Package phase

Class PhaseData

java.lang.Object

phase.PhaseData

public class PhaseData
extends java.lang.Object

Class PhaseData contains the input data for phasing genotypes.

Instances of class PhaseData are immutable.

Constructor Summary

Constructors

Constructor	Description
PhaseData(CurrentData cd, EstPhase estPhase, double recombFactor, int it, long seed)	Constructs a new ImpData instance from the specified data.

Method Summary

Modifier and Type	Method	Description
int	allele(int marker, int hap)
boolean	burnin()	Returns true if the current phasing iteration is a burnin iteration and returns false otherwise.
FloatArray	genDist()	Return a FloatArray of size this.nTargMarkers() whose k-th element is the genetic distance between the k-th target marker and the previous marker, or 0.0 if (k == 0).
int	iter()	Returns the iteration index.
Marker	marker(int marker)	Returns the specified marker.
Markers	markers()	Returns the list of target markers.
int	nHaps()	Returns the number of reference and target haplotypes.
int	nItsRemaining()	Returns the number of iterations remaining.
int	nMarkers()	Returns the number of target markers
int	nRefHaps()	Return the number of reference haplotypes.
int	nTargHaps()	Return the number of target haplotypes.
int	nTargSamples()	Returns the number of target samples.
Par	par()	Returns the command line parameters
float	pErr(int marker)	Returns the probability that the allele carried by the specified target marker cluster matches the allele labeling the latent HMM state.
double[]	pos()	Returns the array of genetic map positions whose k-th element equals this.pos(k).
FloatArray	pRecomb()	Return a FloatArray of size this.nTargMarkers() whose k-th element is the factor multiplied by genetic distance to obtain the probability of transitioning to a random HMM state between the k-th target marker and the previous marker.
long	seed()	Returns the seed for generating random numbers.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PhaseData

public PhaseData(CurrentData cd,
                 EstPhase estPhase,
                 double recombFactor,
                 int it,
                 long seed)

Constructs a new ImpData instance from the specified data.

Parameters:

cd - the input data for the current marker window

estPhase - the current estimate of phased target genotypes

recombFactor - the factor multiplied by genetic distance to obtain the probability of transitioning to a random HMM state.

it - the current iteration (first iteration has index 0)

seed - seed for random numbers

Throws:

java.lang.IllegalArgumentException - if cd.targMarkers().equals(estPhase.markers() == false

java.lang.IllegalArgumentException - if recombFactor < 0 || Double.isFinite(recombFactor)==false

java.lang.IllegalArgumentException - if cd.targSamples().equals(estPhase.samples()) == false

java.lang.NullPointerException - if any parameter is null

Method Detail

par

public Par par()

Returns the command line parameters

Returns:

the command line parameters

burnin

public boolean burnin()

Returns true if the current phasing iteration is a burnin iteration and returns false otherwise.

Returns:

true if the current phasing iteration is a burnin iteration

allele

public int allele(int marker,
                  int hap)

iter

public int iter()

Returns the iteration index.

Returns:

the iteration index

nItsRemaining

public int nItsRemaining()

Returns the number of iterations remaining.

Returns:

the number of iterations remaining

nMarkers

public int nMarkers()

Returns the number of target markers

Returns:

the number of target markers

markers

public Markers markers()

Returns the list of target markers.

Returns:

the list of target markers

marker

public Marker marker(int marker)

Returns the specified marker.

Parameters:

marker - a marker index

Returns:

the specified marker

Throws:

java.lang.IndexOutOfBoundsException - if marker < 0 || marker >= this.nMarkers()

nTargSamples

public int nTargSamples()

Returns the number of target samples.

Returns:

the number of target samples

nRefHaps

public int nRefHaps()

Return the number of reference haplotypes.

Returns:

the number of reference haplotypes

nTargHaps

public int nTargHaps()

Return the number of target haplotypes.

Returns:

the number of target haplotypes

nHaps

public int nHaps()

Returns the number of reference and target haplotypes.

Returns:

the number of reference and target haplotypes

pErr

public float pErr(int marker)

Returns the probability that the allele carried by the specified target marker cluster matches the allele labeling the latent HMM state.

Parameters:

marker - index of a target marker cluster

Returns:

the probability that the allele carried by the specified target marker cluster matches the allele labeling the latent HMM state

Throws:

java.lang.IndexOutOfBoundsException - if cluster < 0 || cluster >= this.nClusters()

pos

public double[] pos()

Returns the array of genetic map positions whose k-th element equals this.pos(k).

Returns:

the array of genetic map positions

genDist

public FloatArray genDist()

Return a FloatArray of size this.nTargMarkers() whose k-th element is the genetic distance between the k-th target marker and the previous marker, or 0.0 if (k == 0).

Returns:

a FloatArray of size this.nTargMarkers() whose k-th element is the genetic distance between the k-th target marker and the previous marker,

pRecomb

public FloatArray pRecomb()

Return a FloatArray of size this.nTargMarkers() whose k-th element is the factor multiplied by genetic distance to obtain the probability of transitioning to a random HMM state between the k-th target marker and the previous marker.

Returns:

a FloatArray of size this.nTargMarkers() whose k-th element is the factor multiplied by genetic distance to obtain the probability of transitioning to a random HMM state between the k-th target marker and the previous marker

seed

public long seed()

Returns the seed for generating random numbers.

Returns:

the seed for generating random numbers