Plots: Plotting Functions.

In matdoering/openPrimeR: Multiplex PCR Primer Design and Analysis

Plotting Functions.

Description

plot_cvg_vs_set_size

Plots the coverage ratios of the input primer sets against the size of the sets.

plot_penalty_vs_set_size

Plots the penalties of the input primer sets against the number of primers contained in each set. The penalties are computed using score_primers where more information is provided on how to set alpha.

plot_primer_subsets

Visualizes the coverage of optimized primer subsets.

plot_primer

Visualizes the binding positions of every primer relative to the target binding region in the corresponding template sequences.

plot_template_cvg

Creates a bar plot visualizing the covered templates.

plot_primer_cvg

Shows which groups of templates are covered by individual primers.

plot_constraint

Shows the distribution of the primer properties. The current constraint settings are indicated with dashed lines.

plot_constraint_fulfillment

Visualizes which primers pass the constraints and which primers break the constraints

plot_cvg_constraints

Plots the distribution of the coverage constraint values.

plot_constraint_deviation

Plots the deviation of primer properties from the target ranges.

plot_primer_binding_regions

Visualizes the number of binding events of the primers with respect to the allowed binding regions in the templates.

plot_conservation

Plots the template sequence conservation (range [0,1]) according to the Shannon entropy of the sequences.

Usage

plot_conservation(entropy.df, alignments, template.df, gap.char = "-")

plot_primer_binding_regions(
  primers,
  templates,
  direction = c("both", "fw", "rev"),
  group = NULL,
  relation = c("fw", "rev"),
  region.names = c("Binding region", "Amplification region"),
  ...
)

plot_constraint(
  primers,
  settings,
  active.constraints = names(constraints(settings)),
  ...
)

plot_constraint_fulfillment(
  primers,
  settings,
  active.constraints = names(constraints(settings)),
  plot.p.vals = FALSE,
  ...
)

plot_cvg_constraints(
  primers,
  settings,
  active.constraints = names(cvg_constraints(settings)),
  ...
)

plot_constraint_deviation(
  primers,
  settings,
  active.constraints = names(constraints(settings)),
  ...
)

plot_cvg_vs_set_size(
  primer.data,
  template.data,
  show.labels = TRUE,
  highlight.set = NULL
)

plot_penalty_vs_set_size(
  primer.data,
  settings,
  active.constraints = names(constraints(settings)),
  alpha = 0
)

plot_primer_subsets(primer.subsets, template.df, required.cvg = 1)

plot_primer(
  primer.df,
  template.df,
  identifier = NULL,
  relation = c("fw", "rev"),
  region.names = c("Binding region", "Amplification region")
)

plot_template_cvg(primers, templates, per.mismatch = FALSE, ...)

plot_primer_cvg(primers, templates, per.mismatch = FALSE, ...)

Arguments

entropy.df	A data frame with entropies. Each row gives the entropies of a group of related template sequences for all columns of the alignment.
alignments	A list with DNABin alignment objects corresponding to the groups (rows) in the alignment.
template.df	An object of class Templates containing the template sequences.
gap.char	The gap char in the alignments. By default, gap.char is set to "-".
primers	Either a single Primers object with evaluated primer coverage or a list containing such Primers objects.
templates	If primers is a Primers object, templates should be a Templates object. If primers is a list, then templates should be a list of Templates objects.
direction	The directionality of primers to be plotted. This can either be "both" to plot primers of both directions (the default), "fw" to plot only forward primers, or "rev" to plot only reverse primers.
group	Optional identifiers of template groups for which binding events should be determined. By default, group is set to NULL such that all templates are considered.
relation	Whether binding positions are computed relative to forward ("fw") or reverse ("rev") binding regions. The default is "fw".
region.names	Character vector of length 2 providing the names of the binding and amplification region.
...	Optional arguments groups (a character vector of groups to be plotted when primers is a single primer set), highlight.set (the identifier of a primer set to be highlighted when primers is a list), ncol (a numeric indicating the number of facet columns if primers is a list), deviation.per.primer (a boolean indicating whether constraint deviations should be plotted per primer rather than per constraint if primers is a list)
settings	An object of class DesignSettings containing the constraints to be considered.
active.constraints	A character vector containing the identifiers to be considered for plotting. By default, active.constraints is NULL such that all computed constraints found in settings are plotted.
plot.p.vals	An optional logical argument indicating whether p-values computed via primer_significance should be annotated in the plot. The default is FALSE.
primer.data	List with objects of class Primers containing the primer sets that are to be compared.
template.data	List with objects of class Templates containing the templates corresponding to primer.data.
show.labels	Whether the identifiers of the primer sets should be annotated in the plot. The default is TRUE.
highlight.set	A character vector providing the identifiers of primer sets to highlight. By default, highlight.set is NULL such that no highlighting takes place.
alpha	A numeric in the range [0,1] defining the trade-off between the maximal deviation of a constraint (large alpha) and all constraint deviations (large alpha). By default, alpha is set to 0 such that the absolute deviation across all constraints is considered.
primer.subsets	A list with optimal primer subsets, each of class Primers. The k-th list entry should correspond to an object of class Primers representing the primer subset of size k whose coverage ratio is the largest among all possible subsets of size k.
required.cvg	The required coverage ratio. The default is 100%; this value is plotted as a horizontal line.
primer.df	An object of class Primers containing primers with evaluated primer coverage.
identifier	Identifiers of primers that are to be considered. If identifier is set to NULL (the default), all primers are considered.
per.mismatch	A logical specifying whether the visualization should be stratified according to the allowed number of mismatches. By default, per.mismatch is set to FALSE such that the overall coverage is plotted.

