CogapsParams-class {CoGAPS} | R Documentation

## CogapsParams

### Description

Encapsulates all parameters for the CoGAPS algorithm

### Slots

`nPatterns`

  number of patterns CoGAPS will learn

`nIterations`

  number of iterations for each phase of the algorithm

`alphaA`

  sparsity parameter for feature matrix

`alphaP`

  sparsity parameter for sample matrix

`maxGibbsMassA`

  atomic mass restriction for feature matrix

`maxGibbsMassP`

  atomic mass restriction for sample matrix

`seed`

  random number generator seed

`sparseOptimization`

  speeds up performance with sparse data (roughly >80 default uncertainty

`distributed`

  either "genome-wide" or "single-cell" indicating which distributed algorithm should be used

`nSets`

  [distributed parameter] number of sets to break data into

`cut`

  [distributed parameter] number of branches at which to cut dendrogram used in pattern matching

`minNS`

  [distributed parameter] minimum of individual set contributions a cluster must contain

`maxNS`

  [distributed parameter] maximum of individual set contributions a cluster can contain

`explicitSets`

  [distributed parameter] specify subsets by index or name

`samplingAnnotation`

  [distributed parameter] specify categories along the rows (cols) to use for weighted sampling

`samplingWeight`

  [distributed parameter] weights associated with samplingAnnotation

`subsetIndices`

  set of indices to use from the data

`subsetDim`

  which dimension (1=rows, 2=cols) to subset

`geneNames`

  vector of names of genes in data

`sampleNames`

  vector of names of samples in data

`fixedPatterns`

  fix either 'A' or 'P' matrix to these values, in the context of distributed CoGAPS (GWCoGAPS/scCoGAPS), the first phase is skipped and fixedPatterns is used for all sets - allowing manual pattern matching, as well as fixed runs of standard CoGAPS

`whichMatrixFixed`

  either 'A' or 'P', indicating which matrix is fixed

`takePumpSamples`

  whether or not to take PUMP samples

[Package CoGAPS version 3.10.0 Index]