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A B C D G H I K L M N P R S T misc
| activeMod | Functional classification of gene groups |
| activeModScoreHTML | Save HTML file with global gene scores from functional gene groups |
| activeNet | Functional classification of gene networks |
| activeNetScoreHTML | Save HTML file with scores and p-values from functional gene networks |
| addGeneGrps | Function to load gene groups into maigesPreRaw object |
| addPaths | Function to load gene pathways into maigesPreRaw object |
| as | Coerce a maiges object to classes defined by packages limma and marray |
| as-method | Coerce a maiges object to classes defined by packages limma and marray |
| bootstrapCor | Calculate bootstrap p-values for correlation measures |
| bootstrapMI | Calculate bootstrap p-values for mutual information (MI) measures |
| bootstrapT | Calculate bootstrap p-values for t statistics |
| boxplot | Method boxplot for objects defined in this package |
| boxplot.maiges | Method boxplot for objects defined in this package |
| boxplot.maigesANOVA | Method boxplot for objects defined in this package |
| boxplot.maigesDEcluster | Method boxplot for objects defined in this package |
| boxplot.maigesRaw | Method boxplot for objects defined in this package |
| calcA | Method calcA to calculate A values |
| calcA.default | Method calcA to calculate A values |
| calcA.maigesRaw | Method calcA to calculate A values |
| calcW | Method calcW to calculate W values |
| calcW.default | Method calcW to calculate W values |
| calcW.maigesRaw | Method calcW to calculate W values |
| classifyKNN | Function to do discrimination analysis |
| classifyKNNsc | Function to do discrimination analysis, by the search and choose method |
| classifyLDA | Function to do discrimination analysis |
| classifyLDAsc | Function to do discrimination analysis, by the search and choose method |
| classifySVM | Function to do discrimination analysis |
| classifySVMsc | Function to do discrimination analysis, by the search and choose method |
| coerce-method | Coerce a maiges object to classes defined by packages limma and marray |
| compCorr | Compute correlation differences and their p-values |
| contrastsFitM | Compute Contrasts from Linear Model Fit |
| createMaigesRaw | Function to create objects of class maigesRaw |
| createTDMS | Create a tab delimited file for TIGR MeV |
| deGenes2by2BootT | Function to do differential expression analysis, comparing only two |
| deGenes2by2Ttest | Function to do differential expression analysis, comparing only two |
| deGenes2by2Wilcox | Function to do differential expression analysis, comparing only two |
| deGenesANOVA | Function to do differential expression analysis, using ANOVA models |
| designANOVA | Function to construct design an contrasts matrices for ANOVA models |
| dim.maiges | Retrieve the dimension of microarray objects |
| dim.maigesANOVA | Retrieve the dimension of microarray objects |
| dim.maigesPreRaw | Retrieve the dimension of microarray objects |
| dim.maigesRaw | Retrieve the dimension of microarray objects |
| gastro | Gastro-esophagic dataset |
| gastro.norm | Gastro-esophagic dataset |
| gastro.raw | Gastro-esophagic dataset |
| gastro.raw2 | Gastro-esophagic dataset |
| gastro.summ | Gastro-esophagic dataset |
| getLabels | Method getLabels to pick gene and sample labels |
| getLabels.default | Method getLabels to pick gene and sample labels |
| getLabels.maigesDE | Method getLabels to pick gene and sample labels |
| getLabels.maigesDEcluster | Method getLabels to pick gene and sample labels |
| getLabels.MAList | Method getLabels to pick gene and sample labels |
| getLabels.marrayNorm | Method getLabels to pick gene and sample labels |
| getLabels.marrayRaw | Method getLabels to pick gene and sample labels |
| getLabels.RGList | Method getLabels to pick gene and sample labels |
| heatmapsM | Function to plot heatmaps separating groups generated by SOM or k-means |
| hierM | Function to do hierarchical cluster analysis |
| hierMde | Function to do hierarchical cluster analysis |
| image | Method image for objects defined in this package |
| image.maiges | Method image for objects defined in this package |
| image.maigesActMod | Method image for objects defined in this package |
| image.maigesActNet | Method image for objects defined in this package |
| image.maigesANOVA | Method image for objects defined in this package |
| image.maigesRaw | Method image for objects defined in this package |
| image.maigesRelNetB | Method image for objects defined in this package |
| image.maigesRelNetM | Method image for objects defined in this package |
| kmeansM | Function to do k-means cluster analysis |
| kmeansMde | Function to do k-means cluster analysis |
| loadData | Load cDNA microarray data tables |
| maiges | maiges class, store normalised microarray datasets |
| maiges-class | maiges class, store normalised microarray datasets |
| maigesActMod | maigesActMod class, store results of functional classification of gene |
| maigesActMod-class | maigesActMod class, store results of functional classification of gene |
| maigesActNet | maigesActNet class, store results of functional classification of gene |
| maigesActNet-class | maigesActNet class, store results of functional classification of gene |
| maigesANOVA | maigesANOVA class, extend maiges class to fit ANOVA models |
