aberrant.plot: Scatter plot of summary statistics

In carbocation/aberrant: A robust clustering algorithm for outlier identification

Description

Draws a scatter plot of the summary statistics showing outliers.

Usage

aberrant.plot(x)

Arguments

x	output from function aberrant

Details

"Normal" individuals are coloured with a gradation from black to grey, with darker colours denoting higher density of individuals. Outliers are coloured with a gradation from orange to red, with darker colours denoting higher posterior probability of being an outlier. 99% confidence ellipse of the inferred inlier distribution is shown as a dashed grey line.

Author(s)

Celine Bellenguez and Chris CA Spencer

References

Celine Bellenguez, Amy Strange, Colin Freeman, Wellcome Trust Case Control Consortium 2, Chris CA Spencer. A robust clustering algorithm for identifying problematic samples in genome-wide association studies. Bioinformatics.

Examples

x<-rmvt(1000, sigma=matrix(c(1,0.5,0.5,1),2,2), df=3)
res<-aberrant(x, lambda=30, alpha=1, beta = 20)
aberrant.plot(res)

carbocation/aberrant documentation built on May 15, 2020, 6:04 p.m.