R: A Correlation Based Multiview Self Organizing Maps Clustering For IMC Datasets

# A Correlation Based Multiview Self Organizing Maps Clustering For IMC Datasets

## Documentation for package ‘FuseSOM’ version 1.15.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

.arsinhNnorm | Function to do arsinh normalization
.computeElbow | A function to compute the elbow point given a set of points
.minmaxNorm | Function to do min max normalization
.percentileNorm | Function to do percentile normalizaton
.runDiscriminant | Discriminant cluster estimator
.uniformData | Creates uniformly distributed data of same dimensionality as input data this function was obtained from the Stab package
clusterPrototypes | Cluster prototypes
computeGridSize | Estimate the optimal grid size
diabetesData | IMC Breast Cancer Data Data from A spatial atlas of breast cancer progression using MIBI-TOF and tissue transcriptomics
estimateNumCluster | Estimate number of clusters
FuseSOM | FuseSOM
generatePrototypes | Generate a Self Organizing Map
markerHeatmap | Generate expression heatmap
normaliseData | Normalise Marker Intensities
normalizeData | Normalize Marker Intensities
optiPlot | Generate elbow plots
risom_dat | IMC Breast Cancer Data Data from A spatial atlas of breast cancer progression using MIBI-TOF and tissue transcriptomics
runFuseSOM | A wrapper function to run the FuseSOM algorithm
somInitPca.default | these functions were obtained from https://rdrr.io/rforge/yasomi/ with some major modifications