An example of a default ManhattanPlot component without any extra properties.
library(dashBio)
library(data.table)
app <- Dash$new()
data = read.table("https://git.io/manhattan_data.csv",
header = TRUE, sep = ",")
genMark <- function(n){
l <- list(sprintf('%s', n))
names(l) <- 'label'
return(l)
}
genMarks <- function(min, max, by){
s <- seq(from=min, to=max, by)
l <- lapply(s, genMark)
names(l) <- s
return(l)
}
app$layout(htmlDiv(list(
'Threshold Value',
dccSlider(
id = 'default-manhattanplot-input',
min = 1,
max = 10,
step = 1,
value = 6,
marks = genMarks(1,10,1)
),
htmlBr(),
htmlDiv(
dccGraph(
id = 'default-manhattanplot',
figure = dashbioManhattan(
dataframe = data
)
)
)
)))
app$callback(
output(id = "default-manhattanplot", property = "figure"),
params = list(
input(id = 'default-manhattanplot-input', property = 'value')
),
update_manhattanplot <- function(threshold){
return(
dashbioManhattan(
dataframe = data,
genomewideline_value = threshold
)
)
}
)
Change the colors of the suggestive line and the genome-wide line.
library(dashBio)
data = read.table("https://git.io/manhattan_data.csv",
header = TRUE, sep = ",")
dccGraph(
figure = dashbioManhattan(
dataframe = data,
suggestiveline_color = "#AA00AA",
genomewideline_color = "#AA5500"
)
)
Change the color of the points that are considered significant.
library(dashBio)
data = read.table("https://git.io/manhattan_data.csv",
header = TRUE, sep = ",")
dccGraph(
figure = dashbioManhattan(
dataframe = data,
highlight_color = "#00FFAA"
)
)
dash_bio.ManhattanPlot
is a Python-based component,
and may not be available in other languages.