multi_best_iter: multi_best_iter

In songjiajia2018/LINEAGE: Label-Free Identification of Endogenous Informative Single Cell Mitochondrial RNA Mutation for Lineage Analysis and Clonal Evolution

multi_best_iter

Description

multi_best_iter performs a parallel iteration process of main to guarantee a more stable and reliable cell clustering/clone tracing result.

Usage

multi_best_iter(
  d,
  centers = c(2, 3),
  nmarker = c(10, 15, 20),
  repeats = 30,
  thread = 10
)

Arguments

d	A list containing 12 submatrices with different mutation types. Output of data_prepare(). Required.
centers	Integer. The number of clusters used in Kmeans procedure. Default: c(2,3).
nmarker	Integer. The number of markers showed in final result. Default: c(10,15,20).
repeats	Integer. The number of iterations. Default: 30.
thread	Integer. Integer. The number of threads to run multi_best_iter. Default: 10.

Details

Parallel iterative optimization

Value

A list containing results of all repeats, including the best result.

Examples

data("TF1_clones")
data=TF1_clones$data
d=data_prepare(data)
a=dim(d[[1]])[2]
if(a>100){
    nmarker=c(15,20)
    centers=3
}else{
    nmarker=c(10,15)
    centers=2
}
# all_results=multi_best_iter(d, centers, nmarker, repeats=30, thread=10)

songjiajia2018/LINEAGE documentation built on Oct. 17, 2022, 6:17 a.m.