| Abstract Detail
Phylogenomics Rusinko, Joseph [1], Yu, Cai [2], Allison, Doherty [3], Katherine, Thompson [4], Boutte, Julien [5], Fishbein, Mark [6], Straub, Shannon [7]. PickMe! A coalescent-based tool for taxa selection for phylogenomics. PickMe! is a new software tool designed to help phylogenomics researchers make informed decisions about which taxa to include in a species tree analysis. Researchers first estimate gene trees using all of the available genes and samples. These initial gene trees are input into PickMe! which outputs a set of the taxa which the data support as coming from a single species tree. This procedure relies on coalescent weights to individual quartet topologies based on the likelihood that the true species tree displays these quartets. Researchers are advised to reanalyze their data using their preferred species tree reconstruction pipeline using only these recommended taxa.
PickMe! is applied to 703 nuclear gene trees inferred from a targeted sequence data set in milkweeds (Apocynaceae, Asclepias), where it reveals that far more taxa could reliably be included in the analysis than the authors previously included based on an ad hoc gene occupancy criterion instead of a formal decision-making tool. We discuss both the details of this process and the implications on our understanding of milkweed evolution.
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1 - Hobart and William Smith Colleges, Mathematics and Computer Science, Geneva, NY, 14456
2 - N/A, N/A, N/A, N/A, N/A
3 - SRC Inc., Syracuse, NY, USA
4 - University of Kentucky, Statistics, Lexington , KY, USA
5 - Julien Boutte A2Bio2, France
6 - Oklahoma State University, Dept Of Plant Biology, Ecology & Evolution, 301 Physical Science, Stillwater, OK, 74078, United States
7 - Hobart and William Smith Colleges, Department of Biology, 300 Pulteney Street, Geneva, NY, 14456, USA
Keywords:
taxa selection
milkweed
species tree.
Presentation Type: Oral Paper
Session: PHYLOV, Phylogenomics V
Location: Virtual/Virtual
Date: Friday, July 23rd, 2021
Time: 3:30 PM(EDT)
Number: PHYLOV003
Abstract ID:919
Candidate for Awards:None |