| maigesANOVA-class | maigesANOVA class, extend maiges class to fit ANOVA models |
| maigesClass | maigesClass class, store results of discrimination (or classification) |
| maigesClass-class | maigesClass class, store results of discrimination (or classification) |
| maigesDE | maigesDE class, store results of differential gene expression analysis |
| maigesDE-class | maigesDE class, store results of differential gene expression analysis |
| maigesDEcluster | maigesDEcluster class, store results of differential gene expression |
| maigesDEcluster-class | maigesDEcluster class, store results of differential gene expression |
| maigesPreRaw | maigesPreRaw class, store pre raw microarray datasets |
| maigesPreRaw-class | maigesPreRaw class, store pre raw microarray datasets |
| maigesRaw | maigesRaw class, store raw microarray datasets |
| maigesRaw-class | maigesRaw class, store raw microarray datasets |
| maigesRelNetB | maigesRelNetB class, store results of relevance network analysis |
| maigesRelNetB-class | maigesRelNetB class, store results of relevance network analysis |
| maigesRelNetM | maigesRelNetM class, store results of relevance network analysis |
| maigesRelNetM-class | maigesRelNetM class, store results of relevance network analysis |
| MI | Calculate Mutual Information |
| normLoc | Normalise a cDNA Microarray Object |
| normOLIN | Normalise a cDNA Microarray Object |
| normRepLoess | Bootstrap of LOWESS normalisation |
| normScaleLimma | Scale adjust a cDNA Microarray Object |
| normScaleMarray | Scale adjust a cDNA Microarray Object |
| plot | Method plot for objects defined in this package |
| plot.maiges | Method plot for objects defined in this package |
| plot.maigesActMod | Method plot for objects defined in this package |
| plot.maigesActNet | Method plot for objects defined in this package |
| plot.maigesANOVA | Method plot for objects defined in this package |
| plot.maigesClass | Method plot for objects defined in this package |
| plot.maigesDE | Method plot for objects defined in this package |
| plot.maigesDEcluster | Method plot for objects defined in this package |
| plot.maigesRaw | Method plot for objects defined in this package |
| plot.maigesRelNetB | Method plot for objects defined in this package |
| plot.maigesRelNetM | Method plot for objects defined in this package |
| plotGenePair | Scatter plots for pair of genes |
| Method to print a nice visualisation of the objects defined in this | |
| print.maiges | Method to print a nice visualisation of the objects defined in this |
| print.maigesActMod | Method to print a nice visualisation of the objects defined in this |
| print.maigesActNet | Method to print a nice visualisation of the objects defined in this |
| print.maigesANOVA | Method to print a nice visualisation of the objects defined in this |
| print.maigesClass | Method to print a nice visualisation of the objects defined in this |
| print.maigesDE | Method to print a nice visualisation of the objects defined in this |
| print.maigesDEcluster | Method to print a nice visualisation of the objects defined in this |
| print.maigesPreRaw | Method to print a nice visualisation of the objects defined in this |
| print.maigesRaw | Method to print a nice visualisation of the objects defined in this |
| print.maigesRelNetB | Method to print a nice visualisation of the objects defined in this |
| print.maigesRelNetM | Method to print a nice visualisation of the objects defined in this |
| relNet2TGF | Transform Relevance Network analysis in TGF output |
| relNet2TGF.maigesRelNetB | Transform Relevance Network analysis in TGF output |
| relNet2TGF.maigesRelNetM | Transform Relevance Network analysis in TGF output |
| relNetworkB | Relevance Network analysis |
| relNetworkM | Relevance Network analysis |
| robustCorr | Calculate a robust correlation value |
| selSpots | Select spots to use in normalisation |
| show | Show a nice visualisation of the objects defined in this package |
| show-method | Show a nice visualisation of the objects defined in this package |
| somM | Function to do SOM cluster analysis |
| somMde | Function to do SOM cluster analysis |
| summarizeReplicates | Summarise microarray objects |
| summary | Method summary for the object from this package |
| summary.maiges | Method summary for the object from this package |
| summary.maigesActMod | Method summary for the object from this package |
| summary.maigesActNet | Method summary for the object from this package |
| summary.maigesANOVA | Method summary for the object from this package |
| summary.maigesClass | Method summary for the object from this package |
| summary.maigesDE | Method summary for the object from this package |
| summary.maigesDEcluster | Method summary for the object from this package |
| summary.maigesPreRaw | Method summary for the object from this package |
| summary.maigesRaw | Method summary for the object from this package |
| summary.maigesRelNetB | Method summary for the object from this package |
| summary.maigesRelNetM | Method summary for the object from this package |
| tableClass | Save HTML or CSV tables of good classifiers (cliques) |
| tablesDE | Save HTML or CSV tables of differentially expressed genes |
| [ | Sub-setting methods for maiges objects |
| [-method | Sub-setting methods for maiges objects |