aucPlot: Sample, Train, and Predict logistic regression model using...

In jamez-eh/casc: Casc

Description

Sample, Train, and Predict logistic regression model using singleCellExperiment and glmnet

Usage

aucPlot(casc_list)

Arguments

casc_list

A casc_list object produced by casc

Value

A ggplot scatterplot with AUCs plotted for each cluster

Examples

library(SingleCellExperiment)

counts <- matrix(rnorm(40000, 10, 10), ncol=200, nrow=200)
sce <- SingleCellExperiment(assays = list(logcounts = counts))
colnames(sce) <- stringi::stri_rand_strings(200, 5)
rownames(sce) <- stringi::stri_rand_strings(200, 5)

cluster_1 <- rep(c(0, 1, 1, 1, 1, 0, 1, 1, 1, 1), 20)
cluster_2 <- rep(c(0, 1, 1, 0, 1, 0, 1, 1, 0, 1), 20)

casc_list <- casc(sce, list(cluster_1, cluster_2), marker_num=1500)
aucPlot(casc_list)

jamez-eh/casc documentation built on June 12, 2019, 1:43 a.m.