Releases: paternogbc/sensiPhy
ON CRAN v.0.8.4
sensiPhy v0.8.4 (10 Dec 2019)
BUG FIXES
- This new version adjusts sensiPhy code for R 4.0.0 release.
In all sensiPhy functions the use of class(.) == was replaced by inherits(., *).
NOTES
- Updated sensiPhy citation reference.
commit b2504ae
sensiPhy v0.8.1 (MEE)
sensiPhy 0.8.1 (MEE)
Version associated with the manuscript accepted in Methods in Ecology and Evolution.
Minor changes:
- Fixed some typos in README file.
- Updated the package description in the help file.
sensiPhy v0.8.1 (ON CRAN)
sensiPhy 0.8.1
Additions:
The vigentee now include two new sections:
- Using sensiPhy to analyse results from other packages
- How long does it take?
Also available at the online tutorial: https://github.com/paternogbc/sensiPhy/wiki
sensiPhy v0.8.0 (ON CRAN)
sensiPhy 0.8.0
Major additions
sensiPhy
now performs sensitivity analysis for a new class of methods which allows users to perform sensitivity analyses of both continuous and discrete (binary) macro-evolutionary models of trait evolution (e.g. Mkn models for binary traits, OU, BM, lambda etc. for continuous traits).
sensiPhy
nor performs sensitivity analysis of phylogenetic uncertainty for simple metrics of diversification and speciation rates (Magallon and Sanderson (2000) method) or speciation rate using bd.km (Kendall-Moran method)
New functions (trait evolution)
Influential species:
-
influ_continuous()
: Performs sensitivity analysis of influential species for
models of trait evolution (continuous characters) -
influ_discrete()
: Performs sensitivity analysis of influential species for
models of trait evolution (binary discrete characters)
Influential clades:
-
clade_continuous()
: Performs sensitivity analysis of influential clades for models of trait evolution (continuous characters) -
clade_discrete()
: Performs sensitivity analysis of influential clades for for
models of trait evolution (binary discrete characters)
Sampling size
-
samp_continuous()
: Performs sensitivity analysis of species sampling for models of trait evolution (continuous characters) -
samp_discrete()
: Performs sensitivity analysis of species sampling for
models of trait evolution (binary discrete characters)
Phylogenetic uncertainty
-
tree_continuous()
: Performs sensitivity analysis of phylogenetic uncertainty for models of trait evolution (continuous characters) -
tree_discrete()
: Performs sensitivity analysis of phylogenetic uncertainty for
models of trait evolution (binary discrete characters)
New functions (diversification rates)
Phylogenetic uncertainty
tree_bd()
: Performs estimates of diversification rate evaluating uncertainty in trees topology.
New functions (Diagnostic plots and stats)
summary()
andsensi_plot
methods were implemented (for all new functions) to provide a quick and intuitive overview of results from sensitivite analysis.
Bug fix
- Corrected progressbar bug when track=FALSE in physig functions
sensiPhy v.07.0 (CRAN )
sensiPhy 0.7.0
Core changes
sensiPhy
now imports the package phytools
Major additions
sensiPhy
now performs sensitivity analysis by interacting two types of uncertainty at the same time (tree and intra against influ, clade and samp methods)sensiPhy
now performs sensitivity analysis for phylogenetic signal
New functions
Phylogenetic signal
influ_physig()
: Performs sensitivity analysis of influential species for phylogenetic signal estimate (k or lambda)clade_physig()
: Performs sensitivity analysis of influential clades for phylogenetic signal estimate (k or lambda)samp_physig()
: Performs sensitivity analysis of influential species for phylogenetic signal estimate (k or lambda)tree_physig()
: Performs sensitivity analysis of phylogenetic signal estimate (k or lambda) accounting for phylogenetic uncertaintyintra_physig()
: Performs sensitivity analysis of phylogenetic signal estimate (k or lambda) accounting for intra-specific variation and measurement errors
Interactions for phylolm models
tree_intra_phylm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and intraspecific variability for phylolm models (linear regression)tree_intra_phyglm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and intraspecific variability for phylolm models (logistic regression)tree_clade_phylm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and sensitivity to species sampling for phylolm models (linear regression)tree_clade_phyglm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and sensitivity to species sampling for phylolm models (logistic regression)tree_influ_phylm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and influential species detection for phylolm models (linear regression)tree_influ_phyglm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and influential species detection for phylolm models (logistic regression)tree_samp_phylm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and sensitivity to species sampling for phylolm models (linear regression)tree_samp_phyglm()
: Performs sensitivity analysis of interaction between phylogenetic uncertainty and sensitivity to species sampling for phylolm models (logistic regression)intra_clade_phylm()
: Performs sensitivity analysis of interaction between intraspecific variability and influential clades for phylolm models (linear regression)intra_clade_phyglm()
: Performs sensitivity analysis of interaction between intraspecific variability and influential clades for phylolm models (logistic regression)intra_influ_phylm()
: Performs sensitivity analysis of interaction between intraspecific variability and influential species detection for phylolm models (linear regression)intra_influ_phyglm()
: Performs sensitivity analysis of interaction between intraspecific variability and influential species detection for phylolm models (logistic regression)intra_samp_phylm()
: Performs sensitivity analysis of interaction between intraspecific variability and species sampling for phylolm models (linear regression)intra_samp_phyglm()
: Performs sensitivity analysis of interaction between intraspecific variability and species sampling for phylolm models (logistic regression)
Improvements
match_data_phy()
now accepts datasets with no information on species names as row names. If the number of species corresponds to the number of tips a warning informs the user that the function assumes that the dataset and the phylogeny are in the same order.
Naming standardization between functions:
- For all
sensiPhy
function the following changes were made:
- slope -> estimate
- DF -> DIF
- model estimates -> sensi.estimates
Bug fix
Tree
methods: Data order was matching order of the first tree of the multiphylo file only. This bug is now fixed. Data and order matching is now done at each iteration.
v0.6.0
sensiPhy 0.6.0
New Functions
miss.phylo.d()
- Calculates phylogenetic signal for missing data (D statistic; Fritz & Purvis 2010).
Missingness is recoded into a binary variable.
Improvements:
- The package now includes a Vignette with a quick introduction to all sensiPhy functions.
clade_phylm()
andclade_phyglm()
now account for clade sample size bias.
This is done by estimating a null distribution of intercepts and slopes considering only
the number of species in the clade.summary()
methods forclade_phylm()
&clade_phyglm()
now includes a randomization test
to account for the number of species in clades (tests if change in model parameters (without the focal clade) is within the null distribution - one-tailed test).sensi_plot()
for clade analysis now include a histogram with the simulated DFslopes (null distribution).sensi_plot()
for influential species analysis (influ_phylm
/influ_phyglm
) now prints the names
of the most influential species on the regression plot.sensi_plot()
now uses font size = 12 for better visualization.- Packages datasets ("primates", "alien") now loads data and phylogeny in independent objects to
faciliate usage in examples.
For CRAN submission
Fixed all bugs and issues before the first submission to CRAN.
v0.3.0
Code ready for CRAN submission.
Missing only examples in help.
v0.2.2
Improve loop optimization.
v0.2.1
Fix bugs related to ggplot2 dev version 1.0.1.9003