find_optimal_stability {scGPS} | R Documentation

## Find the optimal cluster

### Description

from calculated stability based on Rand indexes for consecutive clustering run, find the resolution (window), where the stability is the highest

### Usage

    find_optimal_stability(list_clusters, run_RandIdx, bagging = FALSE,
      windows = seq(from = 0.025, to = 1, by = 0.025))

### Arguments

`list_clusters` | is a `list` object containing 40 clustering results
`run_RandIdx` | is a `data frame` object from iterative clustering runs
`bagging` | is a logical that is true if bagging is to be performed, changes return
`windows` | a numeric vector specifying the ranges of each window.

### Value

bagging == FALSE => a `list` with optimal stability, cluster count and summary stats bagging == TRUE => a `list` with high res cluster count, optimal cluster count and keystats

### Author(s)

Quan Nguyen, 2017-11-25

### Examples

    day5 <- day_5_cardio_cell_sample
    mixedpop2 <-new_summarized_scGPS_object(ExpressionMatrix = day5$dat5_counts,
        GeneMetadata = day5$dat5geneInfo, CellMetadata = day5$dat5_clusters)
    cluster_all <-clustering(object=mixedpop2)
    stab_df <- find_stability(list_clusters=cluster_all$list_clusters,
                             cluster_ref = cluster_all$cluster_ref)
    optimal_stab <- find_optimal_stability(list_clusters =
        cluster_all$list_clusters, stab_df, bagging = FALSE)

[Package scGPS version 1.2.0 Index]