IMP: a pipeline for reproducible metagenomic and metatranscriptomic analyses

IMP: a pipeline for reproducible metagenomic and metatranscriptomic analyses

Shaman Narayanasamy, Yohan Jarosz, Emilie E.L. Muller, Cédric C. Laczny, Malte Herold, Anne Kaysen, Anna Heintz-Buschart, Nicolás Pinel, Patrick May, Paul Wilmes

Inferring the frequency spectrum of derived variants to quantify adaptive molecular evolution in protein-coding genes of Drosophila melanogaster

Inferring the frequency spectrum of derived variants to quantify adaptive molecular evolution in protein-coding genes of Drosophila melanogaster

Peter D. Keightley, Jose Campos, Tom Booker, Brian Charlesworth

Efficient analysis of large datasets and sex bias with ADMIXTURE

Efficient analysis of large datasets and sex bias with ADMIXTURE

Suyash S. Shringarpure, Carlos D. Bustamante, Kenneth L. Lange, David H. Alexander

No evidence for the positive relationship between genetic correlations and heritabilities

No evidence for the positive relationship between genetic correlations and heritabilities

Szymon Marian Drobniak, Mariusz Cichoń

Disentangling incomplete lineage sorting and introgression to refine species-tree estimates for Lake Tanganyika cichlid fishes

Disentangling incomplete lineage sorting and introgression to refine species-tree estimates for Lake Tanganyika cichlid fishes

Britta S Meyer, Michael Matschiner, Walter Salzburger

Multi-dimensional structure function relationships in human β-cardiac myosin from population scale genetic variation.

Multi-dimensional structure function relationships in human β-cardiac myosin from population scale genetic variation.

Julian R Homburger, Eric M Green, Colleen Caleshu, Margaret Sunitha, Rebecca Taylor, Kathleen M Ruppel, Raghu Metpally, SHaRe Investigators, Steven D Colan, Michelle Michels, Sharlene Day, Iacopo Olivotto, Carlos D Bustamante, Frederick Dewey, Carolyn Ho, James A Spudich, Euan A Ashley

Combinatorial Scoring of Phylogenetic Networks

Combinatorial Scoring of Phylogenetic Networks
Nikita Alexeev, Max A. Alekseyev

Construction of phylogenetic trees and networks for extant species from their characters represents one of the key problems in phylogenomics. While solution to this problem is not always uniquely defined and there exist multiple methods for tree/network construction, it becomes important to measure how well constructed networks capture the given character relationship across the species.
In the current study, we propose a novel method for measuring the specificity of a given phylogenetic network in terms of the total number of distributions of character states at the leaves that the network may impose. While for binary phylogenetic trees, this number has an exact formula and depends only on the number of leaves and character states but not on the tree topology, the situation is much more complicated for non-binary trees or networks. Nevertheless, we develop an algorithm for combinatorial enumeration of such distributions, which is applicable for arbitrary trees and networks under some reasonable assumptions.