Check Time Homogeneity and Markov Chain Order
MOrder provide functions to check time homogeneity and order
of markov chain by using chi-squared test, AIC value and BIC value.
Akshay Chougule <akshaychougule@email.arizona.edu>, Dr Robert Canales
<rcanales@email.arizona.edu>

Multi-Patient Analysis of Genomic Markers
Quentin Grimonprez with contributions from Guillemette Marot and Samuel
Blanck. Some functions use code created by Sjoerd Vosse, Mark van de Wiel,
Pierre Neuvial, Henrik Bengtsson.
MPAgenomics provides functions to preprocess and analyze genomic
data. It provides wrappers from commonly used packages to streamline their
repeated manipulation, offering an easy-to-use pipeline.
The segmentation of successive multiple profiles is performed with an
automatic choice of parameters involved in the wrapped packages.
Considering multiple profiles in the same time, MPAgenomics wraps
efficient penalized regression methods to select relevant markers
associated with a given outcome.

Preprocess and analysis of genomic data. MPAgenomics
provides wrappers from commonly used packages to streamline their repeated
manipulation, offering an easy-to-use pipeline. The segmentation of
successive multiple profiles is performed with an automatic choice of
parameters involved in the wrapped packages. Considering multiple profiles
in the same time, MPAgenomics wraps efficient penalized regression methods
to select relevant markers associated with a given outcome.

c(person(given = "Quentin",
family = "Grimonprez",
role = "aut"),
person(given = "Sjoerd",
family = "Vosse",
role = "ctb"),
person(given = "Mark",
family = "van de Wiel",
role = "ctb"),
person(given = "Pierre",
family = "Neuvial",
role = "ctb"),
person(given = "Henrik",
family = "Bengtsson",
role = "ctb"),
person(given = "Ilari",
family = "Scheinin",
role = "ctb"),
person(given = "Guillemette",
family = "Marot",
role = "ctb"),
person(given = "Samuel",
family = "Blanck",
role = c("aut", "cre"),
email = "samuel.blanck@univ-lille.fr"),
person(given = "Inria",
role = "cph"))
Preprocessing and analysis of genomic data. 'MPAgenomics'
provides wrappers from commonly used packages to streamline their repeated
manipulation, offering an easy-to-use pipeline. The segmentation of
successive multiple profiles is performed with an automatic choice of
parameters involved in the wrapped packages. Considering multiple profiles
in the same time, 'MPAgenomics' wraps efficient penalized regression methods
to select relevant markers associated with a given outcome.
Grimonprez et al. (2014) <doi:10.1186/s12859-014-0394-y>.
Quentin Grimonprez [aut],
Sjoerd Vosse [ctb],
Mark van de Wiel [ctb],
Pierre Neuvial [ctb],
Henrik Bengtsson [ctb],
Ilari Scheinin [ctb],
Guillemette Marot [ctb],
Samuel Blanck [aut, cre],
Inria [cph]