NEWS.md
New function PlotSignatureTransformed() : Plot evolutionary signatures across transcriptomes and RNA-seq transformations
New function tfStability(): Perform Permutation Tests Under Different Transformations (to test the robustness of the p-values of a given test (e.g. FlatLineTest(), ReductiveHourglassTest(), ReverseHourglassTest(), EarlyConservationTest() and LateConservationTest()) to expression data transformations)
New function LateConservationTest() : Perform Reductive Late Conservation Test (to test for a high-mid-low (or high-high-low) TAI or TDI pattern)
New function lcScore() : Compute the Hourglass Score for the LateConservationTest
internal rcpp functions are now using Eigen to automatically enable parallelization
PlotSignature() updated to be able to perform the TestStatistic = "LateConservationTest".
PlotSignature() now prints p-value as a subtitle rather than via ggplot2::annotate().
tf() now has a pseudocount parameter, which is useful for performing logarithmic transformations when there are genes with 0 counts.
tf() now has an intergerise parameter, which is needed when applying vst or rlog transformations.
tf() updated documentation for performing rank transformation, which assigns ranks to the gene expression values within each stage, based on their relative positions compared to other values.
Improvements to existing test functions (ecScore(), rhScore() and reversehourglassScore()) to give a message when the phylotranscriptomic pattern is unlikely to follow the test statistics.
FlatLineTest() - newly returns the ks test statistics for the fitting of gamma
FlatLineTest() - improved fitting
FlatLineTest() - cpp functions are newly parallelized and progress bar is implemented for the computation of permutations
devtools::test() and devtools::check(), when building this package, which has been accumulated from previous updates.TEI(): Compute the Transcriptome Evolutionary IndexpMatrixTEI: Compute Partial Transcriptome Evolutionary Index (TEI) ValuespStrataTEI: Compute Partial Transcriptome Evolutionary Index (TEI) Strata ValuesbootTEI: Compute a Permutation Matrix of Transcriptome Evolutionary Index (TEI)rcpp functions to support parallel C++ computations for TEI(), pMatrixTEI(), pStrataTEI(), bootTEI()
CollapseReplicates() now returns tibble objectsPlotCategoryExpr() received a new argument y.ticks
std::random_shuffle() function to sample plylostratum or divergence stratum columns and replacing it with std::shuffle(). See full discussion here.dplyr::funs() and tibble::is.tibble()
set.seed(123) which causes an error in the new R version 3.6.0 due to the switch from a non-uniform "Rounding" sampler to a "Rejection" sampler in the new R version; the corresponding unit test test-PlotEnrichment.R was adjusted accordingly. Here the CRAN statement:Note that this ensures using the (old) non-uniform “Rounding” sampler for all 3.x versions of R, and does not add an R version dependency. Note also that the new “Rejection” sampler which R will use from 3.6.0 onwards by default is definitely preferable over the old one, so that the above should really only be used as a temporary measure for reproduction of the previous behavior (and the run time tests relying on it).
new function ReverseHourglassTest() to perform a Reverse Hourglass Test. The Reverse Hourglass Test aims to statistically evaluate the existence of a reverse hourglass pattern based on TAI or TDI computations. The corresponding p-value quantifies the probability that a given TAI or TDI pattern (or any phylotranscriptomics pattern) does follow an hourglass like shape. A p-value < 0.05 indicates that the corresponding phylotranscriptomics pattern does rather follow a reverse hourglass (low-high-low) shape.
new function reversehourglassScore() for computing the Reverse Hourglass Score for the Reverse Hourglass Test
PlotSignature() receives a new TestStatistic (TestStatistic = "ReverseHourglassTest") to perform a revserse hourglass test (= testing the significance of a low-high-low pattern)PlotCIRatio() to compute and visualize TAI/TDI etc patters using bootstrapping and confidence intervals (contributed by @ljljolinq1010)is.ExpressionSet() now prints out more detailed error messages when ExpressionSet format is violated
adapt PlotContribution() to new version of dplyr where summarise_each() is deprecated.
Error message occurring after new dplyr release was:
PlotContribution() works properly with DivergenceExpressionSet input… (@test-PlotContribution.R#16) PlotContribution(DivergenceExpressionSetExample, legendName = “DS”) produced messages.summarise_each() is deprecated. Use summarise_all(), summarise_at() or summarise_if() instead. To map funs over all variables, use summarise_all() summarise_each() is deprecated. Use summarise_all(), summarise_at() or summarise_if() instead. To map funs over all variables, use summarise_all()
Is now fixed.
new function PlotSignature() allows users to plot evolutionary signatures across transcriptomes (based on ggplot2 -> new main visualization function aiming to replace the PlotPattern() function)
new function TPI() allows users to compute the Transcriptome Polymorphism Index introduced by Gossmann et al., 2015.
new function PlotMedians() allows users to compute and visualize the median expression of all age categories
new function PlotVars() allows users to compute and visualize the expression variance of all age categories
PlotContribution() is now based on ggplot2 and loses base graphics arguments
now R/RcppExports.R and src/rcpp_funcs.cpp are included in the package due to previous compilation problems (see also stackoverflow discussion)
MatchMap() is now based on dplyr::inner_join() to match age category table with a gene expression dataset
PlotCorrelation() has been extended and optimized for producing high publication quality plots
PlotMeans() is now based on ggplot2 and lost all base graphics arguments.
PlotRE() is now based on ggplot2 and lost all base graphics arguments.
