Gene-tree-inference error can cause species-tree-inference artefacts in summary phylogenomic coalescent analyses. Here we integrate two ways of accommodating these inference errors: collapsing arbitrarily or dubiously resolved gene-tree branches, and subsampling gene trees based on their pairwise congruence. We tested the effect of collapsing gene-tree branches with 0% approximate-likelihood-ratio-test (SH-like aLRT) support in likelihood analyses and strict consensus trees for parsimony, and then subsampled those partially resolved trees based on congruence measures that do not penalize polytomies. For this purpose we developed a new TNT script for congruence sorting (congsort), and used it to calculate topological incongruence for eight phylogenomic datasets using three distance measures: standard Robinson-Foulds (RF) distances; overall success of resolution (OSR), which is based on counting both matching and contradicting clades; and RF contradictions, which only counts contradictory clades. As expected, we found that gene-tree incongruence was often concentrated in clades that are arbitrarily or dubiously resolved and that there was greater congruence between the partially collapsed gene trees and the coalescent and concatenation topologies inferred from those genes. Coalescent branch lengths typically increased as the most incongruent gene trees were excluded, although branch supports typically did not. We investigated two successful and complementary approaches to prioritizing genes for investigation of alignment or homology errors. Coalescent-tree clades that contradicted concatenation-tree clades were generally less robust to gene-tree subsampling than congruent clades. Our preferred approach to collapsing likelihood gene-tree clades (0% SH-like aLRT support) and subsampling those trees (OSR) generally outperformed competing approaches for a large fungal dataset with respect to branch lengths, support and congruence. We recommend widespread application of this approach (and strict consensus trees for parsimony-based analyses) for improving quantification of gene-tree congruence/conflict, estimating coalescent branch lengths, testing robustness of coalescent analyses to gene-tree-estimation error, and improving topological robustness of summary coalescent analyses. This approach is quick and easy to implement, even for huge datasets.
Abstract Large-scale selection analyses of protein-coding sequences and phylogenetic tree reconstructions require suitable trees in Newick format. We developed the NewickTreeModifier (NTM), a simple web-based tool to trim and modify Newick trees for such analyses. The users can choose provided master trees or upload a tree to prune it to selected species available in FASTA, NEXUS, or PHYLIP sequence format with an internal converter, a simple species list, or directly determined from a checklist interface of the master trees. Plant, insect, and vertebrate master trees comprise the maximum number of species in an up-to-date phylogenetic order directly transferable to the pruned Newick outfile. NTM is available at https://retrogenomics.uni-muenster.de/tools/ntm.
Specimens form the falsifiable evidence used in plant systematics. Derivatives of specimens (including the specimen as the organism in the field) such as tissue and DNA samples play an increasing role in research. The EDIT Platform for Cybertaxonomy is a specialist's tool that allows to document and sustainably store all data that are used in the taxonomic work process, from field data to DNA sequences. The types of data stored can be very heterogeneous consisting of specimens, images, text data, primary data files, taxon assignments, etc. The EDIT Platform organizes the linking between such data by using a generic data model for representing the research process. Each step in the process is regarded as a derivation step and generates a derivative of the previous step. This could be a field unit having a specimen as its derivative or a specimen having a tissue sample as its derivative. Each derivation step also produces meta data storing who, when and how the derivation was done. The Platform's Common Data Model (CDM) and the applications build on the CDM library thus represent the first comprehensive implementation of the largely theoretical models developed in the late 1990ies (Berendsohn et al. 1999). In a pilot project research data about the genus Campanula (Kilian et al. 2015, FUB, BGBM 2012) was gathered and used to create a hierarchy of derivatives reaching from field data to DNA sequences. Additionally, the open source library for multiple sequence alignments LibrAlign (Stöver and Müller 2015) was used to integrate an alignment editor into the EDIT platform that allows to generate consensus sequences as derivatives of DNA sequences. The persistent storage of each link in the derivation process and the degree of detail on how the data and meta data are stored will speed up the research process, ease the reproducibility of research results and enhance sustainability of collections.
We present the model and implementation of a workflow that blazes a trail in systematic biology for the re-usability of character data (data on any kind of characters of pheno- and genotypes of organisms) and their additivity from specimen to taxon level. We take into account that any taxon characterization is based on a limited set of sampled individuals and characters, and that consequently any new individual and any new character may affect the recognition of biological entities and/or the subsequent delimitation and characterization of a taxon. Taxon concepts thus frequently change during the knowledge generation process in systematic biology. Structured character data are therefore not only needed for the knowledge generation process but also for easily adapting characterizations of taxa. We aim to facilitate the construction and reproducibility of taxon characterizations from structured character data of changing sample sets by establishing a stable and unambiguous association between each sampled individual and the data processed from it. Our workflow implementation uses the European Distributed Institute of Taxonomy Platform, a comprehensive taxonomic data management and publication environment to: (i) establish a reproducible connection between sampled individuals and all samples derived from them; (ii) stably link sample-based character data with the metadata of the respective samples; (iii) record and store structured specimen-based character data in formats allowing data exchange; (iv) reversibly assign sample metadata and character datasets to taxa in an editable classification and display them and (v) organize data exchange via standard exchange formats and enable the link between the character datasets and samples in research collections, ensuring high visibility and instant re-usability of the data. The workflow implemented will contribute to organizing the interface between phylogenetic analysis and revisionary taxonomic or monographic work.
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