tjGCluster: trajectory analysis

In CBIIT-CGBB/scCorr: A graph-based k-partitioning approach for single-cell gene-gene correlation analysis

trajectory analysis

Description

trajectory analysis

Usage

tjGCluster(m, from=NULL, to=NULL);

Arguments

m	data.frame or matrix or igraph object
from	start vetex
to	end vetex

Value

A list of trajectory analysis results.

Examples

rm(list=ls());

library(scCorr);

## get data
## 5 clusters of CD4 T cells
ct.c   <- c(6:10); 
## tsne result/output
tsnef  <- "https://github.com/CBIIT-CGBB/scCorr/raw/master/data/01/do_tsne30_2000.txt";
tsne   <- read.table(tsnef, header=T);

## cluster matrix
cluf   <- "https://github.com/CBIIT-CGBB/scCorr/raw/master/data/01/03clust_table.txt";
clu    <- read.table(cluf, header=T);

## make coordinate vector
## sample index of CD4 T cells in the cluster matrix
s.i    <- which(clu[,23] 
## CD4 T cells 
tsne <- tsne[s.i,];
## do trajectory
out  <- tj_list(tsne, ctf = 100);
out.index     <- out[[1]];
out.cellname  <- out[[2]];

CBIIT-CGBB/scCorr documentation built on Dec. 11, 2023, 4 a.m.