simNormalize: Normalization Simulator

In OskarHansson/pcrsim: Simulation of the Forensic DNA Process

Description

Simulates the normalization process of a DNA extract.

Usage

simNormalize(
  data = NULL,
  volume = NULL,
  accuracy = 1,
  target = 0.5/17.5,
  tolerance = 0.1,
  multiple = FALSE,
  debug = FALSE
)

Arguments

data	data.frame with simulated data. Preferably output from simExtraction. Required columns are 'Marker', 'Allele', 'Sim', 'Volume', 'Ex.Conc', and 'DNA'.
volume	numeric for the final volume after dilution.If NULL it will be taken from column 'Volume'.
accuracy	numeric for the pipetting accuracy e.g. minimum pipetting volume.
target	numeric for the target concentration.
tolerance	numeric for the tolerance around the target concentration e.g. 0.1 is +-10%.
multiple	logic if TRUE the function will call itself until target is reached. Only the last round of results will be stored in the simulated dataset.
debug	logical flagging for debug mode.

Details

Simulates the normalization process by binomial selection of molecules. The average concentration per sample is used to calculate the dilution factor.

Value

data.frame with simulation results in columns 'Norm.Avg.Conc', 'Norm.Vol', 'Norm.Aliq', 'Norm.Aliq.Prob', 'Norm.DNA', 'Norm.Conc', and 'DNA'.

See Also

simExtraction

Examples

# Create a data frame with a DNA profile.
markers = rep(c("D3S1358","TH01","FGA"), each=2)
alleles = c(15,18,6,10,25,25)
df <- data.frame(Marker=markers, Allele=alleles)

# Simulate profile.
res <- simProfile(data=df, sim=3, name="Test")

# Simulate diploid sample.
res <- simSample(data=res, cells=10000, sd.cells=200)

# [OPTIONAL] Simulate degradation.
res <- simDegradation(data=res, kit="ESX17", deg=0.003, quant.target=80)

# Simulate extraction.
res <- simExtraction(data=res, vol.ex=200, sd.vol=10, prob.ex=0.3, sd.prob=0.1)

# Simulate normalization.
res <- simNormalize(data=res, volume=100)

OskarHansson/pcrsim documentation built on Jan. 22, 2022, 11:55 a.m.