View source: R/genMPSevidence.R
genMPSevidence | R Documentation |
Function for generating replicated mixture samples given same contributors and model parameters.
genMPSevidence(
calibration,
NOC,
popFreq,
mu = 1000,
omega = 0.1,
beta = 1,
sorted = FALSE,
mx = NULL,
refData = NULL,
nrep = 1,
kit = NULL,
platform = "MPS"
)
calibration |
An object indicating the fitted calibration model (marker efficiency,stutters,noise) (MLE based) |
NOC |
Number of contributors |
popFreq |
A list of allele frequencies for a given population. |
mu |
Expected peak heights for a het. single contributor allele |
omega |
Coeffecient of variance of peak heights. |
beta |
Coeffecient related to degree of degradation. |
sorted |
Boolean for wheter sorting the contributors with respect to decreasingly mixture proportions. |
mx |
A vector of known mixture proportions. Default is random uniform. |
refData |
A list of given reference profiles given as refData[[i]][[s]]. Default is random from population. |
nrep |
Number of replicates (same contributors) to generate. Default is 1. |
kit |
Kitname for considered kit (shortname). Required for degradation model |
platform |
The platform name that is used |
genDataset samples random mixture peak heights given as gamma(rho*sum(h_k),tau), with h_k as peak height of k-te contributor. genData conditions on alleles given by refData. Empty references are generated with population frequencies.
List with elements theta,samples,refData where theta is the true parameters of the model. samples is a list with samples which for each samples has locus-list elements with list elements adata and hdata
Oyvind Bleka
## Not run:
kit = "ForenSeq"
pkg = path.package("MPSproto")
calib = readRDS(paste0(pkg,"/paper_stutterChar/calibrated_MPSproto.RDS"))
popFreq = importMPSfreqs(paste0(pkg,"/paper_stutterChar/freqFile_ForenSeqFWbrack_Norway.csv"))[[1]]
gen = genMPSevidence(calib,2,popFreq,mu=1000,omega=0.2,beta=1,kit=kit )
plotMPS(gen$samples,gen$refData,AT=10)
## End(Not run)
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