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Plot evolutionary signatures across transcriptomes

Source: R/PlotSignature.R
PlotSignature.Rd

Main function to visualize transcriptome indices.

Usage

PlotSignature(
  ExpressionSet,
  measure = "TAI",
  TestStatistic = "FlatLineTest",
  modules = NULL,
  permutations = 1000,
  lillie.test = FALSE,
  p.value = TRUE,
  shaded.area = FALSE,
  custom.perm.matrix = NULL,
  xlab = "Ontogeny",
  ylab = "Transcriptome Index",
  main = "",
  lwd = 4,
  alpha = 0.1,
  y.ticks = 10
)

Arguments

ExpressionSet

a standard PhyloExpressionSet, DivergenceExpressionSet or PolymorphismsExpressionSet object.

measure

type of transcriptome index that shall be computed. E.g.

  • measure = "TAI" (Transcriptome Age Index)

  • measure = "TDI" (Transcriptome Divergence Index)

  • measure = "TPI" (Transcriptome Polymorphism Index)

TestStatistic

a string defining the type of test statistics to be used to quantify the statistical significance the present phylotranscriptomics pattern. Possible values can be:

  • TestStatistic = "FlatLineTest" : Statistical test for the deviation from a flat line

  • TestStatistic = "ReductiveHourglassTest" : Statistical test for the existence of a hourglass shape (high-low-high pattern)

  • TestStatistic = "EarlyConservationTest" : Statistical test for the existence of a early conservation pattern (low-high-high pattern)

  • TestStatistic = "LateConservationTest" : Statistical test for the existence of a late conservation pattern (high-high-low pattern)

  • TestStatistic = "ReverseHourglassTest" : Statistical test for the existence of a reverse hourglass pattern (low-high-low pattern)

modules

a list storing three elements for the ReductiveHourglassTest, EarlyConservationTest, LateConservationTest, or ReverseHourglassTest: early, mid, and late. Each element expects a numeric vector specifying the developmental stages or experiments that correspond to each module. For example:

  • module = list(early = 1:2, mid = 3:5, late = 6:7) divides a dataset storing seven developmental stages into 3 modules.

permutations

a numeric value specifying the number of permutations to be performed for the FlatLineTest, EarlyConservationTest, LateConservationTest, ReductiveHourglassTest or ReverseHourglassTest.

lillie.test

a boolean value specifying whether the Lilliefors Kolmogorov-Smirnov Test shall be performed.

p.value

a boolean value specifying whether the p-value of the test statistic shall be printed as a subtitle.

shaded.area

a boolean value specifying whether a shaded area shall be drawn for the developmental stages defined to be the presumptive phylotypic period.

custom.perm.matrix

a custom bootMatrix (permutation matrix) to perform the underlying test statistic visualized by PlotSignature. Default is custom.perm.matrix = NULL.

xlab

label of x-axis.

ylab

label of y-axis.

main

figure title.

lwd

line width.

alpha

transparency of the shaded area (between [0,1]). Default is alpha = 0.1.

y.ticks

number of ticks on the y-axis. Default is ticks = 10.

Details

This function substitutes the functionality of the PlotPattern function and is based on ggplot2 insead of base R graphics.

The following transcriptome indices can be computed and visualized with this function:

  • Transcriptome Age Index (TAI)

  • Transcriptome Divergence Index (TDI)

  • Transcriptome Polymorphism Index (TPI)

Author

Hajk-Georg Drost

Examples

data(PhyloExpressionSetExample)

# plot TAI pattern and perform flat line test
PlotSignature(PhyloExpressionSetExample, 
              measure       = "TAI", 
              permutations  = 100,
              TestStatistic = "FlatLineTest",
              ylab = "Transcriptome Age Index")
#> Plot signature: ' TAI ' and test statistic: ' FlatLineTest ' running  100  permutations.
#> 
#> [ Number of Eigen threads that are employed on your machine: 8 ]
#> 
#> [ Computing age assignment permutations for test statistic ... ]
#> 
[=========================================] 100%   
#> [ Computing variances of permuted transcriptome signatures ... ]
#> 
#> 
#> [ Number of Eigen threads that are employed on your machine: 8 ]
#> 
#> [ Computing age assignment permutations for test statistic ... ]
#> 
[=========================================] 100%   
#> [ Computing variances of permuted transcriptome signatures ... ]
#> 
#> 
#> Total runtime of your permutation test: 0.071  seconds.
#> 
#> -> We recommended using at least 20000 permutations to achieve a sufficient permutation test.
#> 
#> Significance status of signature:  significant.
#> 
#> -> Now run 'FlatLineTest(..., permutations  = 100, plotHistogram = TRUE)' to analyse the permutation test performance.