---
title: "deepSTRAPP: All tutorials"
author: "Maël Doré"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{deepSTRAPP: All tutorials}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r set_options, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## 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](https://maeldore.github.io/deepSTRAPP/articles/main_tutorial.html) and within R: `vignette("main_tutorial")`.

This tutorial presents the main functions in a typical **deepSTRAPP workflow**. <br>
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**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [1.1/ Full deepSTRAPP workflow for __continuous__ trait data](https://maeldore.github.io/deepSTRAPP/articles/deepSTRAPP_continuous_data.html): `vignette("deepSTRAPP_continuous_data")`.

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [1.2/ Full deepSTRAPP workflow for __categorical__ trait data with 3-levels](https://maeldore.github.io/deepSTRAPP/articles/deepSTRAPP_categorical_data.html): `vignette("deepSTRAPP_categorical_data")`.

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [1.3/ Full deepSTRAPP workflow for __biogeographic__ range data](https://maeldore.github.io/deepSTRAPP/articles/deepSTRAPP_biogeographic_data.html): `vignette("deepSTRAPP_biogeographic_data")`.

### **2/ Explore options for trait evolution**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [2.1/ Model evolution of __continuous__ trait data](https://maeldore.github.io/deepSTRAPP/articles/model_continuous_trait_evolution.html): `vignette("model_continuous_trait_evolution")`.

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [2.2/ Model evolution of __categorical__ trait data](https://maeldore.github.io/deepSTRAPP/articles/model_categorical_trait_evolution.html): `vignette("model_categorical_trait_evolution")`.

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [2.3/ Model evolution of __biogeographic__ range data](https://maeldore.github.io/deepSTRAPP/articles/model_biogeographic_range_evolution.html): `vignette("model_biogeographic_range_evolution")`.

### **3/ Explore options for BAMM**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Model __diversification dynamics__ with BAMM within deepSTRAPP](https://maeldore.github.io/deepSTRAPP/articles/model_diversification_dynamics.html): `vignette("model_diversification_dynamics")`.

### **4/ Explore the STRAPP test options**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Test different hypotheses](https://maeldore.github.io/deepSTRAPP/articles/explore_STRAPP_test_types.html): `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)**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Explore options for plotting diversification __rates through time__ in relation to trait data](https://maeldore.github.io/deepSTRAPP/articles/plot_rates_through_time.html): `vignette("plot_rates_through_time")`.

### **6/ Handle uncertainty**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Handle __uncertainty__ in trait and rate estimates](https://maeldore.github.io/deepSTRAPP/articles/handle_uncertainty.html): `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.
<br>

### **7/ Import external analyses**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Import __external analyses__](https://maeldore.github.io/deepSTRAPP/articles/import_external_analyses.html): `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.
<br>

### **8/ Cut phylogenies**

&nbsp;&nbsp;&nbsp;&nbsp;&#x25CF;&nbsp;&nbsp; [Cut different types of __(mapped) phylogenies__ for a given focal-time](https://maeldore.github.io/deepSTRAPP/articles/cut_phylogenies.html): `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.
<br>