Authors:
Fernando Izquierdo-Carrasco
1
;
Julien Gagneur
2
and
Alexandros Stamatakis
1
Affiliations:
1
The Exelixis Lab and Scientific Computing Group, Germany
;
2
European Molecular Biology Laboratory, Germany
Keyword(s):
Memory versus runtime trade-offs, Phylogenetic likelihood function, RAxML.
Related
Ontology
Subjects/Areas/Topics:
Algorithms and Software Tools
;
Bioinformatics
;
Biomedical Engineering
Abstract:
The revolution in wet-lab sequencing techniques that has given rise to a plethora of whole-genome or wholetranscriptome
sequencing projects, often targeting 50 up to 1000 species, poses new challenges for efficiently
computing the phylogenetic likelihood function both for phylogenetic inference and statistical post-analysis
purposes. The phylogenetic likelihood function as deployed in maximum likelihood and Bayesian inference
programs consumes the vast majority of computational resources, that is, memory and CPU time. Here, we
introduce and implement a novel, general, and versatile concept to trade additional computations for memory
consumption in the likelihood function which exhibits a surprisingly small impact on overall execution times.
When trading 50% of the required RAM for additional computations, the average execution time increase
because of additional computations amounts to only 15%. We demonstrate that, for a phylogeny with n
species only log(n)+2 memory space is require
d for computing the likelihood. This is a promising result
given the exponential growth of molecular datasets.
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