summary: Summarize FSCseq clustering results

In DavidKLim/FSCseq: Feature Selection and Clustering of RNA-seq Count Data

Description

Outputs relevant summary of FSCseq clustering results

Usage

summary(res, true_cls = NULL, true_disc = NULL)

Arguments

res	Output of FSCseq clustering analysis
true_cls	(optional) vector of true cluster labels to calculate Adjusted Rand Index (ARI)
true_disc	(optional) TRUE/FALSE vector of true cluster-discriminatory gene status to calculate True Positive Rate (TPR) and False Positive Rate (FPR)

Value

Summary of FSCseq clustering results: #clusters (K), clusters, ARI (if true_cls input), TPR and FPR (vs. true cluster-discriminatory genes if true_disc input)

Author(s)

David K. Lim, [e-mail]

References

https://github.com/DavidKLim/FSCseq

Examples

sim.dat = FSCseq::simulateData(B=1, g=10000, K=2, n=50, LFCg=1, pDEg=0.05, beta0=12, phi0=0.35, nsims=1, save_file=F)[[1]]
## Not run: FSCseq_results = FSCseq_workflow(cts=sim.dat$cts, K_search=c(2:3), lambda_search=c(1.0, 1.5), alpha_search=c(0.1, 0.2))
## Not run: summary(FSCseq_workflow$results)

DavidKLim/FSCseq documentation built on Dec. 12, 2021, 3:46 a.m.