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Summarize multiple probe sets targeting one gene into one value for that gene. On most microarays there will be more than one probe set for a gene. However, in the underlying network the gene will only be present one time. Therefore, in order to calculate a Gene(Page)Rank weight for this gene, all expression measurements have to be summarized.
● Data Source:
CranContrib
● Keywords:
● Alias: summarizeProbes
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read.hprd
(Package: pathClass) :
Parse the HPRD flat file
This function parses the tab delimited flat file of protein-protein interactions coming from the HPRD (http://www.hprd.org/download).
● Data Source:
CranContrib
● Keywords:
● Alias: read.hprd
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predict.rrfe
(Package: pathClass) :
Predict Method for RRFE Fits
Obtains predictions from a fitted RRFE object.
● Data Source:
CranContrib
● Keywords:
● Alias: predict.rrfe
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predict.rfe
(Package: pathClass) :
Predict Method for RFE Fits
Obtains predictions from a fitted RFE object.
● Data Source:
CranContrib
● Keywords:
● Alias: predict.rfe
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Obtains predictions from a fitted networkBasedSVM object.
● Data Source:
CranContrib
● Keywords:
● Alias: predict.networkBasedSVM
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Obtains predictions from a fitted graphSVM object.
● Data Source:
CranContrib
● Keywords:
● Alias: predict.graphSVM
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plot.pathClassResult
(Package: pathClass) :
Prints the result of one or more cross-validation run(s)
This function creates boxplots of the distribution of AUC for each reapeat of the cross-validation. In a second plot the ROC curve of the AUCs is shown. If your result contains more than one cross-validation result these are plotted one after the other.
● Data Source:
CranContrib
● Keywords:
● Alias: plot.pathClassResult
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pathClass-package
(Package: pathClass) :
Classification with SMVs and prior knowledge
Classification with SMVs and prior knowledge
● Data Source:
CranContrib
● Keywords: package
● Alias: pathClass, pathClass-package
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matchMatrices
(Package: pathClass) :
Matches the expression data to the adjacency matrix using the provided mapping.
Usually the dimension of the graph and the expression data do not fit to each other. Additionally most often the graph comprises another type of knowledge, i.e. the expression matrix measures 10.000 genes represented as 15.000 probe sets and the graph provides information on 7.000 proteins. Thus, a node (protein) of the graph might match to two probe sets in the expression matrix (since both target the gene encoding the protein). Therefore, this method uses the relationship between probe sets and i.e. proteins which is encoded in the mapping to create a graph of probe sets rather then a graph of proteins.
● Data Source:
CranContrib
● Keywords:
● Alias: matchMatrices
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getGeneRanks
(Package: pathClass) :
Calculate GeneRanks as used by RRFE
Uses the GeneRank to calculate the ranks for genes. Afterwards the ranks are transformed as needed for the RRFE algorithm.
● Data Source:
CranContrib
● Keywords:
● Alias: getGeneRanks
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