Package index • tidypopgen

`gen_tibble`

Functions for creating, saving, and loading gen_tibble objects.

gen_tibble(): Constructor for a gen_tibble

gt_save(): Save a gen_tibble

gt_load(): Load a gen_tibble

gt_get_file_names(): Get the names of files storing the genotypes of a gen_tibble

Show

Functions to view loci and genotype information stored in a gen_tibble.

show_genotypes(): Show the genotypes of a gen_tibble

show_loci() `show_loci<-`(): Show the loci information of a gen_tibble

show_ploidy(): Show the ploidy information of a gen_tibble

count_loci(): Count the number of loci in a gen_tibble

augment_loci(): Augment the loci table with information from a analysis object

Selecting loci

Functions to select loci from a gen_tibble, either based on loci information, or genotype information.

select_loci(): The select verb for loci

select_loci_if(): The select_if verb for loci

Imputing

Functions for imputing missing data in a gen_tibble.

gt_impute_simple(): Simple imputation based on allele frequencies

gt_has_imputed(): Checks if a gen_tibble has been imputed

gt_uses_imputed(): Checks if a gen_tibble uses imputed data

gt_set_imputed(): Sets a gen_tibble to use imputed data

Merging

Functions for merging gen_tibble objects.

rbind_dry_run(): Generate a report of what would happen to each SNP in a merge

rbind(<gen_tbl>): Combine two gen_tibbles

summary(<rbind_report>): Print a summary of a merge report

Exporting

Functions for exporting a gen_tibble to another format.

gt_as_genind(): Convert a gen_tibble to a genind object from adegenet

gt_as_genlight(): Convert a gen_tibble to a genlight object from adegenet

gt_as_geno_lea(): Convert a gentibble to a .geno file for sNMF from the LEA package

gt_as_hierfstat(): Convert a gen_tibble to a data.frame compatible with hierfstat

gt_as_plink(): Export a gen_tibble object to PLINK bed format

gt_as_vcf(): Convert a gen_tibble to a VCF

Quality control

Functions reporting summary statistics for a gen_tibble.

qc_report_loci(): Create a Quality Control report for loci

qc_report_indiv(): Create a Quality Control report for individuals

autoplot(<qc_report_loci>): Autoplots for qc_report_loci objects

autoplot(<qc_report_indiv>): Autoplots for qc_report_indiv objects

filter_high_relatedness(): Filter individuals based on a relationship threshold

Loci

Functions operating across loci.

loci_alt_freq() loci_maf(): Estimate allele frequencies at each each locus

loci_chromosomes(): Get the chromosomes of loci in a gen_tibble

loci_hwe(): Test Hardy-Weinberg equilibrium at each locus

loci_ld_clump(): Clump loci based on a Linkage Disequilibrium threshold

loci_missingness(): Estimate missingness at each locus

loci_names(): Get the names of loci in a gen_tibble

loci_transitions(): Find transitions

loci_transversions(): Find transversions

Individual

Functions operating across individuals.

indiv_het_obs(): Estimate individual observed heterozygosity

indiv_missingness(): Estimate individual missingness

indiv_ploidy(): Return individual ploidy

Population

Functions operating on a gen_tibble grouped by population.

pop_fis(): Compute population specific FIS

pop_fst(): Compute population specific Fst

pop_global_stats(): Compute basic population global statistics

pop_het_exp() pop_gene_div(): Compute the population expected heterozygosity

pop_het_obs(): Compute the population observed heterozygosity

Pairwise

Functions comparing individuals or populations.

pairwise_allele_sharing(): Compute the Pairwise Allele Sharing Matrix for a gen_tibble object

pairwise_ibs(): Compute the Identity by State Matrix for a gen_tibble object

pairwise_pop_fst(): Compute pairwise population Fst

pairwise_king(): Compute the KING-robust Matrix for a a gen_tibble object

PCA

Functions for performing Principal Component Analysis.

gt_pca: Principal Component Analysis for gen_tibble objects

gt_pca_autoSVD(): PCA controlling for LD for gen_tibble objects

gt_pca_partialSVD(): PCA for gen_tibble objects by partial SVD

gt_pca_randomSVD(): PCA for gen_tibble objects by randomized partial SVD

predict(<gt_pca>): Predict scores of a PCA

tidy(<gt_pca>): Tidy a gt_pca object

augment(<gt_pca>): Augment data with information from a gt_pca object

augment_loci(<gt_pca>): Augment the loci table with information from a gt_pca object

autoplot(<gt_pca>): Autoplots for gt_pca objects

DAPC

Functions for performing Discriminant Analysis of Principal Components.

gt_dapc(): Discriminant Analysis of Principal Components for gen_tibble

gt_cluster_pca(): Run K-clustering on principal components

gt_cluster_pca_best_k(): Find the best number of clusters based on principal components

tidy(<gt_dapc>): Tidy a gt_dapc object

augment(<gt_dapc>): Augment data with information from a gt_dapc object

autoplot(<gt_dapc>): Autoplots for gt_dapc objects

autoplot(<gt_cluster_pca>): Autoplots for gt_cluster_pca objects

K-clustering (e.g. ADMXITURE)

Functions for creating, tidying, and visualising q_matrix objects.

q_matrix(): Read and structure .Q files or existing matrices as q_matrix or q_matrix_list objects.

get_q_matrix(): Return a single Q matrix from a q_matrix_list object

get_p_matrix(): Return a single P matrix from a q_matrix_list object

tidy(<q_matrix>): Tidy a Q matrix

augment(<q_matrix>): Augment data with information from a q_matrix object

autoplot(<q_matrix>): Autoplots for q_matrix objects

summary(<q_matrix_list>): Summarise a Q matrix list

distruct_colours: Distruct colours

scale_fill_distruct(): Scale constructor using the distruct colours

theme_distruct(): A theme to match the output of distruct

Other analyses (e.g. ADMIXTOOLS2, pcadapt)

Functions for other analyses within R.

gt_extract_f2(): Compute and store blocked f2 statistics for ADMIXTOOLS 2

gt_roh_window(): Detect runs of homozygosity using a sliding-window approach

gt_pcadapt(): pcadapt analysis on a gen_tibble object

autoplot(<gt_pcadapt>): Autoplots for gt_pcadapt objects

`bigSNP`

Mostly for developers: Functions for operating directly on bigSNP objects.

snp_allele_sharing(): Compute the Pairwise Allele Sharing Matrix for a bigSNP object

snp_ibs(): Compute the Identity by State Matrix for a bigSNP object

snp_king(): Compute the KING-robust Matrix for a bigSNP object