myTAI

Perform Evolutionary Transcriptomics with R

To put aside for a moment the matter-of-factness of an exact scientist, I will confess that I frequently have the feeling in my experimental work of holding a dialogue with someone who is considerably brighter than me.

- Hans Spemann

Development is the major process establishing complex life on earth. Hence, studying the evolution of developmental processes allows us to understand the key machanisms that control and constraint the evolution and diversification of complex organisms on this planet. Evolutionary transcriptomics can be used as a method to quantify the evolutionary conservation of developmental transcriptomes (Drost et al., 2015 Mol. Biol. Evol. ; Drost et al., 2016 Mol. Biol. Evol.).

In general, the myTAI package implements methods to quantify transcriptome conservation in biological processes.

This evolutionary transcriptomics approach (= phylotranscriptomics) summarizes the concept of combining the phylogenetic age of genes or their sequence conservation with gene expression levels to quantify transcriptome conservation throughout biological processes (Domazet-Loso and Tautz, 2010 Nature ; Quint, Drost et al., 2012 Nature ; Drost et al., 2015 Mol. Biol. Evol. ; Drost et al., 2016 Mol. Biol. Evol.).

This subfield of Evolutionary Developmental Biology aims to determine and investigate stages or periods of evolutionary conservation in biological processes of extant species. However, although motivated by and applied to developmental processes, the myTAI package is implemented to quantify transcriptome conservation in any transcriptome experiment of interest and therefore aims to provide a standard approach to investigate the evolution of biological processes in the context of transcriptome conservation.

The myTAI package aims to provide a standard tool for evolutionary transcriptomics studies and relies on gene age and sequence conservation estimates as input. This approach allows researchers to study the evolution of biological processes and to detect stages or periods of evolutionary conservation or variability. In particular, myTAI provides an easy to use and optimized software framework to perform evolutionary transcriptomics analyses for any annotated organism and biological process of interest. Additionally, customized visualization functions implemented in myTAI allow users to generate publication quality plots for their own evolutionary transcriptomics research.

The following tutorials will provide use cases and detailed explainations of how to quantify transcriptome conservation with myTAI and how to interpret the results generated with this software tool.

Citation

Please cite one of the following papers when using myTAI for your own research (depending on your application). This will allow me to continue working on this software tool and will motivate me to extend its functionality and usability. Many thanks in advance :)

Drost HG, Gabel A, Domazet-Loso T, Quint M, Grosse I. 2016. Capturing Evolutionary Signatures in Transcriptomes with myTAI. bioRxiv

Drost HG, Bellstädt J, Ó'Maoiléidigh DS, Silva AT, Gabel A, Weinholdt C, Ryan PT, Dekkers BJW, Bentsink L, Hilhorst H, Ligterink W, Wellmer F, Grosse I, and Quint M. 2016. Post-embryonic hourglass patterns mark ontogenetic transitions in plant development. Mol. Biol. Evol. 33 (5): 1158-1163. doi:10.1093/molbev/msw039

Drost HG, Gabel A, Grosse I, Quint M. 2015. Evidence for Active Maintenance of Phylotranscriptomic Hourglass Patterns in Animal and Plant Embryogenesis. Mol. Biol. Evol. 32 (5): 1221-1231. doi:10.1093/molbev/msv012

Tutorials

These tutorials introduce users to myTAI:

• Introduction to the myTAI Package
• Intermediate Concepts of Phylotranscriptomics
• Advanced Topics of Phylotranscriptomics
• Perform Age Enrichment Analyses
• Gene Expression Analysis with myTAI
• Taxonomic Information Retrieval

NEWS

The current status of the package as well as a detailed history of the functionality of each version of myTAI can be found in the NEWS section.

