circlize (version 0.4.10)

circos.genomicHeatmap: Add heatmaps for selected regions

Description

Add heatmaps for selected regions

Usage

circos.genomicHeatmap(
    bed,
    col,
    na_col = "grey",
    numeric.column = NULL,
    border = NA,
    border_lwd = par("lwd"),
    border_lty = par("lty"),
    connection_height = convert_height(5, "mm"),
    line_col = par("col"),
    line_lwd = par("lwd"),
    line_lty = par("lty"),
    heatmap_height = 0.15,
    side = c("inside", "outside"),
    track.margin = circos.par("track.margin"))

Arguments

bed

a data frame in bed format, the matrix is stored from the fourth column.

col

colors for the heatmaps. The value can be a matrix or a color mapping function generated by colorRamp2.

na_col

color for NA values.

numeric.column

column index for the numeric columns. The values can be integer index or character index

border

border of the heatmap grids.

border_lwd

line width for borders of heatmap grids

border_lty

line style for borders of heatmap grids

connection_height

height of the connection lines. If it is set to NULL, no connection will be drawn.

line_col

col of the connection line. The value can be a vector.

line_lwd

line width of the connection lines.

line_lty

line style of the connection lines.

heatmap_height

height of the heatmap track

side

side of the heatmaps. Is the heatmap facing inside or outside?

track.margin

bottom and top margins

Details

The function visualizes heatmaps which correspond to a subset of regions in the genome. The correspondance between heatmaps and regions are identified by connection lines.

The function actually creates two tracks, one track for the connection lines and one track for the heamtaps. The heatmaps always fill the whole track.

See Also

https://jokergoo.github.io/circlize_book/book/high-level-genomic-functions.html#genomic-heatmap

Examples

# NOT RUN {
circos.initializeWithIdeogram(plotType = c("labels", "axis"))
bed = generateRandomBed(nr = 100, nc = 4)
col_fun = colorRamp2(c(-1, 0, 1), c("green", "black", "red"))
circos.genomicHeatmap(bed, col_fun, side = "inside", border = "white")
circos.genomicHeatmap(bed, col_fun, side = "outside", 
    line_col = as.numeric(factor(bed[[1]])))
# }