prepareC_prediction: prepareC_prediction
In oyvble/MPSproto: A Quantitative Model for MPS data with complex stutters

prepareC_prediction

R Documentation

prepareC_prediction

Description

Helpfunction to prepare data for calling C (used in calcLogLikC_prediction)

Usage

prepareC_prediction(
  dat,
  hypothesis,
  calibration,
  kit = NULL,
  platform = "MPS",
  model = "GA"
)

Arguments

`dat`	A list returned from prepareData_prediction function (includes evididence,reference,frequency data)
`hypothesis`	A list which defines the hypothesis to evaluate. Must contain the following elements: NOC Number of contributors in model (Mandatory). condOrder (conditioning references from refData (must be consistent order). For instance condOrder=(0,2,1,0) means that we restrict the model such that Ref2 and Ref3 are respectively conditioned as 2. contributor and 1. contributor in the model. fst The co-ancestry coefficient. Can be a vector (must contain the marker names). Default is 0. knownRef Specify known non-contributing references from refData (indices). For instance knownRef=(1,2) means that reference 1 and 2 is known non-contributor in the hypothesis. This affectes coancestry correction.
`calibration`	A list from calibration results (per marker). Must contain the following elements (in following order): AT Analytical threshold markerEff Marker efficiency param nNoiseParam Parameter for modeling distr of number of noise (Noise model) noiseSizeParam Parameter for modeling size of noise alleles (Noise model) Reg-coeffs (b0,b1,b2) for different stutter types (each element considers a particular stutter type)
`kit`	shortname of kit. Used to model degradation model. Obtained from getMPSkit().
`platform`	Platform type "MPS","CE". NOTE: CE has only consider only some stutter types (BW1,DBW1,FW1)
`model`	Selected model for the signals (read/peak heights): "GA"=gamma,"NB"=negative binomial