shazam (version 1.2.0)

plotSlideWindowTune: Visualize parameter tuning for sliding window approach

Description

Visualize results from slideWindowTune

Usage

plotSlideWindowTune(
  tuneList,
  plotFiltered = c("filtered", "remaining", "per_mutation"),
  percentage = FALSE,
  jitter.x = FALSE,
  jitter.x.amt = 0.1,
  jitter.y = FALSE,
  jitter.y.amt = 0.1,
  pchs = 1:length(tuneList),
  ltys = 1:length(tuneList),
  cols = 1,
  plotLegend = TRUE,
  legendPos = "topright",
  legendHoriz = FALSE,
  legendCex = 1,
  title = NULL,
  returnRaw = FALSE
)

Arguments

tuneList

a list of logical matrices returned by slideWindowTune.

plotFiltered

whether to plot the number of filtered ('filtered'), or remaining ('remaining') sequences for each mutation threshold. Use 'per_mutation' to plot the number of sequences at each mutation value. Default is 'filtered'.

percentage

whether to plot on the y-axis the percentage of filtered sequences (as opposed to the absolute number). Default is FALSE.

jitter.x

whether to jitter x-axis values. Default is FALSE.

jitter.x.amt

amount of jittering to be applied on x-axis values if jitter.x=TRUE. Default is 0.1.

jitter.y

whether to jitter y-axis values. Default is FALSE.

jitter.y.amt

amount of jittering to be applied on y-axis values if jitter.y=TRUE. Default is 0.1.

pchs

point types to pass on to plot. Default is 1:length(tuneList).

ltys

line types to pass on to plot. Default is 1:length(tuneList).

cols

colors to pass on to plot.

plotLegend

whether to plot legend. Default is TRUE.

legendPos

position of legend to pass on to legend. Can be either a numeric vector specifying x-y coordinates, or one of "topright", "center", etc. Default is "topright".

legendHoriz

whether to make legend horizontal. Default is FALSE.

legendCex

numeric values by which legend should be magnified relative to 1.

title

plot main title. Default is NULL (no title)

returnRaw

Return a data.frame with sequence counts (TRUE) or a plot. Default is FALSE.

Details

For each windowSize, if plotFiltered='filtered', the x-axis represents a mutation threshold range, and the y-axis the number of sequences that have at least that number of mutations. If plotFiltered='remaining', the y-axis represents the number of sequences that have less mutations than the mutation threshold range. For the same window size, a sequence can be included in the counts for different mutation thresholds. For example, sequence "CCACCAAAA" with germline "AAAAAAAAA" has 4 mutations. This sequence has at least 2 mutations and at least 3 mutations, in a window of size 4. the sequence will be included in the sequence count for mutation thresholds 2 and 3. If plotFiltered='per_mutation', the sequences are counted only once for each window size, at their largest mutation threshold. The above example sequence would be included in the sequence count for mutation threshold 3.

When plotting, a user-defined amount of jittering can be applied on values plotted on either axis or both axes via adjusting jitter.x, jitter.y, jitter.x.amt and jitter.y.amt. This may be help with visually distinguishing lines for different window sizes in case they are very close or identical to each other. If plotting percentages (percentage=TRUE) and using jittering on the y-axis values (jitter.y=TRUE), it is strongly recommended that jitter.y.amt be set very small (e.g. 0.01).

NA for a combination of mutThresh and windowSize where mutThresh is greater than windowSize will not be plotted.

See Also

See slideWindowTune for how to get tuneList. See jitter for use of amount of jittering.

Examples

# Use an entry in the example data for input and germline sequence
data(ExampleDb, package="alakazam")

# Try out thresholds of 2-4 mutations in window sizes of 3-5 nucleotides 
# on a subset of ExampleDb
tuneList <- slideWindowTune(db = ExampleDb[1:10, ], 
                           mutThreshRange = 2:4, windowSizeRange = 3:5,
                           verbose = FALSE)

# Visualize
# Plot numbers of sequences filtered without jittering y-axis values
plotSlideWindowTune(tuneList, pchs=1:3, ltys=1:3, cols=1:3, 
                    plotFiltered='filtered', jitter.y=FALSE)
                    
# Notice that some of the lines overlap
# Jittering could help
plotSlideWindowTune(tuneList, pchs=1:3, ltys=1:3, cols=1:3,
                    plotFiltered='filtered', jitter.y=TRUE)
                    
# Plot numbers of sequences remaining instead of filtered
plotSlideWindowTune(tuneList, pchs=1:3, ltys=1:3, cols=1:3, 
                    plotFiltered='remaining', jitter.y=TRUE, 
                    legendPos="bottomright")
                    
# Plot percentages of sequences filtered with a tiny amount of jittering
plotSlideWindowTune(tuneList, pchs=1:3, ltys=1:3, cols=1:3,
                    plotFiltered='filtered', percentage=TRUE, 
                    jitter.y=TRUE, jitter.y.amt=0.01)