| Abstract Detail
Phylogenomics Kandziora, Martha [1], McTavish, Emily Jane [2]. Physcraper: automatic updating of phylogenies. The rate of DNA sequencing has outpaced the ability of researchers to analyze sequence data. This means that many species are not included in any published phylogeny, despite available sequence data. There is an opportunity to provide active, automated extension of the tree of life with new inferences made directly from sequence data. We have developed a software pipeline, physcraper, to add these new taxa into existing trees.
Physcraper automates the updating of phylogenetic relationships by placing new sequences based on similarity to existing sequences in the alignment and builds a starting tree including the new sequences. The use of a starting tree decreases the time to calculate a new tree. Physcraper generates new, integrated, maximum likelihood estimates of species relationships, with minimal researcher time and effort. The advantage is, that the method rapidly computes a new phylogeny including support values for large scale phylogenies which then can be used for further analyses without losing accuracy. We will present the workflow in more detail and show the ability of the method to rapidly update phylogenies on an Asteraceae sublineage example, Senecioneae, and show how it decreases the computational time considerably in comparison to calculating a new phylogeny from scratch.
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1 - University of California, Merced, Life and Environmental Science, Merced, CA, 95340, USA
2 - University of California, Merced, Life and Environmental Science, Merced, 95340, USA
Keywords:
Phylogenetics
workflow
automatic updating
python
Senecioneae
Asteraceae.
Presentation Type: Poster
Session: P, Phylogenomics
Location: Grand Ballroom - Exhibit Hall/Mayo Civic Center
Date: Monday, July 23rd, 2018
Time: 5:30 PM This poster will be presented at 6:15 pm. The Poster Session runs from 5:30 pm to 7:00 pm. Posters with odd poster numbers are presented at 5:30 pm, and posters with even poster numbers are presented at 6:15 pm.
Number: PPH002
Abstract ID:260
Candidate for Awards:None |
