Run_Genotyping: Launch genotyping phase in parallel

In GenoTriplo: Genotyping Triploids (or Diploids) from Luminescence Data

Launch genotyping phase in parallel

Description

Function that launch the genotyping phase from the dataset with SampleName, Contrast and SigStren for each markers and the result of the 'Run_clustering' function.

Usage

Run_Genotyping(
  data_clustering,
  res_clust,
  ploidy,
  SeuilNoCall = 0.85,
  SeuilNbSD = 2.8,
  SeuilSD = 0.28,
  n_core = 1,
  corres_ATCG = NULL,
  pop = "Yes",
  cr_marker = 0.97,
  fld_marker = 3.4,
  hetso_marker = -0.3,
  save_n = "",
  batch = "",
  ALL = TRUE,
  path_log = ""
)

Arguments

data_clustering	dataframe result from create dataset phase
res_clust	object from clustering phase
ploidy	ploidy of offspring
SeuilNoCall	threshold of the probability of belonging to a cluster
SeuilNbSD	threshold for the distance between an individuals and his cluster (x=Contrast)
SeuilSD	threshold for the standard deviation of a cluster (SeuilSD*(1+0.5*abs(mean_contrast_cluster)))
n_core	number of cores used for parallelization
corres_ATCG	dataframe with the correspondence between A/B of AXAS and A/T/C/G (three columns : probeset_id, Allele_A, Allele_B)
pop	Yes or No : are individuals from a same population
cr_marker	call rate threshold
fld_marker	FLD threshold
hetso_marker	HetSO threshold
save_n	name of the saving file. If ” no auto save and return value is changed
batch	batch number in case of parallelization else ignore
ALL	TRUE/FALSE whether the dataset has been cut or not (from the shiny app)
path_log	path for log file when run by the shiny app

Value

if save_n != ” : 3 objects list : dataframe with call rate by individuals, dataframe with call rate and other metrics of markers and another dataframe – Automatically save results. Else : return list with genotype

Examples

data(GenoTriplo_to_clust)
data(GenoTriplo_to_geno)
res = Run_Genotyping(data_clustering=GenoTriplo_to_clust,
                     res_clust=GenoTriplo_to_geno,
                     ploidy=3)

GenoTriplo documentation built on May 29, 2024, 11:22 a.m.