sim_autorun: This is the simulation autorun that generates data, calls...

In mccoy-lab/rhapsodi: R haploid sperm/oocyte data imputation

This is the simulation autorun that generates data, calls rhapsodi, and compares rhapsodi's output with the truth/generated data

Description

First this simulation autorun function calls the generative model producing input data for rhapsodi as well as the true fully known data to be used later in assessment of rhapsodi Then it calls the rhapsodi autorun function which passes the generated output through the rhapsodi steps, returning rhapsodi's predictions Then it calls assessment using the function assess_it to compare the fully known truth/generated data with the rhapsodi predictions. which first assesses donor haplotypte phasing, producing a named list with single values for lhs (largest haplotype segment), ser (switch error rate), acc (accuracy), com (completeness) Then second assesses gamete genotype imputation, producing a named list with vectors for lhs (largest haplotype segment), ser (switch error rate), acc (accuracy), com (completeness) Then third assesses recombination discovery producing a named list with single values for precision, recall, accuracy, specificity, fdr (false discovery rate), fpr (false positive rate) f1 (f1 score), true_n (number of true recombination breakpoints), pred_n (number of predicted recombination breakpoints), tn (true negative), fn (false negative), tp (true positive), fp (false positive) Finally, it returns a list of named lists where phasing contains the phasing assessment named list gam_imputation contains the gamete genotype imputation assessment named list and recomb contains the recombination breakpoint discovery assessment named list

Usage

sim_autorun(
  num_gametes,
  num_snps,
  coverage,
  recomb_lambda,
  random_seed = 42,
  threads = 2,
  input_cov = TRUE,
  input_mgr = FALSE,
  missing_genotype_rate = NULL,
  add_seq_error = TRUE,
  seqError_add = 0.005,
  add_de_novo_mut = FALSE,
  de_novo_lambda = 5,
  de_novo_alpha = 7.5,
  de_novo_beta = 10,
  cons = FALSE,
  sampleName = "sim",
  chrom = "chrS",
  seqError_model = 0.005,
  avg_recomb_model = 1,
  window_length = 3000,
  overlap_denom = 2,
  calculate_window_size_bool = FALSE,
  mcstop = FALSE,
  stringent_stitch = TRUE,
  stitch_new_min = 0.5,
  smooth_imputed_genotypes = FALSE,
  fill_ends = TRUE,
  smooth_crossovers = TRUE,
  verbose = FALSE
)

