tcm: TCM: A package for visualizing temporal scRNA-seq data

Description Usage Arguments Value Author(s) Examples

Description

TCM: A package for visualizing temporal scRNA-seq data

Visualizing temporal scRNA-seq by topographic cell map

Usage

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tcm(X, time.table, ls, init = NULL, control = NULL)

Arguments

X

a read count matrix where each row represents a gene and each column represents a cell

time.table

a cell by time point table indicating the source of each cell

ls

the prototype landscape for TCM (default: landscape(type = 'temporal.convolving', time.points = ncol(CT), K = 15, n.prototype = 15, n.circle = 10, n.prev = 3))

init:

initialization parameters

control:

control parameters

Value

a tcm object

Author(s)

Wuming Gong, gongx030@umn.edu

Examples

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library(tcm)

# simulate a simple temporal scRNA-seq data with 2,000 genes, 500 cells and five different lineages.  
# The single cell data are sampled across five time points following a sequentail differentiation model. 
set.seed(122)
sim <- sim.rnaseq.ts(N = 2000, M = 500, n.lineage = 5, n.time.points = 5)
X <- assays(sim)$count
time.table <- colData(sim)$time.table
mf <- tcm(X, time.table = time.table)
bg.cell <- rainbow(5)[colData(sim)$lineage]
dev.new(height = 10, width = 12)
par(mar = c(5, 5, 5, 15))
plot(mf, pch = 21, bg = bg.cell, cex = 1.5)

legend(par('usr')[2], par('usr')[4], 1:sim$n.lineage, bty = 'n', xpd = NA, pt.bg = bg.lineage, pch = 21, col = 'black', cex = 1.75)

gongx030/tcm documentation built on June 4, 2019, 7:26 p.m.