We present IMP, an automated pipeline for reproducible integrated analyses of coupled metagenomic and metatranscriptomic data. IMP incorporates preprocessing, iterative co-assembly of metagenomic and metatranscriptomic data, analyses of microbial community structure and function as well as genomic signature-based visualizations. Complementary use of metagenomic and metatranscriptomic data improves assembly quality and enables the estimation of both population abundance and community activity while allowing the recovery and analysis of potentially important components, such as RNA viruses. IMP is containerized using Docker which ensures reproducibility. IMP is available at http://r3lab.uni.lu/web/imp/.
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.