View source: R/calcOutlierMap.R
calcOutlierMap | R Documentation |
Calculate the median absolute deviation (statistical) outliers measurements
and fold-change criteria from an ADAT. Two values are required for the
calculation: median absolute deviation (MAD) and fold-change (FC). Outliers
are determined based on the result of both 6*MAD
and x*FC
, where x
is the number of fold changes defined.
calcOutlierMap(
data,
anno_tbl = NULL,
apt.order = c(NA, "dilution", "signal"),
sample.order = NULL,
fc.crit = 5
)
## S3 method for class 'outlier_map'
print(x, ...)
data |
A |
anno_tbl |
An annotations table produced via |
apt.order |
Character. How should the columns/features be ordered?
Options include: by dilution mix ("dilution"), by median overall signal
("signal"), or as-is in |
sample.order |
Either a character string indicating the column name
with entries to be used to order the data frame rows, or a numeric vector
representing the order of the data frame rows. The
default ( |
fc.crit |
Integer. The fold change criterion to evaluate. Defaults to 5x. |
x |
An object of class |
... |
Arguments for S3 print methods. |
For the S3 plotting method, see plot.Map()
.
A list of class c("outlier_map", "Map")
containing:
matrix |
A boolean matrix of |
x.lab |
A character string containing the plot x-axis label. |
title |
A character string containing the plot title. |
rows.by.freq |
A logical indicating if the samples are ordered by outlier frequency. |
class.tab |
A table containing the frequencies of each class if input
|
sample.order |
A numeric vector representing the order of the data frame rows. |
legend.sub |
A character string containing the plot legend subtitle. |
print(outlier_map)
: There is a S3 print method for class "outlier_map"
.
Stu Field
Other Calc Map:
getOutlierIds()
,
plot.Map()
dat <- example_data |> dplyr::filter(SampleType == "Sample")
om <- calcOutlierMap(dat)
class(om)
# S3 print method
om
# `sample.order = "frequency"` orders samples by outlier frequency
om <- calcOutlierMap(dat, sample.order = "frequency")
om$rows.by.freq
om$sample.order
# order samples field in Adat
om <- calcOutlierMap(dat, sample.order = "Sex")
om$sample.order
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