Preprocessing

GPRparser(model, getCNFSets)[source]

Maps the GPR rules of the model to a specified format that is used by the model extraction methods

USAGE

parsedGPR = GPRparser (model)

INPUT

model – cobra model structure

OPTIONAL INPUT

getCNFSets – whether to get the CNF sets (true) or DNF sets (false). DNF sets represent functional enzyme complexes, while CNF sets represent the possible subunits of a complex. (default: false , i.e. DNF sets)

OUTPUT

parsedGPR – cell matrix containing parsed GPR rule

AUTHORS: Thomas Pfau & Anne Richelle, May 2017

findUsedGenesLevels(model, exprData, printLevel)[source]

Returns vectors of gene identifiers and corresponding gene expression levels for each gene present in the model (‘model.genes’).

USAGE

  • [gene_id, gene_expr] = findUsedGenesLevels (model, exprData)

  • [gene_id, gene_expr, gene_sig] = findUsedGenesLevels (model, exprData)

INPUTS

  • model – input model (COBRA model structure)

  • exprData – mRNA expression data structure .gene cell array containing GeneIDs in the same

    format as model.genes

    .value Vector containing corresponding expression value (FPKM) .sig: [optional field] Vector containing significance values of

    expression corresponding to expression values in exprData.value (ex. p-values)

OPTIONAL INPUTS

printLevel – Printlevel for output (default 0);

OUTPUTS

  • gene_id – vector of gene identifiers present in the model that are associated with expression data

  • gene_expr – vector of expression values associated to each ‘gene_id’

OPTIONAL OUTPUTS:
gene_sig: vector of significance values associated to each

‘gene_id’

mapExpressionToReactions(model, expressionData, minSum)[source]

Determines the expression data associated to each reaction present in the model

USAGE

  • [expressionRxns parsedGPR, gene_used] = mapExpressionToReactions (model, expressionData)

  • [expressionRxns, parsedGPR, gene_used, signifRxns] = mapExpressionToReactions (model, expressionData, minSum)

INPUTS
  • model model strusture

    • expressionData mRNA expression data structure

.gene cell array containing GeneIDs in the same

format as model.genes

.value Vector containing corresponding expression

value (FPKM/RPKM)

.sig: [optional field] Vector containing significance values of

expression corresponding to expression values in expressionData.value (ex. p-values)

OPTIONAL INPUT

minSum – instead of using min and max, use min for AND and Sum for OR (default: false, i.e. use min)

OUTPUTS

  • expressionRxns – n x 1 non-negative value for reaction expression, corresponding to model.rxns. expressionRxns(j) is NaN when there is no expression data for the genes corresponding to reaction j.

  • parsedGPR – cell matrix containing parsed GPR rule

  • gene_used – gene identifier, corresponding to model.rxns, from GPRs whose value (expression and/or significance) was chosen for that reaction

OPTIONAL OUTPUTS:

signifRxns: significance of reaction expression, corresponding to model.rxns.

selectGeneFromGPR(model, gene_names, gene_exp, parsedGPR, minSum, gene_sig)[source]

Map gene expression to reaction expression using the GPR rules. An AND will be replaced by MIN and an OR will be replaced by MAX.

USAGE

  • [expressionCol, gene_used] = selectGeneFromGPR (model, gene_names, gene_exp, parsedGPR, minSum)

  • [expressionCol, gene_used, signifCol] = selectGeneFromGPR (model, gene_names, gene_exp, parsedGPR, minSum, gene_sig)

INPUTS

  • model – COBRA model struct

  • gene_names – gene identifiers corresponding to gene_exp. Names must be in the same format as model.genes (column vector) (as returned by “findUsedGeneLevels.m”)

  • gene_exp – gene FPKM/expression values, corresponding to names (column vector) (as returned by “findUsedGeneLevels.m”)

  • parsedGPR – GPR matrix as returned by “GPRparser.m”

OPTIONAL INPUTS

  • minSum – instead of using min and max, use min for AND and Sum for OR

  • gene_sig – vector of significance values associated to each ‘gene_id’ (as returned by “findUsedGeneLevels.m”)

OUTPUTS

  • expressionCol – reaction expression, corresponding to model.rxns. No gene-expression data and orphan reactions will be given a value of NaN.

  • gene_used – gene identifier, corresponding to model.rxns, from GPRs whose value (expression and/or significance) was chosen for that reaction

OPTIONAL OUTPUTS:
signifCol: reaction significance, corresponding to model.rxns.

No gene-expression data and orphan reactions will be given a value of 0.