Installation

Users can download myTAI from CRAN :

# install myTAI 0.4.0 from CRAN
install.packages("myTAI", dependencies = TRUE)

Package Dependencies

# to perform differential gene expression analyses with myTAI
# please install the edgeR package
# install edgeR
source("http://bioconductor.org/biocLite.R")
biocLite("edgeR")

Getting started with myTAI

Users can also read the tutorials within (RStudio) :

# source the myTAI package
library(myTAI)

# look for all tutorials (vignettes) available in the myTAI package
# this will open your web browser
browseVignettes("myTAI")

# or as single tutorials

# open tutorial: Introduction to Phylotranscriptomics and myTAI
 vignette("Introduction", package = "myTAI")

# open tutorial: Intermediate Concepts of Phylotranscriptomics
 vignette("Intermediate", package = "myTAI")

# open tutorial: Advanced Concepts of Phylotranscriptomics
 vignette("Advanced", package = "myTAI")

# open tutorial: Age Enrichment Analyses
 vignette("Enrichment", package = "myTAI")
 
# open tutorial: Gene Expression Analysis with myTAI
 vignette("Expression", package = "myTAI")
 
 # open tutorial: Taxonomic Information Retrieval with myTAI
 vignette("Taxonomy", package = "myTAI")
 

In the myTAI framework users can find:

Phylotranscriptomics Measures:

• TAI() : Function to compute the Transcriptome Age Index (TAI)
• TDI() : Function to compute the Transcriptome Divergence Index (TDI)
• REMatrix() : Function to compute the relative expression profiles of all phylostrata or divergence-strata
• RE() : Function to transform mean expression levels to relative expression levels
• pTAI() : Compute the Phylostratum Contribution to the global TAI
• pTDI() : Compute the Divergence Stratum Contribution to the global TDI
• pMatrix() : Compute Partial TAI or TDI Values
• pStrata() : Compute Partial Strata Values

Visualization and Analytics Tools:

• PlotPattern() : Function to plot the TAI or TDI profiles and perform statistical tests
• PlotCorrelation() : Function to plot the correlation between phylostratum values and divergence-stratum values
• PlotRE() : Function to plot the relative expression profiles
• PlotBarRE() : Function to plot the mean relative expression levels of phylostratum or divergence-stratum classes as barplot
• PlotMeans() : Function to plot the mean expression profiles of phylostrata or divergence-strata
• PlotDistribution() : Function to plot the frequency distribution of genes within the corresponding phylostratigraphic map or divergence map
• PlotContribution() : Plot the Phylostratum or Divergence Stratum Contribution to the Global TAI/TDI Pattern
• PlotEnrichment() : Plot the Phylostratum or Divergence Stratum Enrichment of a given Gene Set
• PlotGeneSet() : Plot the Expression Profiles of a Gene Set
• PlotCategoryExpr() : Plot the Expression Levels of each Age or Divergence Category as Barplot or Violinplot
• PlotGroupDiffs() : Plot the significant differences between gene expression distributions of PS or DS groups
• PlotSelectedAgeDistr() : Plot the PS or DS distribution of a selected set of genes

A Statistical Framework and Test Statistics:

• FlatLineTest() : Function to perform the Flat Line Test that quantifies the statistical significance of an observed phylotranscriptomics pattern (significant deviation from a frat line = evolutionary signal)
• ReductiveHourglassTest() : Function to perform the Reductive Hourglass Test that statistically evaluates the existence of a phylotranscriptomic hourglass pattern (hourglass model)
• EarlyConservationTest() : Function to perform the Reductive Early Conservation Test that statistically evaluates the existence of a monotonically increasing phylotranscriptomic pattern (early conservation model)
• EnrichmentTest() : Phylostratum or Divergence Stratum Enrichment of a given Gene Set based on Fisher's Test
• bootMatrix() : Compute a Permutation Matrix for Test Statistics

All functions also include visual analytics tools to quantify the goodness of test statistics.

