Package 'APIS'

Title: Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents
Description: Parentage assignment package. Parentage assignment is performed based on observed average Mendelian transmission probability distributions or Exclusion. The main functions of this package are the function APIS_2n(), APIS_3n() and launch_APIShiny(), which perform parentage assignment.
Authors: Julien Roche [aut, cre], Ronan Griot [aut], Mathieu Besson [aut], François Allal [aut], Marc Vandeputte [aut], Jonathan D'Ambrosio [aut], Romain Morvezen [aut], Florence Phocas [aut], Sophie Brard-Fudulea [aut], Pierrick Haffray [aut]
Maintainer: Julien Roche <[email protected]>
License: GPL
Version: 2.0.8
Built: 2026-05-13 09:12:14 UTC
Source: https://github.com/cran/APIS

Help Index

APIS for diploids

Description

APIS for diploids

Usage

APIS_2n(
  offspring_genotype,
  sire_genotype,
  dam_genotype,
  method = "mendel",
  exclusion_threshold = NULL,
  error = 0.05,
  simulation_if_small = FALSE,
  number_offspring_simulated = max(0, 500 - nrow(offspring_genotype)),
  number_cores = 2,
  verbose = FALSE
)

Arguments

offspring_genotype

matrix of the offspring genotypes
sire_genotype

matrix of the sire genotypes
dam_genotype

matrix of the offspring genotypes
method

method : "mendel" i.e. likelihood or "exclusion" (default : "mendel"). Can also be "" to select the method a posteriori.
exclusion_threshold

threshold for "exclusion" method (default : NULL). Override the error parameter if not NULL
error

error accepted (default : 0.05)
simulation_if_small

simulate individuals (TRUE or FALSE)
number_offspring_simulated

number of offspring simulated (default : 500)
number_cores

number of cores
verbose

verbose

Value

list of 2 elements : a pedigree file and the log file

Examples

data("APIS_offspring")
data("APIS_sire")
data("APIS_dam")

assignment <- APIS_2n(offspring_genotype = APIS_offspring[1:35,1:50],
                      sire_genotype = APIS_sire[ ,1:50],
                      dam_genotype = APIS_dam[ ,1:50],
                      simulation_if_small = FALSE)

APIS for triploids

Description

APIS for triploids

Usage

APIS_3n(
  offspring_genotype,
  sire_genotype,
  dam_genotype,
  method = "mendel",
  exclusion_threshold = NULL,
  error = 0.05,
  simulation_if_small = FALSE,
  number_offspring_simulated = max(0, 500 - nrow(offspring_genotype)),
  number_cores = 2,
  verbose = FALSE,
  t_recom = 0.5
)

Arguments

offspring_genotype

matrix of the offspring genotypes
sire_genotype

matrix of the sire genotypes
dam_genotype

matrix of the dam genotypes
method

method : "mendel" i.e. likelihood or "exclusion" (default : "mendel"). Can also be "" to select the method a posteriori.
exclusion_threshold

threshold for "exclusion" method (default : NULL). Override the error parameter if not NULL
error

error accepted (default : 0.05)
simulation_if_small

simulate individuals (TRUE or FALSE) (default : TRUE)
number_offspring_simulated

number of offspring simulated (default : 500)
number_cores

number of cores
verbose

verbose
t_recom

recombination rate

Value

list of 2 elements : a pedigree file and the log file

Examples

data("APIS_offspring3n")
data("APIS_sire")
data("APIS_dam")
assignment <- APIS_3n(offspring_genotype = APIS_offspring3n[1:35,1:50],
                      sire_genotype = APIS_sire[ ,1:50],
                      dam_genotype = APIS_dam[ ,1:50],
                      simulation_if_small = FALSE)

Example dam genotypes

Description

Example dam genotypes

Usage

APIS_dam

Format

A matrix with 14 rows (one row = one dam) and 100 columns (one column = one marker)

Example offspring genotypes

Description

Example offspring genotypes

Usage

APIS_offspring

Format

A matrix with 500 rows (one row = one offspring) and 100 columns (one column = one marker)

Example offspring 3n genotypes

Description

Example offspring 3n genotypes

Usage

APIS_offspring3n

Format

A matrix with 50 rows (one row = one offspring) and 100 columns (one column = one marker)

