public class LDKNNiImputationPlugin
extends AbstractPlugin
This imputation algorithm uses LD to identify good predictors for each SNP, and then uses the high LD SNPs to identify K- Nearest Neighbors. The genotype is called with a weighted mode of the KNNs.
public LDKNNiImputationPlugin()
public LDKNNiImputationPlugin(java.awt.Frame parentFrame,
boolean isInteractive)
protected void preProcessParameters(DataSet input)
public java.lang.String getCitation()
public javax.swing.ImageIcon getIcon()
public java.lang.String getButtonName()
public java.lang.String getToolTipText()
public static void main(java.lang.String[] args)
public GenotypeTable runPlugin(DataSet input)
Convenience method to run plugin with one return object.
public java.lang.Integer highLDSSites()
Maximum number of sites in high LD to use in imputation
public LDKNNiImputationPlugin highLDSSites(java.lang.Integer value)
Set High LD Sites. Maximum number of sites in high LD to use in imputation
value - High LD Sitespublic java.lang.Integer knnTaxa()
Maximum number of neighbours to use in imputation
public LDKNNiImputationPlugin knnTaxa(java.lang.Integer value)
Set Number of nearest neighbors. Maximum number of neighbours to use in imputation
value - Number of nearest neighborspublic java.lang.Integer maxDistance()
Maximum physical distance between sites to look for LD (-1 for no distance cutoff - unlinked chromosomes will be tested)
public LDKNNiImputationPlugin maxDistance(java.lang.Integer value)
Set Max distance between site to find LD. Maximum physical distance between sites to look for LD (-1 for no distance cutoff - unlinked chromosomes will be tested)
value - Max distance between site to find LDpublic static kotlin.Array[] dist(kotlin.Array[] b1,
kotlin.Array[] b2,
int min)
Alternative to current IBS distance measure AA <> AA = 0 Aa <> Aa = 0 distance (normal IBS distance this is 0.5) AA <> aa = 1 distance