Package index • algatr

Genetic data processing

data_processing_packages(): Install data processing packages
gen_to_geno(): Convert dosage matrix or vcf to geno type object (N.B.: this only works for diploids!)
geno_to_dosage(): Convert lfmm/geno matrix to dosage matrix (N.B.: this only works for diploids!)
ld_prune(): ld_prune prunes SNPs based on linkage disequilibrium using SNPRelate and SeqArray packages
simple_impute(): Impute NA values NOTE: use extreme caution when using this form of simplistic imputation. We mainly provide this code for creating test datasets and highly discourage its use in analyses.
str_impute(): Imputation of missing values using population structure inferred with LEA::snmf
vcf_to_dosage(): Convert a vcf to a dosage matrix

envirodata_packages(): Install environmental and geographic data processing packages
check_dists(): Check geographic and environmental distances for collinearity
check_env(): Check environmental layers for collinearity
check_vals(): Check extracted values for collinearity
env_dist(): Calculate distance between environmental vars
geo_dist(): Calculate geographic distance between coordinates
get_worldclim(): Download and merge WorldClim data for study area
rm_islands(): Remove islands from mapping

extrap_mask() range_mask() sd_mask() buffer_mask() chull_mask(): Create raster mask based on coordinates
masking_packages(): Install masking packages

tess_barplot(): Create TESS barplot
tess_col_default(): Create default TESS color palette
tess_do_everything(): TESS function to do everything
tess_ggbarplot(): Create TESS barplot using ggplot2
tess_ggplot(): ggplot of TESS results
tess_krig(): Krige admixture values
tess_ktest(): Test multiple K values
tess_legend(): Create a custom legend for TESS maps
tess_packages(): Install TESS packages
tess_plot_allK(): Plot all kriged Q values for each K
bestK(): Best K Selection based on cross entropy
geom_tess(): Create geom of TESS results that can be added to a ggplot object

mmrr_df(): Make nice dataframe from MMRR results
mmrr_do_everything(): MMRR function to do everything
mmrr_packages(): Install MMRR packages
mmrr_plot(): Plot MMRR results
mmrr_run(): Run MMRR and return model object
mmrr_table(): Create gt table of MMRR results
mmrr_var_sel(): mmrr_var_sel performs MMRR with backward elimination variable selection
MMRR(): MMRR performs Multiple Matrix Regression with Randomization analysis
unfold(): unfold converts the lower diagonal elements of a matrix into a vector

gdm_coeffs(): Get coefficients for each predictor
gdm_df(): Create dataframe of GDM results
gdm_do_everything(): GDM function to do everything (fit model, get coefficients, make and save raster)
gdm_format(): Format Data for Generalized Dissimilarity Modeling (GDM)
gdm_map(): Make map from model
gdm_packages(): Install GDM packages
gdm_plot_diss(): Plot compositional dissimilarity spline plots
gdm_plot_isplines(): Plot I-splines for each variable
gdm_plot_vars(): Create a PCA plot for GDM
gdm_run(): Run GDM and return model object
gdm_table(): Create gt table of GDM results
gdm_var_sel(): Get best set of variables from a GDM model
gdm_varimp_table(): Generate a Variable Importance Table for GDM Models
scale01(): Scale genetic distances from 0 to 1
scaleRGB(): Scale three layers of environmental data to R, G, and B for mapping

rda_cor(): Genotype-environment correlation test
rda_do_everything(): RDA function to do everything
rda_getoutliers(): Get significant outliers from RDA model
rda_packages(): Install RDA packages
rda_plot(): Plot RDA results
rda_run(): Run RDA
rda_table(): Create gt table of RDA results
rda_varpart(): Partial RDA variance partitioning
rda_varpart_table(): Create gt table with RDA variance partitioning results

lfmm_df(): Convert LFMM results into a tidy dataframe for downstream processing
lfmm_do_everything(): LFMM function to do everything
lfmm_manhattanplot(): LFMM Manhattan Plot
lfmm_packages(): Install LFMM packages
lfmm_qqplot(): LFMM QQplot
lfmm_run(): Run LFMM
lfmm_table(): Create gt table of LFMM results
select_K() select_K_tw() select_K_elbow() select_K_tess() select_K_fc(): K selection
quick_elbow(): Quickly choose an elbow for a PC
tw(): Tracy–Widom test

wingen_do_everything(): wingen function to do everything (preview and generate moving window maps, krige, and mask)
wingen_packages(): Install wingen packages

alazygatr_packages(): Install alazygatr packages
do_everything_for_me(): Lazy run of all landscape genomic analyses contained within algatr

load_algatr_example(): Load example data
CA_env: Example environmental data, calculated by performing a raster PCA on 18 bioclimatic variables for state of California
liz_coords: Example coordinates from Bouzid et al. 2022
liz_gendist: Example genetic distance matrix, calculated with Plink using data from Bouzid et al. 2022
liz_vcf: Example VCF from Bouzid et al. 2022

coords_to_sf(): Convert from matrix, data frame, or sf to sf (sf is a pass through)
coords_to_sp(): Convert from matrix, data frame, or sf to formatted sp