Example sire genotypes

Description

Example sire genotypes

Usage

APIS_sire

Format

A matrix with 39 rows (one row = one sire) and 100 columns (one column = one marker)

Assignment power

Description

Assignment power

Usage

assignment_power(
  sire_genotype,
  dam_genotype,
  ploidy_level = 2,
  verbose = FALSE
)

Arguments

sire_genotype

matrix of the sire genotypes
dam_genotype

matrix of the dam genotypes
ploidy_level

ploidy level of the parents
verbose

verbose

Value

the theoretical assignment power calculated with the formula proposed in Vandeputte (2012)

Examples

data("APIS_sire")
data("APIS_dam")

P = assignment_power(sire_genotype = APIS_sire, dam_genotype = APIS_dam)

Import from Plink .ped

Description

Import from Plink .ped

Usage

import_from_ped(
  ped_file,
  no_fid = FALSE,
  no_parents = FALSE,
  no_sex = FALSE,
  no_pheno = FALSE,
  marker_names = NULL
)

Arguments

ped_file

name of the ped file (from Plink)
no_fid

if "no_fid" parameter was used in plink (default : FALSE)
no_parents

if "no_parents" parameter was used in plink (default : FALSE)
no_sex

if "no_sex" parameter was used in plink (default : FALSE)
no_pheno

if "no_pheno" parameter was used in plink (default : FALSE)
marker_names

list of marker names (default : NULL)

Value

matrix of genotypes for APIS

Import from .vcf

Description

Import from .vcf

Usage

import_from_vcf(vcf_file)

Arguments

vcf_file

name of the vcf file

Value

matrix of genotypes for APIS

Shiny App for interactive session of APIS

Description

Launch the shiny interface to use APIS interactively

Usage

launch_APIShiny()

Value

void : most results are automatically saved

Plot deltas

Description

Plot deltas

Usage

plot_delta(log_file, threshold = NULL, simulated_individuals = NULL)

Arguments

log_file

log file from the APIS_2n() or APIS_3n function
threshold

threshold
simulated_individuals

names of the simulated individuals

Value

plot of the distribution of delta

Plot mismatches

Description

Plot mismatches

Usage

plot_mismatches(log_file, threshold = NULL, simulated_individuals = NULL)

Arguments

log_file

log file from the APIS_2n() or APIS_3n function
threshold

threshold
simulated_individuals

names of the simulated individuals

Value

plot of the distribution of mismatches

Plot probabilities

Description

Plot probabilities

Usage

plot_probabilities(log_file, threshold = NULL, simulated_individuals = NULL)

Arguments

log_file

log file from the APIS_2n() or APIS_3n function
threshold

threshold
simulated_individuals

names of the simulated individuals

Value

plot of the distribution of probabilities

Simulate offspring

Description

Simulate offspring

Usage

simulate_offspring(
  sire_genotype,
  dam_genotype,
  number_offspring,
  ploidy_level = 2,
  sire_contribution = 1,
  dam_contribution = 1,
  recombination_rate = 0.5,
  genotyping_error = 0.01
)

Arguments

sire_genotype

sire genotype
dam_genotype

dam genotype
number_offspring

number of offspring to simulate
ploidy_level

ploidy level of offspring
sire_contribution

sire contribution
dam_contribution

dam contribution
recombination_rate

recombination rate (only important for tri/tetra ploids offspring)
genotyping_error

genotyping error

Value

list with matrix with simulated offspring and pedigree

Examples

data("APIS_sire")
data("APIS_dam")

# For diploide offspring
simulate_offspring(sire_genotype=APIS_sire, dam_genotype=APIS_dam,
                   number_offspring=10,
                   ploidy_level = 2,
                   sire_contribution = 1, dam_contribution = 1,
                   recombination_rate = 0.5,
                   genotyping_error = 0.01)

# For triploide offspring
simulate_offspring(sire_genotype=APIS_sire, dam_genotype=APIS_dam,
                   number_offspring=10,
                   ploidy_level = 3,
                   sire_contribution = 1, dam_contribution = 2,
                   recombination_rate = 0.5,
                   genotyping_error = 0.01)