Differential Gene Expression Analysis

• DiffGenes() : Implements Popular Methods for Differential Gene Expression Analysis
• CollapseReplicates() : Combine Replicates in an ExpressionSet
• CombinatorialSignificance() : Compute the Statistical Significance of Each Replicate Combination
• Expressed() : Filter Expression Levels in Gene Expression Matrices (define expressed genes)
• SelectGeneSet() : Select a Subset of Genes in an ExpressionSet
• PlotReplicateQuality() : Plot the Quality of Biological Replicates
• GroupDiffs() : Quantify the significant differences between gene expression distributions of PS or DS groups

Taxonomic Information Retrieval

• taxonomy() : Retrieve Taxonomic Information for any Organism of Interest

Minor Functions for Better Usibility and Additional Analyses

• MatchMap() : Match a Phylostratigraphic Map or Divergence Map with a ExpressionMatrix
• tf() : Transform Gene Expression Levels
• age.apply() : Age Category Specific apply Function
• ecScore() : Compute the Hourglass Score for the EarlyConservationTest
• geom.mean() : Geometric Mean
• harm.mean() : Harmonic Mean
• omitMatrix() : Compute TAI or TDI Profiles Omitting a Given Gene
• rhScore() : Compute the Hourglass Score for the Reductive Hourglass Test

Developer Version of myTAI

The developer version of myTAI might include more functionality than the stable version on CRAN. Hence users can download the current developer version of myTAI by typing:

# The developer version can be installed directly from github:

# install.packages("devtools")

# install developer version of myTAI
library(devtools)
install_github("HajkD/myTAI", build_vignettes = TRUE, dependencies = TRUE)

# On Windows, this won't work - see ?build_github_devtools
# install_github("HajkD/myTAI", build_vignettes = TRUE, dependencies = TRUE)

# When working with Windows, first you need to install the
# R package: rtools -> http://cran.r-project.org/bin/windows/Rtools/
# or consult: http://www.rstudio.com/products/rpackages/devtools/

# Afterwards you can install devtools -> install.packages("devtools")
# and then you can run:

devtools::install_github("HajkD/myTAI", build_vignettes = TRUE, dependencies = TRUE)

# and then call it from the library
library("myTAI", lib.loc = "C:/Program Files/R/R-3.1.1/library")

References

Domazet-Lošo T. and Tautz D. A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature (2010) 468: 815-8.

Quint M, Drost HG, et al. A transcriptomic hourglass in plant embryogenesis. Nature (2012) 490: 98-101.

Drost HG, Gabel A, Grosse I, Quint M. Evidence for Active Maintenance of Phylotranscriptomic Hourglass Patterns in Animal and Plant Embryogenesis. Mol. Biol. Evol. (2015) 32 (5): 1221-1231.

Drost HG, Bellstädt J, Ó'Maoiléidigh DS, Silva AT, Gabel A, Weinholdt C, Ryan PT, Dekkers BJW, Bentsink L, Hilhorst H, Ligterink W, Wellmer F, Grosse I, and Quint M. Post-embryonic hourglass patterns mark ontogenetic transitions in plant development. Mol. Biol. Evol. (2016) doi:10.1093/molbev/msw039

Discussions and Bug Reports

I would be very happy to learn more about potential improvements of the concepts and functions provided in this package.

Furthermore, in case you find some bugs or need additional (more flexible) functionality of parts of this package, please let me know:

https://github.com/HajkD/myTAI/issues

Acknowledgement

I would like to thank several individuals for making this project possible.

First I would like to thank Ivo Grosse and Marcel Quint for providing me a place and the environment to be able to work on fascinating topics of Evo-Devo research and for the fruitful discussions that led to projects like this one.

Furthermore, I would like to thank Alexander Gabel and Jan Grau for valuable discussions on how to improve some methodological concepts of some analyses present in this package.

I would also like to thank Master Students: Sarah Scharfenberg, Anne Hoffmann, and Sebastian Wussow who worked intensively with this package and helped me to improve the usability and logic of the package environment.