Online tutorial

Gijsbert Werner edited this page Jan 23, 2018 · 12 revisions

Introduction to sensiPhy

The sensiPhy package provides simple functions to perform sensitivity analyses in phylogenetic comparative methods. It uses several simulation methods to estimate the impact of different types of uncertainty on Phylogenetic comparative methods:

(i) Species Sampling uncertainty (sample size; influential species and clades)
(ii) Phylogenetic uncertainty
(iii) Data uncertainty (intraspecific variation and measurement error)

Functions for sensitivity analysis

sensiPhy functions use a common syntax that combines the type of uncertainty and the type of analysis:

  • xxx_phylm (for linear regressions)
  • xxx_phyglm (for logistic regressions)
  • xxx_physig (for phylogenetic signal)
  • xxx_continuous (for continuous trait evolution)
  • xxx_discrete (for discrete trait evolution)

where "xxx" can be one of the 5 sensiPhy methods (see Figure below):

  • Species sampling uncertainty: influ; clade; samp;
  • Phylogenetic uncertainty: tree
  • Data uncertainty: intra

sensiPhy workflow & functions

figure 1

Additional functions

Function Description
match_dataphy Match data and phylogeny based on model formula
miss.phylo.d Calculates the phylogenetic signal for missing data Tree diversification and speciation with phylogenetic uncertainty

Get started:

The following links provide a quick tutorial to sensiPhy functions and their basic usage.

Useful information:

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