Keen and Reliable Interface Subroutines for Bioinformatic
Analysis
c(person(given = "Kridsadakorn", family = "Chaichoompu", email = "kridsadakorn.chaichoompu@gmail.com", role = c("aut", "cre")),person(given = "Kristel", family = 'Van Steen', role = "aut"),person(given = "Fentaw", family = "Abegaz", role = "aut"),person(given = "Sissades", family = "Tongsima", role = "aut"),person(given = "Philip", family = "James Shaw", role = "aut"),person(given = "Anavaj", family = "Sakuntabhai", role = "aut"),person(given = "Luisa", family = "Pereira", role = "aut"))
Provides useful functions which are needed for bioinformatic analysis such as calculating linear principal components from numeric data and Single-nucleotide polymorphism (SNP) dataset, calculating fixation index (Fst) using Hudson method, creating scatter plots in 3 views, handling with PLINK binary file format, detecting rough structures and outliers using unsupervised clustering, and calculating matrix multiplication in the faster way for big data.
Kridsadakorn Chaichoompu [aut, cre],
Kristel Van Steen [aut],
Fentaw Abegaz [aut],
Sissades Tongsima [aut],
Philip James Shaw [aut],
Anavaj Sakuntabhai [aut],
Luisa Pereira [aut]

c(person(given = "Kridsadakorn", family = "Chaichoompu", email = "kridsadakorn@biostatgen.org", role = c("aut", "cre")),person(given = "Kristel", family = 'Van Steen', role = "aut"),person(given = "Fentaw", family = "Abegaz", role = "aut"),person(given = "Sissades", family = "Tongsima", role = "aut"),person(given = "Philip", family = "James Shaw", role = "aut"),person(given = "Anavaj", family = "Sakuntabhai", role = "aut"),person(given = "Luisa", family = "Pereira", role = "aut"))

Kernel-based Regularized Least Squares (KRLS)
Jens Hainmueller (MIT) Chad Hazlett (MIT)
Package implements Kernel-based Regularized Least Squares
(KRLS), a machine learning method that can be used to fit
multidimensional functions for regression and classification
problems without relying on linearity or additivity
assumptions. This package is currently in alpha phase (feedback
is appreciated).