| Type: | Package |
| Title: | Auto-Adaptive Parentage Inference Software Tolerant to Missing Parents |
| Version: | 2.0.8 |
| 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. |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Imports: | cowplot, data.table, doParallel, dplyr, DT, foreach, ggplot2, gridExtra, htmltools, methods, plotly, rlang, shiny, shinythemes |
| Depends: | R (≥ 3.5.0), shinyBS |
| NeedsCompilation: | yes |
| Packaged: | 2024-11-04 09:24:31 UTC; Proprietaire |
| Author: | 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 <julien.roche@inrae.fr> |
| Repository: | CRAN |
| Date/Publication: | 2024-11-04 09:40:02 UTC |
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)