
Usage:
[model, rxnIdx] = selectKcatValue(model,kcatList,criteria,overwrite)0001 function [model, rxnIdx] = selectKcatValue(model,kcatList,criteria,overwrite) 0002 % selectKcatValue 0003 % From a kcatList with predicted or suggested kcat values, where each 0004 % reaction may have multiple entries, one kcat value is selected and 0005 % written to model.ec.kcat. Zero values are discarded from the start. By 0006 % default, the maximum value is chosen, but alternatives are available. 0007 % The kcatList structure is an output of e.g. readDLKcatOutput, 0008 % readGotEnzymesOutput, readManualKcatList. 0009 % 0010 % Input: 0011 % model an ecModel in GECKO 3 format (with ecModel.ec structure) 0012 % kcatList structure array with separate entries for each kcat value 0013 % source e.g. 'DLKcat' or 'gotenzymes' 0014 % rxns reaction identifiers, matching model.rxns 0015 % genes gene identifiers, matching model.genes 0016 % substrate substrates, matching model.mets 0017 % kcat predicted kcat value in /sec 0018 % criteria which kcat value should be selected if multiple values are 0019 % provided. Options: 'max', 'min', 'median', 'mean'. (Opt, 0020 % default 'max') 0021 % overwrite whether existing kcat values should be overwritten. 0022 % Options: 'true', 'false', 'ifHigher'. The last option will 0023 % overwrite only if the new kcat value is higher. (Opt, 0024 % default 'true') 0025 % 0026 % Output: 0027 % model ecModel with updated model.ec.kcat and model.ec.source 0028 % rxnIdx list of reaction indices (matching model.ec.rxns), to 0029 % indicate which kcat values have been changed. 0030 % Usage: 0031 % [model, rxnIdx] = selectKcatValue(model,kcatList,criteria,overwrite) 0032 0033 if nargin < 4 0034 overwrite = 'true'; 0035 elseif islogical(overwrite) 0036 if overwrite 0037 overwrite = 'true'; 0038 else 0039 overwrite = 'false'; 0040 end 0041 end 0042 if nargin < 3 0043 criteria = 'max'; 0044 end 0045 0046 % Remove zero kcat values. Only adjusting fields that are used later. 0047 removeZero = kcatList.kcats == 0; 0048 kcatList.kcats(removeZero) = []; 0049 kcatList.rxns(removeZero) = []; 0050 0051 % Map to model.ec.rxns 0052 [sanityCheck,idxInModel] = ismember(kcatList.rxns,model.ec.rxns); 0053 if ~all(sanityCheck) 0054 error('Not all reactions in kcatList are found in model.ec.rxns') 0055 end 0056 % Make vector with single kcat value per reaction 0057 idxInModelUnique = unique(idxInModel); 0058 selectedKcats = zeros(numel(idxInModelUnique),1); 0059 selectedSource = cell(numel(selectedKcats),1); 0060 if ~isfield(kcatList,'kcatSource') 0061 kcatList.kcatSource = cell(numel(kcatList.kcats),1); 0062 kcatList.kcatSource(:) = {kcatList.source}; 0063 end 0064 for i=1:numel(idxInModelUnique) 0065 ind = idxInModelUnique(i); 0066 idxMatch = find(idxInModel == ind); 0067 % Choose the maximum number 0068 switch criteria 0069 case 'max' 0070 [selectedKcats(i),j] = max(kcatList.kcats(idxMatch)); 0071 case 'min' 0072 [selectedKcats(i),j] = min(kcatList.kcats(idxMatch)); 0073 case 'median' 0074 [selectedKcats(i),j] = median(kcatList.kcats(idxMatch)); 0075 case 'mean' 0076 [selectedKcats(i),j] = mean(kcatList.kcats(idxMatch)); 0077 otherwise 0078 error('Invalid criteria specified') 0079 end 0080 selectedSource(i) = kcatList.kcatSource(idxMatch(j)); 0081 end 0082 0083 % Populate model.ec.kcat 0084 switch overwrite 0085 case 'true' 0086 model.ec.kcat(idxInModelUnique) = selectedKcats; 0087 model.ec.source(idxInModelUnique) = selectedSource; 0088 case 'false' 0089 emptyKcats = find(model.ec.kcat == 0); 0090 [idxInModelUnique,whickKcats] = intersect(idxInModelUnique,emptyKcats,'stable'); 0091 model.ec.kcat(idxInModelUnique) = selectedKcats(whickKcats); 0092 model.ec.source(idxInModelUnique) = selectedSource(whickKcats); 0093 0094 case 'ifHigher' 0095 higherKcats = model.ec.kcat(idxInModelUnique) < selectedKcats; 0096 selectedKcats(~higherKcats) = []; 0097 selectedSource(~higherKcats) = []; 0098 idxInModelUnique(~higherKcats) = []; 0099 model.ec.kcat(idxInModelUnique) = selectedKcats; 0100 model.ec.source(idxInModelUnique) = selectedSource; 0101 otherwise 0102 error('Invalid overwrite flag specified') 0103 end 0104 rxnIdx = idxInModelUnique; 0105 end