circos.genomicInitialize | R Documentation |
Initialize circular plot with any genomic data
circos.genomicInitialize(
data,
sector.names = NULL,
major.by = NULL,
plotType = c("axis", "labels"),
tickLabelsStartFromZero = TRUE,
axis.labels.cex = 0.4*par("cex"),
labels.cex = 0.8*par("cex"),
track.height = NULL,
...)
data |
A data frame in bed format. |
sector.names |
Labels for each sectors which will be drawn along each sector. It will not modify values of sector index. |
major.by |
Increment of major ticks. It is calculated automatically if the value is not set (about every 10 degrees there is a major tick). |
plotType |
If it is not |
tickLabelsStartFromZero |
Whether axis tick labels start from 0? This will only affect the axis labels while not affect x-values in cells. |
axis.labels.cex |
The font size for the axis tick labels. |
labels.cex |
The font size for the labels. |
track.height |
If |
... |
Pass to |
The function will initialize circular plot from genomic data. If plotType
is set with value in axis
or labels
, there will
create a new track.
The order of sectors related to data structure of data
. If the first column in data
is a factor, the order of sectors
is levels(data[[1]])
; If the first column is just a simple vector, the order of sectors is unique(data[[1]]
.
For more details on initializing genomic plot, please refer to the vignettes.
df = read.cytoband()$df
circos.genomicInitialize(df)
df = data.frame(name = c("TP53", "TP63", "TP73"),
start = c(7565097, 189349205, 3569084),
end = c(7590856, 189615068, 3652765),
stringsAsFactors = FALSE)
circos.genomicInitialize(df)
circos.clear()
circos.genomicInitialize(df, tickLabelsStartFromZero = FALSE)
circos.clear()
circos.genomicInitialize(df, major.by = 5000)
circos.clear()
circos.genomicInitialize(df, plotType = "labels")
circos.clear()
circos.genomicInitialize(df, sector.names = c("tp53", "tp63", "tp73"))
circos.clear()
circos.genomicInitialize(df, sector.names = c("tp53x", "tp63x", "tp73"))
circos.clear()
df[[1]] = factor(df[[1]], levels = c("TP73", "TP63", "TP53"))
circos.genomicInitialize(df)
circos.clear()
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