PlotSelectedAgeDistr() allowing unsers to visualize the PS or DS gene distribution of a subset of genes stored in the input ExpressionSet objectPlotGroupDiffs() allowing users to plot the significant differences between gene expression distributions of PS or DS groupsGroupDiffs() allowing users to perform statistical tests to quantify the gene expression level differences between all genes of defined PS or DS groupsPlotDistribution() now uses ggplot2 to visualize the PS or DS distribution and is also based on the new function PlotSelectedAgeDistr(); furthermore it loses arguments plotText and ... and gains a new argument legendName
remove arguments ‘main.text’ and ‘…’ from PlotCorrelation()
PlotCorrelation() is now based on ggplot2
PlotGroupDiffs() receives a new argument gene.set allowing users to statistically quantify the group specific PS/DS differences of a selected set of genes
analogously to PlotGroupDiffs() the function GroupDiffs() also receives a new argument gene.set allowing users to statistically quantify the group specific PS/DS differences of a selected set of genes
Fixing wrong x-axis labeling in PlotCategoryExpr() when type = "stage-centered" is specified
PlotCategoryExpr() now also prints out the PS/DS absolute frequency distribution of the selected gene.set
PlotCategoryExpr() to Advanced VignettePlotReplicateQuality() to Expression vignettePlotCategoryExpr() allowing users to plot the expression levels of each age or divergence category as boxplot, dot plot or violin plotPlotReplicateQuality() allowing users to visualize the quality of biological replicatesPlotGeneSet() and SelectGeneSet() now have a new argument use.only.map specifying whether or not instead of using a standard ExpressionSet a Phylostratigraphic Map or Divergene Map is passed to the function.adding new vignette Taxonomy providing spep by step instructions on retrieving taxonomic information for any organism of interest
adding new vignette Expression Analysis providing use cases to perform gene expression data analysis with myTAI
adding new vignette Enrichment providing step-by-step instructions on how to perform PS and DS enrichment analyses with PlotEnrichment()
adding examples for pStrata(), pMatrix(), pTAI(), pTDI(), and PlotContribution() to the Introduction Vignette
a new function taxonomy() allows users to retrieve taxonomic information for any organism of interest; this function has been taken from the biomartr package and was removed from biomartr afterwards. Please notice, that in myTAI version 0.1.0 the Introduction vignette referenced to the taxonomy() function in biomartr. This is no longer the case (since myTAI version 0.2.0), because now taxonomy() is implemented in myTAI.
the new taxonomy() function is based on the powerful R package taxize.
a new function SelectGeneSet() allows users to fastly select a subset of genes in an ExpressionSet
a new function DiffGenes() allows users to perform differential gene expression analysis with ExpressionSet objects
a new function EnrichmentTest() allows users to perform a Fisher’s exact test based enrichment analysis of over or underrepresented Phylostrata or Divergence Strata within a given gene set without having to plot the result
a new function PlotGeneSet() allows users to visualize the expression profiles of a given gene set
a new function PlotEnrichment() allows users to visualize the Phylostratum or Divergence Stratum enrichment of a given Gene Set as well as computing Fisher’s exact test to quantify the statistical significance of enrichment
a new function PlotContribution() allows users to visualize the Phylostratum or Divergence Stratum contribution to the global TAI/TDI pattern
a new function pTAI() allows users to compute the phylostratum contribution to the global TAI pattern
a new function pTDI() allows users to compute the divergence stratum contribution to the global TDI pattern
FilterRNASeqCT() has been renamed to Expressed() allowing users to apply this filter function to RNA-Seq data as well as to microarray dataPlotRE() and PlotMeans() are now based on colors from the RColorBrewer package (default)PlotRE() and PlotMeans() now have a new argument colors allowing unsers to choose custom colors for the visualized relative or mean expression profilesgeom.mean() and harm.mean() now are external functions accessible to the myTAI usera new function pStrata() allows users to compute partial TAI/TDI values for all Phylostrata or Divergence Strata
a new function CollapseReplicates() allows users to combine replicate expression levels in ExpressionSet objects
a new function FilterRNASeqCT() allows users to filter expression levels of ExpressionSet objects deriving from RNA-Seq count tables
function MatchMap() now receives a new argument remove.duplicates allowing users to delete duplicate gene ids (that might be stored in the input PhyoMap or DivergenceMap) during the process of matching a Map with an ExpressionSet
FlatLineTest(), ReductiveHourglassTest(), EarlyConservationTest(), and PlotPattern() implement a new argument custom.perm.matrix allowing users to pass their own (custom) permutation matrix to the corresponding function. All subsequent test statistics and p-value/std.dev computations are then based on this custom permutation matrix
EarlyConservationTest() and ReductiveHourglassTest() now have a new parameter gof.warning allowing users to choose whether or not non significant goodness of fit results should be printed as warning
now when specifying TestStatistic = NULL in PlotPattern() only the TAI/TDI profile is drawn (without performing any test statistics); this is equavalent to performing: plot(TAI(PhyloExpressionSetExample)
function combinatorialSignificance() is now named CombinatorialSignificance()
changing the title and description of the myTAI package
some minor changes in vignettes and within the documentation of functions
combinatorialSignificance(), FlatLineTest(), ReductiveHourglassTest(), and EarlyConservationTest() now support multicore processing
MatchMap() has been entirely rewritten and is now based on dplyr; additionally it now has a new argument accumulate that allows you to accumulate multiple expression levels to a unique expressiion level for a unique gene id
All three Vignettes: Introduction, Intermediate, and Advanced have been updated and extended.
two small bugs in ReductiveHourglassTest() and EarlyConservationTest() have been fixed that caused that instead of displaying 3 or 4 plots (par(mfrow=c(1,3)) or par(mfrow=c(2,2))) only 1 plot has been generated
a small bug in PlotMeans() that caused the visualization of a wrong y-axis label when plotting only one group of Phylostrata or Divergence Strata