Plot evolutionary signatures across transcriptomes and RNA-seq transformations
Source:R/PlotSignatureTransformed.R
PlotSignatureTransformed.RdPlotSignatureTransformed aims to statistically evaluate the
stability of ReductiveHourglassTest, FlatLineTest,
ReverseHourglassTest, EarlyConservationTest, or
LateConservationTest
(all based on TAI or TDI computations) against different
data transformations AND plot the resulting TAI profiles using PlotSignature.
The corresponding p-value quantifies the probability that a given TAI or TDI pattern (or any phylotranscriptomics pattern)
does not support the chosen test. A p-value < 0.05 indicates that the corresponding phylotranscriptomics pattern does
indeed support the chosen test.
Usage
PlotSignatureTransformed(
ExpressionSet,
measure = "TAI",
TestStatistic = "FlatLineTest",
transforms = c("none", "sqrt", "log2", "rank", "squared"),
modules = NULL,
permutations = 1000,
pseudocount = 1,
p.value = TRUE,
shaded.area = FALSE,
xlab = "Ontogeny",
ylab = "Transcriptome Index",
main = "",
lwd = 4,
alpha = 0.1,
y.ticks = 3
)Arguments
- ExpressionSet
a standard PhyloExpressionSet or DivergenceExpressionSet 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 lineTestStatistic="ReductiveHourglassTest": Statistical test for the existence of a hourglass shape (high-low-high pattern)TestStatistic="ReverseHourglassTest": Statistical test for the existence of a reverse hourglass pattern (low-high-low 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)
- transforms
a character vector of any valid function that transforms gene expression levels. Available options are:
transforms = "none": No transformation (absolute expression)transforms = "log2": Computes binary (i.e., base 2) logarithms, \(log_{2}{X}\).transforms = "log": Computes natural logarithms, \(log_{e}{X}\).transforms = "log10": Computes common logarithms (i.e., base 10), \(log_{10}{X}\).transforms = "sqrt": Computes the (principle) square root, \(\sqrt{X}\).transforms = "vst": (Quickly) estimates dispersion trend and applies a variance stabilizing transformation (please make sure that the DESeq2 package is installed).transforms = "rlog": (Robustly) estimates dispersion trend and applies a variance stabilizing transformation (please make sure that the DESeq2 package is installed).transforms = "rank": Ranks genes from lowest to highest based on their expression levels, at each condition (e.g., developmental stage). The gene's expression value is replaced by its sample rank or average ranks in case of ties.transforms = "squared": Computes the square, \(X^2\).
- modules
a list storing three elements for the
ReductiveHourglassTest,EarlyConservationTest,LateConservationTest, orReverseHourglassTest: 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,ReductiveHourglassTestorReverseHourglassTest.- pseudocount
any valid number to add to the expression matrix prior to log transformations.
- p.value
a boolean value specifying whether the p-value of the test statistic shall be printed within the plot area.
- shaded.area
a boolean value specifying whether a shaded area shall be drawn for the developmental stages defined to be the presumptive phylotypic period.
- 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 = 3.
Value
a ggplot object containing the following information
for each visualised transcriptome indices:
p.value : the p-value quantifying the statistical significance (depending on the chosen test) of the given phylotranscriptomics pattern.
Details
Visualisation and assessment for the stability of data transforms on the permutation test of choice.
For details, please consult the main function PlotSignature,
as well as tf, ReductiveHourglassTest,
FlatLineTest, ReverseHourglassTest,
LateConservationTest or EarlyConservationTest.
In most cases, users can replace PlotSignature simply with
PlotSignatureTransformed to obtain the multi-panel plot with different
transformations to visualise the stability of the pattern observed with PlotSignature.
Examples
if (FALSE) { # \dontrun{
data(PhyloExpressionSetExample)
# Flat line test
PlotSignatureTransformed(ExpressionSet = PhyloExpressionSetExample,
TestStatistic = "FlatLineTest",
transforms = c("none", "log2", "sqrt", "rank", "squared"))
# Reductive hourglass test
PlotSignatureTransformed(ExpressionSet = PhyloExpressionSetExample,
TestStatistic = "ReductiveHourglassTest",
transforms = c("none", "log2", "sqrt", "rank", "squared"),
modules = list(early = 1:2, mid = 3:5, late = 6:7))
library(DESeq2)
PlotSignatureTransformed(ExpressionSet = PhyloExpressionSetExample,
TestStatistic = "ReductiveHourglassTest",
transforms = c("none", "log2", "sqrt", "vst", "rank", "squared"),
modules = list(early = 1:2, mid = 3:5, late = 6:7))
} # }