ssvSignalBandedQuantiles {seqsetvis} | R Documentation |
plot profiles from bigwigs
ssvSignalBandedQuantiles(bw_data, y_ = "y", x_ = "x", by_ = "fake", hsv_reverse = FALSE, hsv_saturation = 1, hsv_value = 1, hsv_grayscale = FALSE, hsv_hue_min = 0, hsv_hue_max = 0.7, hsv_symmetric = FALSE, n_quantile = 18, quantile_min = 0.05, quantile_max = 0.95, return_data = FALSE)
bw_data |
a GRanges or data.table of bigwig signal.
As returned from |
y_ |
the variable name in bw_data for y axis in plot |
x_ |
the variable name in bw_data for x axis in plot |
by_ |
the variable name in bw_data to facet on |
hsv_reverse |
logical, should color scale be reversed? default FALSE |
hsv_saturation |
numeric [0, 1] saturation for color scale. default 1 |
hsv_value |
numeric [0, 1] value for color scale. default 1 |
hsv_grayscale |
logical, if TRUE gray() is used instead of rainbow(). default FALSE |
hsv_hue_min |
numeric [0, hsv_hue_max) hue min of color scale |
hsv_hue_max |
numeric (hsv_hue_min, 1] hue max of color scale |
hsv_symmetric |
if TRUE, colorscale is symmetrical, default FALSE. |
n_quantile |
number of evenly size quantile bins |
quantile_min |
the lowest quantile start |
quantile_max |
the highest quantile end |
return_data |
logical. If TRUE, return value is no longer ggplot and is instead the data used to generate that plot. Default is FALSE. |
ggplot object using ribbon plots to show quantile distributions
#rainbow colors qgr = CTCF_in_10a_profiles_gr ssvSignalBandedQuantiles(qgr) #grayscale ssvSignalBandedQuantiles(qgr, hsv_grayscale = TRUE, hsv_symmetric = TRUE, hsv_reverse = TRUE) #using "by_" per sample ssvSignalBandedQuantiles(qgr, hsv_grayscale = TRUE, hsv_symmetric = TRUE, hsv_reverse = TRUE, by_ = "sample") #adding spline smoothing splined = applySpline(qgr, n = 10, by_ = c("id", "sample")) ssvSignalBandedQuantiles(splined, n_quantile = 50, quantile_min = .25, quantile_max = .75, hsv_symmetric = TRUE, hsv_reverse = TRUE, by_ = "sample")