PlotSummary: Plot the IKAP result

In NHLBI-BCB/IKAP: IKAP: Identifying K mAjor cell Population group in single cell analysis

Description

This function plots a heat map indicating the increase of gap statistics as the number of cluster (k) increases by varying the number of top principal components (nPC) used. The best set and alternative sets of cell groups are indicated by 'B' and 'X' respectively. The best set is determined based on classification error summarized in DecisionTree().

Usage

PlotSummary(gap.gain, summary.rpart, markers.all, out.dir)

Arguments

gap.gain	a numeric matrix for the increase of gap statistic from k-1 to k. Columns are the number of clusters (k = 2 to k.max) and rows are the number of top principal components (nPC). For example, the first column is the increase of gap statistic from k=1 to k=2 for each nPC (row).
summary.rpart	a numberic matrix with overall classification error summarized for each n split (column) and each candidate set (row). This is usually the output return from DecisionTree().
markers.all	a list of marker gene tables for candidate sets. This is usually the list returned from ComputeMarkers().
out.dir	the path for output directory

Examples

PlotSummary(gap.gain, summary.rpart, markers.all, out.dir)

NHLBI-BCB/IKAP documentation built on March 21, 2020, 8:08 p.m.