Plot quality-control metrics and thresholds of a "nacho" object
Source:R/autoplot.R
autoplot.nacho.Rd
This function allows to plot any qualit-control figures available
within the shiny app using visualise()
or in the HTML report from render()
.
Usage
# S3 method for nacho
autoplot(
object,
x,
colour = "CartridgeID",
size = 0.5,
show_legend = TRUE,
show_outliers = TRUE,
outliers_factor = 1,
outliers_labels = NULL,
...
)
Arguments
- object
[list] List obtained from
load_rcc()
ornormalise()
.- x
[character] Character string naming the quality-control metrics to plot from
nacho_object
. The possible values are:"BD"
(Binding Density)"FoV"
(Imaging)"PCL"
(Positive Control Linearity)"LoD"
(Limit of Detection)"Positive"
(Positive Controls)"Negative"
(Negative Controls)"Housekeeping"
(Housekeeping Genes)"PN"
(Positive Controls vs. Negative Controls)"ACBD"
(Average Counts vs. Binding Density)"ACMC"
(Average Counts vs. Median Counts)"PCA12"
(Principal Component 1 vs. 2)"PCAi"
(Principal Component scree plot)"PCA"
(Principal Components planes)"PFNF"
(Positive Factor vs. Negative Factor)"HF"
(Housekeeping Factor)"NORM"
(Normalisation Factor)
- colour
[character] Character string of the column in
ssheet_csv
or more generally innacho_object$nacho
to be used as grouping colour.- size
[numeric] A numeric controlling point size (
ggplot2::geom_point()
or line size (ggplot2::geom_line()
).- show_legend
[logical] Boolean to indicate whether the plot legends should be plotted (
TRUE
) or not (FALSE
). Default isTRUE
.- show_outliers
[logical] Boolean to indicate whether the outliers should be highlighted in red (
TRUE
) or not (FALSE
). Default isTRUE
.- outliers_factor
[numeric] Size factor for outliers compared to
size
. Default is1
.- outliers_labels
[character] Character to indicate which column in
nacho_object$nacho
should be used to be printed as the labels for outliers or not. Default isNULL
.- ...
Other arguments (Not used).