sigp {scpoisson}

Significance for first split using sigclust2

Description

This function returns a list with elements mainly generated from sigclust2.

Usage

sigp(test_dat, minSize = 10, sim = 100)

Arguments

test_dat

A UMI count data matrix with samples to cluster as rows and features as columns.

minSize

A numeric value specifying the minimal allowable cluster size (the number of cells for the smallest cluster, default 10).

sim

A numeric value specifying the number of simulations during the Monte Carlo simulation procedure (default 100).

Details

This is a function used to calculate the significance level of the first split from hierarchical clustering based on euclidean distance and Ward's linkage.

Value

A list with the following elements:

• p: p-value for the first split

• z: z-score for the first split

• shc_result: a shc S3-object as defined in sigclust2 package

• clust2: a vector with group index for each cell

• clust_dat: a matrix of data representation used as input for hierarchical clustering

References

Kimes PK, Liu Y, Neil Hayes D, Marron JS (2017). “Statistical significance for hierarchical clustering.” Biometrics, 73(3), 811–821. Michael Linderman (2019). Rclusterpp: Linkable C++ Clustering. R package version 0.2.5, https://github.com/nolanlab/Rclusterpp.