MGsforA: Marker genes detected by CAM for estimating A

In debCAM: Deconvolution by Convex Analysis of Mixtures

Description

This function returns marker genes detected by CAM for estimating A.

Usage

MGsforA(CAMResult = NULL, K = NULL, PrepResult = NULL, MGResult = NULL,
  corner.strategy = 2)

Arguments

CAMResult	Result from CAM.
K	The candidate subpopulation number.
PrepResult	An object of class "CAMPrepObj" from CAMPrep.
MGResult	An object of class "CAMMGObj" from CAMMGCluster.
corner.strategy	The method to detect corner clusters. 1: minimum sum of margin-of-errors; 2: minimum sum of reconstruction errors. The default is 2.

Details

This function needs to specify CAMResult and K, or PrepResult and MGResult. The returned marker genes are those used by CAM for estimating A. To obtain a more complete marker gene list, please refer to MGstatistic.

Value

A list of vectors, each of which contains marker genes for one subpopulation.

Examples

#obtain data and run CAM
data(ratMix3)
data <- ratMix3$X
rCAM <- CAM(data, K = 3, dim.rdc= 3, thres.low = 0.30, thres.high = 0.95)
#obtain marker genes detected by CAM for estimating A
MGlist <- MGsforA(rCAM, K = 3)

#obtain data and run CAM step by step
rPrep <- CAMPrep(data, dim.rdc= 3, thres.low = 0.30, thres.high = 0.95)
rMGC <- CAMMGCluster(3, rPrep)
#obtain marker genes detected by CAM for estimating A
MGlist <- MGsforA(PrepResult = rPrep, MGResult = rMGC)

debCAM documentation built on Nov. 8, 2020, 5:33 p.m.