Main tutorial
Quick-to-run example
A simple use-case that shows how deepSTRAPP can be
used to test for differences in diversification rates between
two trait states along evolutionary times is available here
and within R: vignette("main_tutorial").
This tutorial presents the main functions in a typical
deepSTRAPP workflow.
For more advanced uses,
please refer to the vignettes/tutorials below.
Advanced uses / tutorials
This vignette points to tutorials detailing how to
use the [deepSTRAPP] package beyond the simple use-case
presented in the README file and also available here:
vignette("main_tutorial").
The following tutorials present more advanced usages of deepSTRAPP. They provide explanations on available arguments and interpretations of results of deepSTRAPP across multiple types of data.
1/ Full deepSTRAPP workflows on different types of data
● 1.1/
Full deepSTRAPP workflow for continuous trait data:
vignette("deepSTRAPP_continuous_data").
● 1.2/
Full deepSTRAPP workflow for categorical trait data
with 3-levels:
vignette("deepSTRAPP_categorical_data").
● 1.3/
Full deepSTRAPP workflow for biogeographic range
data: vignette("deepSTRAPP_biogeographic_data").
2/ Explore options for trait evolution
● 2.1/
Model evolution of continuous trait data:
vignette("model_continuous_trait_evolution").
● 2.2/
Model evolution of categorical trait data:
vignette("model_categorical_trait_evolution").
● 2.3/
Model evolution of biogeographic range data:
vignette("model_biogeographic_range_evolution").
3/ Explore options for BAMM
● Model
diversification dynamics with BAMM within
deepSTRAPP:
vignette("model_diversification_dynamics").
4/ Explore the STRAPP test options
● Test
different hypotheses:
vignette("explore_STRAPP_test_types").
- Type of STRAPP tests: two-tailed vs. one-tailed.
- Continuous: “negative” or “positive” correlation.
- Binary with hypothesis: (A > B) vs. (B > A).
- Multinominal: Hypotheses for all post hoc tests.
5/ Plot rates through time (RTT)
● Explore
options for plotting diversification rates through time
in relation to trait data:
vignette("plot_rates_through_time").
6/ Handle uncertainty
● Handle
uncertainty in trait and rate estimates:
vignette("handle_uncertainty").
Explore the three strategies available: - ‘rates_only’: Only accounts
for diversification-rate uncertainty across BAMM posterior samples. -
‘paired’: Accounts for both diversification-rate and ancestral
trait/range reconstruction uncertainty by pairing BAMM posterior samples
with stochastic maps. - ‘full’: Accounts for both diversification-rate
and ancestral reconstruction uncertainty by evaluating every combination
of BAMM posterior samples and stochastic maps.
7/ Import external analyses
● Import
external analyses:
vignette("import_external_analyses").
Import and format results of external analyses of trait-evolution
histories and diversification dynamics, and make them ready-to-use as
inputs for a deepSTRAPP run.
8/ Cut phylogenies
● Cut
different types of (mapped) phylogenies for a given
focal-time: vignette("cut_phylogenies").
- time-calibrated phylogenies.
- contMap(s) for continuous traits.
- densityMap(s) for categorical and biogeographic traits.
- simmaps for categorical and biogeographic traits.
- BAMM_object for diversification dynamics.