lineage: lineage

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

lineage

Description

'lineage' can perform label-free identification of endogenous informative single cell mitochondrial RNA mutation for lineage analysis and clonal evolution. Using mitochondrial genotype matrix as input, select the informative variants of mitochondrial RNA for clones and perform lineage analysis with a consensus clustering method.

Usage

lineage(data, repeats = 30, thread = 10)

Arguments

data	A dataframe containing mitochondrial variants frequency matrix, where a column represents a single cell and a row represents variants frequency of a specific mitochondrial genotype, and two other columns "altAllele" and "refAllele". "altAllele" column represents the mutant allele; "refAllele" column represents the reference allele. Required.
repeats	Number of iterations. Default:30.
thread	Number of threads to use. NULL for non-parallel iterative optimization. Default:10.

Value

A Rdata with the following elements.

best	List, containing the best result in all repeats with max Sscore
label	List, containing the name/id and inferredlineage label of each sample
suggest	Character, recommended dimensional reduction method, tsne or umap
results	List, containing results of all repeats with different 'centers' and 'num of markers'
scores	Numeric, Sscores of all repeats

Examples

data("TF1_clones")
data=TF1_clones$data
## performs a non-parallel iteration process
result=lineage(data, repeats=30, thread=NULL)
## performs a parallel iteration process 
# result=lineage(data, repeats=30, thread=10)

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