Run deepSTRAPP to test for a relationship between diversification rates and trait data at a given focal time

Wrapper function to run deepSTRAPP workflow for a given point in the past (i.e. the focal_time). It starts from traits mapped on a phylogeny (trait data) and BAMM output (diversification data) and carries out the appropriate statistical method to test for a relationship between diversification rates and trait data. Tests are based on block-permutations: rates data are randomized across tips following blocks defined by the diversification regimes identified on each tip (typically from a BAMM).

Such tests are called STructured RAte Permutations on Phylogenies (STRAPP) as described in Rabosky, D. L., & Huang, H. (2016). A robust semi-parametric test for detecting trait-dependent diversification. Systematic biology, 65(2), 181-193. https://doi.org/10.1093/sysbio/syv066.

See the original BAMMtools::traitDependentBAMM() function used to carry out STRAPP test on extant time-calibrated phylogenies.

Tests can be carried out on speciation, extinction and net diversification rates.

Usage

run_deepSTRAPP_for_focal_time(
  contMap = NULL,
  densityMaps = NULL,
  ace = NULL,
  tip_data = NULL,
  trait_data_type,
  BAMM_object,
  focal_time,
  keep_tip_labels = TRUE,
  rate_type = "net_diversification",
  seed = NULL,
  nb_permutations = NULL,
  replace_samples = FALSE,
  alpha = 0.05,
  two_tailed = TRUE,
  one_tailed_hypothesis = NULL,
  posthoc_pairwise_tests = FALSE,
  p.adjust_method = "none",
  return_perm_data = FALSE,
  nthreads = 1,
  print_hypothesis = TRUE,
  extract_diversification_data_melted_df = FALSE,
  return_updated_trait_data_with_Map = FALSE,
  return_updated_BAMM_object = FALSE,
  verbose = TRUE
)

Arguments

contMap

For continuous trait data. Object of class "contMap", typically generated with prepare_trait_data() or phytools::contMap(), that contains a phylogenetic tree and associated continuous trait mapping. The phylogenetic tree must be rooted and fully resolved/dichotomous, but it does not need to be ultrametric (it can includes fossils).

densityMaps

For categorical trait or biogeographic data. List of objects of class "densityMap", typically generated with prepare_trait_data(), that contains a phylogenetic tree and associated posterior probability of being in a given state/range along branches. Each object (i.e., densityMap) corresponds to a state/range. The phylogenetic tree must be rooted and fully resolved/dichotomous, but it does not need to be ultrametric (it can includes fossils).

ace

(Optional) Ancestral Character Estimates (ACE) at the internal nodes. Obtained with prepare_trait_data() as output in the $ace slot.

For continuous trait data: Named numerical vector typically generated with phytools::fastAnc(), phytools::anc.ML(), or ape::ace(). Names are nodes_ID of the internal nodes. Values are ACE of the trait.
For categorical trait or biogeographic data: Matrix that record the posterior probabilities of ancestral states/ranges. Rows are internal nodes_ID. Columns are states/ranges. Values are posterior probabilities of each state per node. Needed in all cases to provide accurate estimates of trait values.

tip_data

(Optional) Named vector of tip values of the trait.

For continuous trait data: Named numerical vector of trait values.
For categorical trait or biogeographic data: Character string vector of states/ranges Names are nodes_ID of the internal nodes. Needed to provide accurate tip values.
For biogeographic data, ranges should follow the coding scheme of BioGeoBEARS with a unique CAPITAL letter per unique areas (ex: A, B), combined to form multi-area ranges (Ex: AB). Alternatively, you can provide tip_data as a matrix or data.frame of binary presence/absence in each area (coded as unique CAPITAL letter). In this case, columns are unique areas, rows are taxa, and values are integer (0/1) signaling absence or presence of the taxa in the area.

trait_data_type

Character string. Specify the type of trait data. Must be one of "continuous", "categorical", "biogeographic".

BAMM_object

Object of class "bammdata", typically generated with prepare_diversification_data(), that contains a phylogenetic tree and associated diversification rate mapping across selected posterior samples. The phylogenetic tree must the same as the one associated with the contMap/densityMaps, ace and tip_data.

focal_time

Numerical. The time, in terms of time distance from the present, at which data must be extracted and the phylogeny and mappings must be cut. It must be smaller than the root age of the phylogeny.

keep_tip_labels

Logical. Specify whether terminal branches with a single descendant tip must retained their initial tip.label on the updated phylogeny. Default is TRUE.

rate_type

A character string specifying the type of diversification rates to use. Must be one of 'speciation', 'extinction' or 'net_diversification' (default).

seed

Integer. Set the seed to ensure reproducibility. Default is NULL (a random seed is used).

nb_permutations

Integer. To select the number of random permutations to perform during the tests. If NULL (default), all posterior samples will be used once.

replace_samples

Logical. To specify whether to allow 'replacement' (i.e., multiple use) of a posterior sample when drawing samples used to carry out the STRAPP test. Default is FALSE.

alpha

Numerical. Significance level to use to compute the estimate corresponding to the values of the test statistic used to assess significance of the test. This does NOT affect p-values. Default is 0.05.

two_tailed

Logical. To define the type of tests. If TRUE (default), tests for correlations/differences in rates will be carried out with a null hypothesis that rates are not correlated with trait values (continuous data) or equals between trait states (categorical and biogeographic data). If FALSE, one-tailed tests are carried out.