Arguments

num_gametes	an integer, the number of gametes, used within sim_run_generative_model, or the number of columns for the sparse gamete data you want generated
num_snps	an integer, the number of SNPs, used within sim_run_generative_model,or the number of rows for the sparse gamete data you want generated. Note: not all of these will be heterozygous due to the coverage and therefore this number won't necessarily equal the number of SNPs following filtering at the end of the generation
coverage	a numeric, input if input_cov is TRUE, suggested NULL otherwise, used within sim_run_generative_model
recomb_lambda	a numeric, the average rate of recombination expected for the simulation, used by sim_find_num_crossovers within sim_run_generative_model
random_seed	an integer, default = 42, the random seed which will be set for the simulation, used within sim_run_generative_model
threads	an integer, default = 2, the number of cores to use when we use mclapply throughout the rhapsodi pipeline
input_cov	a bool, TRUE if coverage (i.e. like 0.01 (x)) will be input rather than missing genotype rate, default = TRUE, used within sim_run_generative_model
input_mgr	a bool, TRUE if missing genotype rate (i.e. like 80 (%) or 0.8) will be input rather than coverage, default = FALSE, used within sim_run_generative_model
missing_genotype_rate	a numeric, input if input_mgr is TRUE and input_cov is FALSE, suggested NULL otherwise, default = NULL, used within sim_run_generative_model
add_seq_error	a bool, TRUE if you want to simulate genotyping error in the generated data, default = TRUE, used within sim_run_generative_model
seqError_add	a numeric, default = 0.005, the genotyping error rate if adding genotyping error to the generated data, used by sim_add_seq_error within sim_run_generative_model
add_de_novo_mut	a bool, TRUE if you want to add de novo mutations to the generated data, default = FALSE, used within sim_run_generative_model
de_novo_lambda	an integer, default = 5, parameterizes a poisson distribution to find the number of de novo mutations (DNM) total, used by sim_add_de_novo_mut within sim_run_generative_model
de_novo_alpha	a numeric, default=7.5, shape parameter for a gamma distribution to find the number of gametes affected per DNM, used by sim_add_de_novo_mut within sim_run_generative_model
de_novo_beta	a numeric, default = 10, scale parameter for a gamma distribution to find the number of gametes affected per DNM, used by sim_add_de_novo_mut within sim_run_generative_model
cons	a bool, default = FALSE, If TRUE, compares recombination breakpoints in a conservative manner such that if two ore more true breakpoints intersect a single prediction, we only consider one intersection to be a tp and the rest to be fn. If FALSE, all are tp. Used by sim_find_tp and sim_find_fn within sim_assess_recomb by sim_assess_it
sampleName	a string, default = "sim", only used in reporting recombination breakpoints by rhapsodi. Used by find_recomb_spots and report_gametes within rhapsodi_autorun
chrom	a string, default = "chrS", only used in reporting recombination breakpoints by rhapsodi. Used by find_recomb_spots and report_gametes within rhapsodi_autorun
seqError_model	a numeric, default = 0.005, used in build_hmm within fill_gametes in rhapsodi_autorun, the expected error rate in genotyping, affects emission probabilities
avg_recomb_model	a numeric, default = 1, used in buil_hmm within fill_gametes in rhapsodi_autorun, the expected number of average recombination spots per chromosome, affects transition probabilities
window_length	an integer, default = 3000, used in split_with_overlap within impute_donor_haplotypes in rhapsodi_autorun as the segment length to use in constructing overlapping windows for phasing
overlap_denom	an integer, default = 2, used in split_with_overlap within impute_donor_haplotypes in rhapsodi_autorun as the denominator in calculating the amount of overlap to use in the overlapping windows for phasing
calculate_window_size_bool	A bool; used in phase_donor_haplotypes, whether or not to calculate the window size based on characteristics of the input dataset; default = FALSE
mcstop	a bool, default = FALSE, used in stitch_haplotypes within impute_donor_haplotypes in rhapsodi_autorun, only considered if stringent_stitch is TRUE. This parameter is used to determine whether phasing continues or exits if the mean concordance bewteen two windows is between 0.1 and 0.9. We prefer TRUE or continuing despite discordance for the simulation section so rhapsodi continues asking which threshold is closer and acts accordingly
stringent_stitch	a bool, default = TRUE, used in stitch_haplotypes within impute_donor_haplotypes in rhapsodi_autorun, this parameter is used to determine the threshold values used in determining whether two windows originate from the same donor. If TRUE, the preset thresholds of 0.1 and 0.9 are used.
stitch_new_min	a numeric, >0, < 1, default = 0.5, used in stitch_haplotypes within impute_donor_haplotypes in rhapsodi_autorun, only evaluated if stringent_stitch is FALSE. This parameter is dually assigned as the different_max and same_min threshold values when considering the mean concordance between two overlapping windows in phasing
smooth_imputed_genotypes	a bool, default = FALSE, used in report_gametes and unsmooth within rhapsodi_autorun, whether to use smoothed data from the HMM or original reads when there are mismatches for ending/predicted filled gamete genotypes. If TRUE, doesn't replace smoothed data from HMM with original reads
fill_ends	a boolean; if TRUE, fills the NAs at the terminal edges of chromosomes with the last known or imputed SNP (for end of chromosome) and the first known or imputed SNP (for beginning of chromosome); if FALSE, leaves these genotypes as NA; default = TRUE
smooth_crossovers	a bool, default = TRUE, used in report_gametes and unsmooth within rhapsodi_autorun, whether to use smoothed data from the HMM or original reads when there are mismatches for recombination breakpoint discovery. If TRUE, doesn't replace smoothed data from HMM with original reads
verbose	a bool; default is FALSE; if TRUE, prints progress statements after each step is successfully completed

Value

all_metrics a named list of named lists with all the assessment metric values or vectors

mccoy-lab/rhapsodi documentation built on July 27, 2022, 3:56 a.m.