Details

The deviations for plot_constraint_deviation are computed in the following way. Let the minimum and maximum allowed constraint values be given by the interval [s, e] and the observed value be p. Then, if p < s, we output -p/|s|, if p > e we output p/|e|, and otherwise, i.e. if s <= p <= e, we output 0.

The primer.subsets argument for plot_primer_subsets can be computed using subset_primer_set. The line plot indicates the ratio of covered templates when considering all primers in a primer set of a given size. The bar plots indicate the coverage ratios of individual primers in a set. The target coverage ratio is indicated by a horizontal line. Bars exceeding the target ratio possibly indicate the existence of redundant coverage events.

Value

plot_conseration returns a plot showing the degree of sequence conservation in the templates.

plot_primer_binding_regions returns a plot of the primer binding regions.

plot_constraint returns a plot showing the distribution of primer properties.

plot_constraint_fulfillment returns a plot indicating the constraints that are fulfilled by the input primers.

plot_cvg_constraints returns a plot showing the distribution of the coverage constraint values.

plot_constraint_deviation returns a plot showing the deviations of the primer properties from the target constraints.

plot_cvg_vs_set_size returns a plot of coverage vs set size.

plot_penalty_vs_set_size returns a plot of constraint penalties vs primer set sizes.

plot_primer_subsets plots the coverages of the primer subsets provided via primer.subsets.

plot_primer plots the primer binding sites in the templates.

plot_template_cvg creates a plot showing the number of covered template sequences.

plot_primer_cvg creates a plot showing the coverage of individual primers.

Note

Computing the conservation scores for using plot_conservation requires the MAFFT software for multiple alignments (http://mafft.cbrc.jp/alignment/software/).

Examples

data(Ippolito)
# Select binding regions for every group of templates and plot:
template.df <- select_regions_by_conservation(template.df, win.len = 30)
if (length(template.df) != 0) {
     p1 <- plot_conservation(attr(template.df, "entropies"), 
                             attr(template.df, "alignments"), template.df)
}
# Select binding regions for all templates and plot:
data(Ippolito)
template.df <- select_regions_by_conservation(template.df, by.group = FALSE)
if (length(template.df) != 0) {
     p2 <- plot_conservation(attr(template.df, "entropies"), 
                             attr(template.df, "alignments"), template.df)
} 

# Primer binding regions of a single primer set
data(Ippolito)
p <- plot_primer_binding_regions(primer.df, template.df)
# Primer binding regions of multiple primer sets
data(Comparison)
p.comp <- plot_primer_binding_regions(primer.data[1:3], template.data[1:3])

# Plot histogram of constraints for a single primer set
data(Ippolito)
p <- plot_constraint(primer.df, settings, 
                     active.constraints = c("gc_clamp", "gc_ratio"))
# Compare constraints across multiple primer sets
data(Comparison)
p.cmp <- plot_constraint(primer.data[1:3], settings, 
                         active.constraints = c("gc_clamp", "gc_ratio"))

# Plot fulfillment for a single primer set:
data(Ippolito)
p <- plot_constraint_fulfillment(primer.df, settings)
# Plot fulfillment for multiple primer sets:
data(Comparison)
p.cmp <- plot_constraint_fulfillment(primer.data[1:5], settings)

# Plot coverage constraints of a single primer set
data(Ippolito)
p <- plot_cvg_constraints(primer.df, settings)
# Plot coverage constraints for mulitple primer sets
data(Comparison)
p.cmp <- plot_cvg_constraints(primer.data[1:2], settings)

# Deviations for a single primer set
data(Ippolito)
p.dev <- plot_constraint_deviation(primer.df, settings)
# Deviations for multiple primer sets
data(Comparison)
p.dev.cmp <- plot_constraint_deviation(primer.data, settings)

# Plot coverage vs primer set size
data(Comparison)
p <- plot_cvg_vs_set_size(primer.data, template.data)

# Plot penalties vs number of primers
data(Comparison)
p <- plot_penalty_vs_set_size(primer.data, settings)

# Plot the coverage of optimal primer subsets
data(Ippolito)
primer.subsets <- subset_primer_set(primer.df, template.df, k = 3)
p <- plot_primer_subsets(primer.subsets, template.df)

# Plot of individual primer binding positions
data(Ippolito)
p <- plot_primer(primer.df[1,], template.df[1:30,])

# Visualize the template coverage of a single primer set
data(Ippolito)
p.cvg <- plot_template_cvg(primer.df, template.df)
# Stratify by allowed mismatches:
p.mm.cvg <- plot_template_cvg(primer.df, template.df, per.mismatch = TRUE)
# Compare the coverage of multiple primer sets
data(Comparison)
p.cmp.cvg <- plot_template_cvg(primer.data[1:2], template.data[1:2])
# Stratify by allowed mismatches:
p.cmp.cvg.mm <- plot_template_cvg(primer.data[1:2], template.data[1:2], 
                                 per.mismatch = TRUE)

# Plot expected coverage per primer
data(Ippolito)
p.cvg <- plot_primer_cvg(primer.df, template.df)
# Plot coverage stratified by allowed mismatches:
p.cvg.mm <- plot_primer_cvg(primer.df, template.df, per.mismatch = TRUE)
# Plot coverage of multiple primer sets
data(Comparison)
p.cvg.cmp <- plot_primer_cvg(primer.data[1:3], template.data[1:3])

matdoering/openPrimeR documentation built on Feb. 11, 2024, 9:22 p.m.