Create a comparison plot of boxplots for bootstrapped AUC values.
Source:R/bootstrap.R
compareBoxplots.Rd
Present the results of AUC bootstrapping for a collection of scored signatures via boxplots.
Usage
compareBoxplots(
SE_scored,
annotationColName,
signatureColNames,
num.boot = 100,
name = "Boxplot Comparison of Signature AUCs",
pb.show = TRUE,
abline.col = "red",
fill.col = "gray79",
outline.col = "black",
rotateLabels = FALSE,
violinPlot = FALSE
)
Arguments
- SE_scored
a
SummarizedExperiment
object with genes as the row features and signature scores in thecolData
. There should also be a column of annotation data. Required.- annotationColName
a character string giving the column name in
colData
that contains the annotation data. Required.- signatureColNames
a vector of column names in the
colData
that contain the signature score data. Required.- num.boot
an integer indicating the number of times to bootstrap the data.
- name
a character string giving the overall title for the plot. The default is
"Boxplot Comparison of Signature AUCs"
.- pb.show
logical for whether to show a progress bar while running code. Default is
TRUE
.- abline.col
the color to be used for the dotted line at AUC = 0.5 (the chance line). The default is
"red"
.- fill.col
the color to be used to fill the boxplots. The default is
"white"
.- outline.col
the color to be used for the boxplot outlines. The default is
"black"
.- rotateLabels
If
TRUE
, rotate labels. Default isFALSE
.- violinPlot
logical. Setting
violinPlot = TRUE
creates violin plots in place of boxplots. The mean and +/- 1 standard deviation are added to the violin plot interior for each signature. The default isFALSE
.
Examples
# Run signature profiling
choose_sigs <- TBsignatures[c("Zak_RISK_16", "Zhao_NANO_6")]
prof_indian <- runTBsigProfiler(TB_indian[seq_len(25), ],
useAssay = "logcounts",
algorithm = "ssGSEA",
signatures = choose_sigs,
parallel.sz = 1)
#> Parameter update_genes is TRUE. Gene names will be updated.
#> Running ssGSEA
#> Estimating ssGSEA scores for 2 gene sets.
#> [1] "Calculating ranks..."
#> [1] "Calculating absolute values from ranks..."
#>
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#>
#> [1] "Normalizing..."
# Create boxplots
compareBoxplots(prof_indian, annotationColName = "label",
signatureColNames = names(choose_sigs), rotateLabels = TRUE)
#>
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