Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes

George Armstrong, Kalen Cantrell, Shi Huang, Daniel McDonald, Niina Haiminen, Anna Paola Carrieri, Qiyun Zhu, Antonio Gonzalez, Imran McGrath, Kristen L. Beck, Daniel Hakim, Aki S. Havulinna, Guillaume Méric, Teemu Niiranen, Leo Lahti, Veikko Salomaa, Mohit Jain, Michael Inouye, Austin D. Swafford, Ho Cheol KimLaxmi Parida, Yoshiki Vázquez-Baeza, Rob Knight

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

Original languageEnglish (US)
Pages (from-to)2131-2137
Number of pages7
JournalGenome research
Volume31
Issue number11
DOIs
StatePublished - Nov 1 2021
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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