For continuous data, it involves defining a one_tailed_hypothesis testing for either a "positive" or "negative" correlation under the alternative hypothesis.
For binary data (two states), it involves defining a one_tailed_hypothesis indicating which states have higher rates under the alternative hypothesis.
For multinominal data (more than two states), it defines the type of post hoc pairwise tests to carry out between pairs of states. If posthoc_pairwise_tests = TRUE, all two-tailed (if two_tailed = TRUE) or one-tailed (if two_tailed = FALSE) tests are automatically carried out.

one_tailed_hypothesis

A character string specifying the alternative hypothesis in the one-tailed test. For continuous data, it is either "negative" or "positive" correlation. For binary data, it lists the trait states with states ordered in increasing rates under the alternative hypothesis, separated by a greater-than such as c('A > B').

posthoc_pairwise_tests

Logical. Only for multinominal data (with more than two states). If TRUE, all possible post hoc pairwise (Dunn) tests will be computed across all pairs of states. This is a way to detect which pairs of states have significant differences in rates if the overall test (Kruskal-Wallis) is significant. Default is FALSE.

p.adjust_method

A character string. Only for multinominal data (with more than two states). It specifies the type of correction to apply to the p-values in the post hoc pairwise tests to account for multiple comparisons. See stats::p.adjust() for the available methods. Default is none.

return_perm_data

Logical. Whether to return the stats data computed from the posterior samples for observed and permuted data in the output. This is needed to plot the histogram of the null distribution used to assess significance of the test with plot_histogram_STRAPP_test_for_focal_time(). Default is FALSE.

nthreads

Integer. Number of threads to use for paralleled computing of the STRAPP tests across the permutations. The R package parallel must be loaded for nthreads > 1. Default is 1.

print_hypothesis

Logical. Whether to print information on what test is carried out, detailing the null and alternative hypotheses, and what significant level is used to rejected or not the null hypothesis. Default is TRUE.

extract_diversification_data_melted_df

Logical. Specify whether diversification data (regimes ID and tip rates) must be extracted from the updated_BAMM_object and returned in a melted data.frame. Default is FALSE.

return_updated_trait_data_with_Map

Logical. Specify whether the trait_data extracted for the given focal_time and the updated version of mapped phylogeny (contMap/densityMaps) provided as input should be returned among the outputs. The updated contMap/densityMaps consists in cutting off branches and mapping that are younger than the focal_time. Default is FALSE.

return_updated_BAMM_object

Logical. Specify whether the updated_BAMM_object with phylogeny and mapped diversification rates cut-off at the focal_time should be returned among the outputs.

verbose

Logical. Should progression be displayed? A message will be printed at each stepof the deepSTRAPP workflow, and for every batch of 100 BAMM posterior samples whose rates are regimes are updated, and optionally extracted in a melted data.frame (if extract_diversification_data_melted_df = TRUE). Default is TRUE.

Value

The function returns a list with at least two elements.

$STRAPP_results List with at least eight elements summarizing the results of the STRAPP tests. See compute_STRAPP_test_for_focal_time() for a detailed description of the output.
$focal_time Integer. The time, in terms of time distance from the present, at which the data were extracted and the STRAPP test carried out.

Optional formatted output:

$diversification_data_df A data.frame with six columns summarizing the diversification data as found on the phylogeny for the focal_time. See extract_diversification_data_melted_df_for_focal_time() for a detailed description of the output.

Optional data updated for the focal_time:

$updated_trait_data_with_Map A list with four elements that contains trait data found at the focal_time and an updated contMap or densityMaps that can be used as input of plot_contMap() or plot_densityMaps_overlay() to display a phylogeny mapped with trait values/states/ranges with branches cut at the focal_time. See extract_most_likely_trait_values_for_focal_time() for a detailed description of the output.
$updated_BAMM_object An updated BAMM_object of class "bammdata" that contains rates and regimes ID found at the focal_time. Can be used as input of plot_BAMM_rates() to display a phylogeny mapped with diversification rates with branches cut at the focal_time. See update_rates_and_regimes_for_focal_time() for a detailed description of the output.

Details

The function encapsulates several functions carrying out each step of the deepSTRAPP workflow:

Extract trait data

extract_most_likely_trait_values_for_focal_time() extracts the most likely trait values found along branches at the focal_time. Optionally, the function can update the mapped phylogeny (contMap/densityMaps) such as branches overlapping the focal_time are shorten to the focal_time, and the trait mapping for the cut off branches are removed by updating the $tree$maps and $tree$mapped.edge elements.

Extract diversification data

update_rates_and_regimes_for_focal_time() updates the BAMM_object to obtain the diversification rates/regimes found along branches the focal_time. Optionally, the function can update the BAMM_object to display a mapped phylogeny such as branches overlapping the focal_time are shorten to the focal_time

Extract diversification data in a melted df

If requested (extract_diversification_data_melted_df = TRUE), extract_diversification_data_melted_df_for_focal_time() will be used to extract regimes ID and tip rates from the updated_BAMM_object and provide a melted data.frame summarizing the diversification data as found on the phylogeny for the focal_time.

Compute STRAPP test

compute_STRAPP_test_for_focal_time() carries out the appropriate statistical method to test for a relationship between diversification rates and trait data for a given point in the past (i.e. the focal_time). It can handle three types of statistical tests depending on the type of trait data provided:

Continuous trait data: Test for correlations with the Spearman's rank correlation test (See stats::cor.test).
Binary trait data (two states): Test for differences in rates between states with the Mann-Whitney-Wilcoxon rank-sum test (See stats::wilcox.test).
Multinominal trait data (More than two states): Test for differences in rates across all states with the Kruskal-Wallis H test (See stats::kruskal.test). If posthoc_pairwise_tests = TRUE, Dunn's post hoc pairwise rank-sum tests between pairs of states will be carried out too (See dunn.test::dunn.test).

Author

Maël Doré