PhyInformR
This is a walkthrough of PhyInformR broken into three main sections
As we aggregate genome scale sequence datasets, disentangling signal from noise is critical to mitigating erroneous inferences
Investigating 'cold cases' of relationships based on sanger-sequence can also overturn our perception of support for certain classic hypotheses
PhyInformR is designed to help you investigate your data and solve cases of incongruence
Installation and Phylogenetic Informativeness Profiles
Learn to install phyinformr and use PI profiles for predicting trends in a dataset
These profiles are of particular relevance for mitigating against homoplasy driven errors in a divergence time studies
Quantification of Signal and Noise
Loci vary in information, presenting an informatic problem of how to target loci for analyses to efficiently improve phylogenetic accuracy by minimizing homoplasy
Here we cover methods for disentangling sources of error that HGT, at worst, can yield strong, but erroneous, support for focal nodes
Advanced visualizations
The quantitative framework of quartet internode calculations lends itself wonderfully to the development of new ways to visualize information in a given dataset. This section highlights graphics from a few recent publications
We hope users fully harness R's potential for innovative new visualization and develop novel approaches that will enable both scrutiny and discovery of patterns within genome-scale data.
Download pdf
A pdf of this manual is available. Please note that some advanced features in the web instructions may be missing depending on our update schedule.