OmicCircos (version 1.10.0)

sim.circos: circular data simulation

Description

This function generates data for user to test the circos functions

Usage

sim.circos(seg=10, po=c(20,50), ind=10, link=10, link.pg=10);

Arguments

seg

integer, the segment number. The default is 10.

po

vector, the segment positions. The default is c(20:50)

ind

integer, the number of samples. The default is 10.

link

integer, the number of links. The default is 10.

link.pg

integer, the number of link ploygons. The default is 10.

Value

• sim.circos returns a list containing at least the following components:
• seg.frame
  data.frame, segment data
• seg.mapping
  data.frame, mapping data
• seg.link
  data.fame, link data
• seg.link.pg
  data.frame, link polygon data

References

OmicCircos: an R package for simple and circular visualization of omics data. Cancer Inform. 2014 Jan 16;13:13-20. doi: 10.4137/CIN.S13495. eCollection 2014. PMID: 24526832 [PubMed] PMCID: PMC3921174

Examples

library(OmicCircos);
options(stringsAsFactors = FALSE);
set.seed(1234);

## initial values for simulation data 
seg.num     <- 10;
ind.num     <- 20;
seg.po      <- c(20:50);
link.num    <- 10;
link.pg.num <- 4;
## output simulation data
sim.out <- sim.circos(seg=seg.num, po=seg.po, ind=ind.num, link=link.num, 
  link.pg=link.pg.num);

seg.f     <- sim.out$seg.frame;
seg.v     <- sim.out$seg.mapping;
link.v    <- sim.out$seg.link
link.pg.v <- sim.out$seg.link.pg
seg.num   <- length(unique(seg.f[,1]));

## select segments
seg.name <- paste("chr", 1:seg.num, sep="");
db       <- segAnglePo(seg.f, seg=seg.name);

colors   <- rainbow(seg.num, alpha=0.5);
pdffile  <- "OmicCircos4vignette3.pdf";
pdf(pdffile, 8, 8);
par(mar=c(2, 2, 2, 2));
plot(c(1,800), c(1,800), type="n", axes=FALSE, xlab="", ylab="", main="");

circos(R=400, type="chr", cir=db, col=colors, print.chr.lab=TRUE, W=4, scale=TRUE);
circos(R=360, cir=db, W=40, mapping=seg.v, col.v=8, type="quant90", B=FALSE, col=colors, lwd=2, scale=TRUE);
circos(R=320, cir=db, W=40, mapping=seg.v, col.v=3, type="sv", B=TRUE, col=colors[7],  scale=TRUE);
circos(R=280, cir=db, W=40, mapping=seg.v, col.v=3, type="ss", B=FALSE, col=colors[3],  scale=TRUE);
circos(R=240, cir=db, W=40, mapping=seg.v, col.v=8, type="heatmap", lwd=3);
circos(R=200, cir=db, W=40, mapping=seg.v, col.v=3, type="s.sd", B=FALSE, col=colors[4]);
circos(R=160, cir=db, W=40, mapping=seg.v, col.v=3, type="ci95", B=TRUE, col=colors[4], lwd=2);
circos(R=150, cir=db, W=40, mapping=link.v, type="link", lwd=2, col=colors[c(1,7)]);
circos(R=150, cir=db, W=40, mapping=link.pg.v, type="link.pg", lwd=2, col=sample(colors,link.pg.num));

the.col1=rainbow(10, alpha=0.5)[3];
highlight <- c(160, 410, 6, 2, 6, 10, the.col1, the.col1);
circos(R=110, cir=db, W=40, mapping=highlight, type="hl", lwd=1);

the.col1=rainbow(10, alpha=0.1)[3];
the.col2=rainbow(10, alpha=0.5)[1];
highlight <- c(160, 410, 3, 12, 3, 20, the.col1, the.col2);
circos(R=110, cir=db, W=40, mapping=highlight, type="hl", lwd=2);

dev.off()