plotBaselineSummary - Plots BASELINe summary statistics

Description

plotBaselineSummary plots a summary of the results of selection analysis using the BASELINe method.

Usage

plotBaselineSummary(
baseline,
idColumn,
groupColumn = NULL,
groupColors = NULL,
subsetRegions = NULL,
facetBy = c("region", "group"),
title = NULL,
style = c("summary"),
size = 1,
silent = FALSE,
...
)

Arguments

baseline
either a data.frame returned from summarizeBaseline or a Baseline object returned from groupBaseline containing selection probability density functions and summary statistics.
idColumn
name of the column in baseline containing primary identifiers. If the input is a Baseline object, then this will be a column in the stats slot of baseline.
groupColumn
name of the column in baseline containing secondary grouping identifiers. If the input is a Baseline object, then this will be a column in the stats slot of baseline.
groupColors
named vector of colors for entries in groupColumn, with names defining unique values in the groupColumn and values being colors. Also controls the order in which groups appear on the plot. If NULL alphabetical ordering and a default color palette will be used. Has no effect if facetBy="group".
subsetRegions
character vector defining a subset of regions to plot, corresponding to the regions for which the baseline data was calculated. If NULL all regions in baseline are plotted.
facetBy
one of c(“group”, “region”) specifying which category to facet the plot by, either values in groupColumn (“group”) or regions defined in baseline (“region”). The data that is not used for faceting will be color coded.
title
string defining the plot title.
style
type of plot to draw. One of:
  • "summary": plots the mean and confidence interval for the selection scores of each value in idColumn. Faceting and coloring are determine by values in groupColumn and regions defined in baseline, depending upon the facetBy argument.
size
numeric scaling factor for lines, points and text in the plot.
silent
if TRUE do not draw the plot and just return the ggplot2 object; if FALSE draw the plot.
…
additional arguments to pass to ggplot2::theme.

Value

A ggplot object defining the plot.

Examples

# Subset example data as a demo
data(ExampleDb, package="alakazam")
db <- subset(ExampleDb, c_call %in% c("IGHM", "IGHG"))
set.seed(112)
db <- dplyr::slice_sample(db, n=25)

# Collapse clones
db <- collapseClones(db, cloneColumn="clone_id",
sequenceColumn="sequence_alignment",
germlineColumn="germline_alignment_d_mask",
method="thresholdedFreq", minimumFrequency=0.6,
includeAmbiguous=FALSE, breakTiesStochastic=FALSE)

# Calculate BASELINe
baseline <- calcBaseline(db, 
sequenceColumn="clonal_sequence",
germlineColumn="clonal_germline", 
testStatistic="focused",
regionDefinition=IMGT_V,
targetingModel=HH_S5F,
nproc=1)

calcBaseline will calculate observed and expected mutations for clonal_sequence using clonal_germline as a reference.

Calculating BASELINe probability density functions...



# Grouping the PDFs by sample and isotype annotations
grouped <- groupBaseline(baseline, groupBy=c("sample_id", "c_call"))


Grouping BASELINe probability density functions...
Calculating BASELINe statistics...



# Plot mean and confidence interval by region with custom group colors
isotype_colors <- c("IGHM"="darkorchid", "IGHD"="firebrick", 
"IGHG"="seagreen", "IGHA"="steelblue")
plotBaselineSummary(grouped, "sample_id", "c_call", 
groupColors=isotype_colors, facetBy="region")

7

See also

Takes as input either a Baseline object returned by groupBaseline or a data.frame returned from summarizeBaseline.