Detect and Remove Outliers in Phylogenomics Datasets
Detection of outliers in 1D and 2D data
Compute gene x species matrix from the result of Distatis
Fast implementation the multivariate analysis method Distatis
Imputation of missing values in a collection of matrices
A robust measure of skewness for univariate data
Median normalization of 2D matrix by row or by colomn
Filter phylogenomics datasets
Plot phylter objects
Prepare data for phylter analysis
Print phylter objects
print objects of class phylterfinal
print objects of class phylterinitial
print summary of phylter objects
Name or rename a list of gene trees or matrices
Simplistic simulation of gene trees with outliers
Get summary for phylter objects
Convert phylogenetic trees to distance matrices
Write summary of phyter analysis to file(s)
Analyzis and filtering of phylogenomics datasets. It takes an input either a collection of gene trees (then transformed to matrices) or directly a collection of gene matrices and performs an iterative process to identify what species in what genes are outliers, and whose elimination significantly improves the concordance between the input matrices. The methods builds upon the Distatis approach (Abdi et al. (2005) <doi:10.1101/2021.09.08.459421>), a generalization of classical multidimensional scaling to multiple distance matrices.
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