Paint Areas on One Data Track

Paint area on one data track with different height and different locations inside of a track. Plot types includes "mountain", "curtain", and "band". Plot data should have genomic positions(chromosome names, start and end positions) as well as height values. For band type plot, two columns of height values are required.

Usage

RCircos.Area.Plot(area.data=NULL, data.col=c(4,5),
    track.num=NULL, side=c("in", "out"), 
    plot.type=c("mountain", "curtain", "band"), 
    min.value=NULL, max.value=NULL, area.color="gray",
    border.col="black", inside.pos=NULL, outside.pos=NULL, 
    genomic.columns=3, is.sorted=TRUE)

Arguments

area.data

A data frame with two or three columns for genomic positions, one or more columns for heights of each data point, and an optional column for polygon colour.

data.col

Non-negative integer, representing the ordinal number of the column in input data set that contains the data to be plotted.

track.num

Non-negative integer, representing the ordinal number of the plot track where the lines will be plotted.

side

Character vector, either "in" or "out", representing the position related to chromosome ideogram.

plot.type

Character vector, either "mountain", "curtain", or "band"

min.value

Numeric, minimum value in data column of polygon data.

max.value

Numeric, maximum value in data column of polygon data.

area.color

Color names for fill of the area.

border.col

Color name for border color, default null.

inside.pos

Non-negative numeric, inside position (relative to the centre of plot area) of the track.

outside.pos

Non-negative numeric, outside position (relative to the centre of plot area) of the track.

genomic.columns

Non-negative integer, total number of columns for genomic position in each row. Must be either 3 or 2.

is.sorted

Logic, whether the data is sorted by chromosome names and start positions.

Author

Henry Zhang

Examples

if (FALSE) { # \dontrun{
library(RCircos);
data(UCSC.HG19.Human.CytoBandIdeogram);
data(RCircos.Polygon.Data);

RCircos.Set.Core.Components(  
    cyto.info=UCSC.HG19.Human.CytoBandIdeogram,  
    chr.exclude=NULL, tracks.inside=10, tracks.outside=5)  
RCircos.Set.Plot.Area();
RCircos.Chromosome.Ideogram.Plot()

load("RCircos/data/RCircos.Histogram.Data.RData")

area.data <- RCircos.Histogram.Data;
adj.value <- runif(nrow(area.data), 0, 0.4)
area.data["DataT"] <- 0.5 + adj.value
area.data["DataB"] <- 0.5 - adj.value

RCircos.Area.Plot(area.data, data.col=4, plot.type="mountain", 
    inside.pos=1.2, outside.pos=1.5, is.sorted=FALSE)

RCircos.Area.Plot(area.data, data.col=4, plot.type="curtain", 
    inside.pos=0.9, outside.pos=1.1, is.sorted=FALSE)

RCircos.Area.Plot(area.data, data.col=c(5,6), plot.type="band", 
    inside.pos=0.4, outside.pos=0.7, is.sorted=FALSE)} # }