geoGraph: using spherical grids to walk through the geographic space | First steps | Installing the package | Data representation | gGraph objects | gData objects | Getting started with geoGraph | Importing geographic data | Finding least-cost paths | Changing local properties of a gGraph | Example application using the Human Genome Diversity Panel

SDMs with tidymodels | Accessing the data for this vignette: how to use rgbif | Preparing your data | Map projection | Thinning step | Fit the model by cross-validation | Projecting to the present | Projecting to the future | Dealing with extrapolation | Visualising the contribution of individual variables | Repeated ensembles

Quality control for SNP datasets | Read data into gen_tibble format | Quality control for individuals | Quality control for loci | Linkage Disequilibrium | Save | Grouping data | Grouped functions

Installation | An overview of CRS codes | Spatial objects in R | Choosing a CRS

Using multi-level factors as predictors | Exploring models with DALEX | Different recipes for certain models | The initial split | Stack ensembles

Tidy data in population genetics | The gen_tibble | Standard dplyr verbs to manipulate the tibble | Using verbs on loci | Grouping individuals in populations | Functions applying to all pairwise and nwise combinations of individuals or populations | Reading data | Merging data | Imputation | Saving data and updating backingfiles | Ordering loci

Creating a gen_tibble | Quality control | Impute | PCA | Plot with ggplot2

An example workflow with real data | Map | PCA | Explore population structure with DAPC | Clustering with ADMIXTURE | Handling Q matrices

File management and reading data: | Quality control: | Handling linkage | Quality control for relatedness (KING) | Merging datasets: | Analysis:

NAs in the data | Recipes and the response variable | Using the desired formula with GAM | When only some splits fail

SDMs with tidymodels for palaeo data | Preparing your data | Fit the model by crossvalidation | Projecting to other times

Overview of datasets available in pastclim

Downscaling | Delta downscaling a dataset in pastclim | An example for one variable | Computing the bioclim variables

Install the library | Download the data | Get climate for locations | Get climate for a region | Cropping | Working with biomes and ice sheets | Adding locations to region plots | Set the samples within the background | Random sampling of background | Downscaling

Present reconstructions | WorldClim | CHELSA | Future projections

Formatting a custom dataset for pastclim | An example: the Trace21k-CHELSEA | Making the data available to others