A generic bioinformatics pipeline to integrate large-scale trait data with large phylogenies

Pasan C Fernando; Laura M Jackson; Erliang Zeng; Paula M Mabee; James P Balhoff

doi:10.1109/BIBM.2017.8218008

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Conference proceeding

A generic bioinformatics pipeline to integrate large-scale trait data with large phylogenies

Pasan C Fernando, Laura M Jackson, Erliang Zeng, Paula M Mabee and James P Balhoff

2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Vol.2017-, pp.2235-2237

11/2017

DOI: 10.1109/BIBM.2017.8218008

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Abstract

Ancestral state reconstructions are used to infer the evolutionary history of phenotypic traits to understand their evolution. Current ancestral state reconstructions require integration of larger trait matrices with larger phylogenies, which introduces several challenges. We identified these challenges and developed a generic pipeline that uses the Phenoscape Knowledgebase (Phenoscape KB) to retrieve raw trait matrices and convert them to an efficient version that can be easily integrated with large phylogenies downloaded from the Open Tree of Life (Open Tree). We demonstrate the performance of this pipeline using the evolution of the pectoral and pelvic fins as the use case, which involves integration of a large-scale phylogeny containing over 38,000 taxa.

Evolution

pipeline

Ancestral state reconstruction

phylogenetic trees

phenotypes

Pipelines

Vegetation

Ontologies

Cognition

trait matrix

Phylogeny

Matrix converters

Details

Title: Subtitle: A generic bioinformatics pipeline to integrate large-scale trait data with large phylogenies
Creators: Pasan C Fernando - Biol. Dept., Univ. of South Dakota, Vermillion, SD, USA
Laura M Jackson - University of Northern Iowa
Erliang Zeng - University of Iowa, Dental Research
Paula M Mabee - Biol. Dept., Univ. of South Dakota, Vermillion, SD, USA
James P Balhoff - Renaissance Comput. Inst., Univ. of North Carolina, Chapel Hill, NC, USA
Resource Type: Conference proceeding
Publication Details: 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Vol.2017-, pp.2235-2237
DOI: 10.1109/BIBM.2017.8218008
Publisher: IEEE
Language: English
Date published: 11/2017
Academic Unit: Preventive and Community Dentistry; Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute; Biostatistics; Dental Research
Record Identifier: 9984071900102771

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