patternMarkers-methods: compute pattern markers statistic

In CoGAPS/CoGAPS: Coordinated Gene Activity in Pattern Sets

compute pattern markers statistic

Description

estimate the most associated pattern for each feature

Usage

patternMarkers(object, threshold = "all", lp = NULL, axis = 1)

## S4 method for signature 'CogapsResult'
patternMarkers(object, threshold = "all", lp = NULL, axis = 1)

Arguments

object	an object of type CogapsResult
threshold	the type of threshold to be used. The default "all" will distribute features into patterns with the highest ranking as ranked by the increasing Euclidian distance between feature loadings and lp. The alternative "cut" will only keep the features that are ranked higher than the first feature having greater intra-pattern compared to inter-pattern rank. This is useful to limit the number of markers ranked similarly everywhere. Features may be present in multiple patterns for "cut".
lp	list of vectors of weights for each pattern to be used for finding markers. If NULL, list of synthetic one-hot markers for each pattern will be generated and matched against.
axis	controls the matrix to use for ranking. 1 for featureLoadings, 2 for sampleFactors.

Value

List of: list of marker features for each pattern (best rank first), a matrix of ranks of each feature in each pattern, a matrix of scores for each feature in each pattern.

List of: list of marker features for each pattern (best rank first), and a matrix of ranks of each feature in each pattern.

Examples

data(GIST)
pm <- patternMarkers(GIST.result)

CoGAPS/CoGAPS documentation built on June 23, 2024, 5:19 p.m.