ORCID Profile
0000-0003-4719-7472
Current Organisation
University of Tokyo
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Publisher: Cold Spring Harbor Laboratory
Date: 07-10-2022
DOI: 10.1101/2022.10.06.511072
Abstract: Bio ersity has typically been quantified using species richness, but this ignores evolutionary history. Due to the increasing availability of robust phylogenies, methods have been developed that incorporate phylogenetic relationships into quantification of bio ersity. CANAPE (categorical analysis of neo- and paleo-endemism) is one such method that can provide insight into the evolutionary processes generating bio ersity. The only currently available software implementing CANAPE is Bio erse, which is written in Perl and can be used either through a graphical user interface (GUI) or user-developed scripts. However, many researchers, particularly in the fields of ecology and evolutionary biology, use the R programming language to conduct their analyses. Here, we present canaper , a new R package that provides functions to conduct CANAPE in R. canaper implements methods for efficient computation, including parallelization and encoding of community data as sparse matrices. The interface is designed for maximum simplicity and reproducibility CANAPE can be conducted with two functions, and parallel computing can be enabled with one line of code. Our case study shows that canaper produces equivalent results to Bio erse and can complete computations on moderately sized datasets quickly ( 10 min to reproduce a canonical study). canaper allows researchers to conduct all analyses from data import and cleaning through CANAPE within R, thereby averting the need to manually import and export data and analysis results between programs. We anticipate canaper will become a part of the toolkit for analyzing bio ersity in R.
Publisher: Wiley
Date: 18-07-2023
DOI: 10.1111/ECOG.06638
Abstract: Bio ersity has typically been quantified using species richness, but this ignores evolutionary history. Due to the increasing availability of robust phylogenies, methods have been developed that incorporate phylogenetic relationships into quantification of bio ersity. CANAPE (categorical analysis of neo‐ and paleo‐endemism) is one such method that can provide insight into the evolutionary processes generating bio ersity. The only currently available software implementing CANAPE is Bio erse, which is written in Perl and can be used either through a graphical user interface (GUI) or user‐developed scripts. However, many researchers, particularly in the fields of ecology and evolutionary biology, use the R programming language to conduct their analyses. Here, we present canaper, a new R package ( www.r‐project.org ) that provides functions to conduct CANAPE in R. canaper implements methods for efficient computation, including parallelization and encoding of community data as sparse matrices. The interface is designed for maximum simplicity and reproducibility CANAPE can be conducted with two functions, and parallel computing can be enabled with one line of code. Our case study shows that canaper produces equivalent results to Bio erse and can complete computations on moderately sized datasets quickly ( min to reproduce a canonical study). canaper allows researchers to conduct all analyses from data import and cleaning through CANAPE within R, thereby obviating the need to manually import and export data and analysis results between programs. We anticipate canaper will become a part of the toolkit for analyzing bio ersity in R.
Location: United States of America
No related grants have been discovered for Joel Nitta.