edgeR, mgcv, pracma, quadprog, Rsamtools, GenomicAlignments,
GenomicRanges, IRanges, csaw(>= 1.12.0), SummarizedExperiment,
BiocGenerics, S4Vectors, RMySQL

Piecewise Smooth Regression by Bootstrapped Binary Segmentation
c(person("McDaid", "Kate", role = c("aut"), email = "km685@alumni.cam.ac.uk"), person("Pein", "Florian", role = c("aut", "cre"), email = "f.pein@lancaster.ac.uk"))
Provides methods for piecewise smooth regression. A piecewise smooth signal is estimated by applying a bootstrapped test recursively (binary segmentation approach). Each bootstrapped test decides whether the underlying signal is smooth on the currently considered subsegment or contains at least one further change-point.
McDaid Kate [aut],
Pein Florian [aut, cre]

c(person("McDaid", "Kate", role = c("aut"), email = "km685@alumni.cam.ac.uk"), person("Pein", "Florian", role = c("aut", "cre"), email = "fp366@cam.ac.uk"))

Stefan Mundus, Christoph Müssel, Ludwig Lausser, Tamara J. Blätte, Martin Hopfensitz, Hans A. Kestler
Provides methods for the binarization of one-dimensional data and some visualization functions.

Creates, Merges, and Reads Binary Dosage Files
c(person(given = "John",
family = "Morrison",
role = c("aut", "cre"),
email = "jmorr@usc.edu"),
person(given = "NIEHS",
role = "fnd",
comment = "P01 CA196559"),
person(given = "NIEHS",
role = "fnd",
comment = "R01 CA201407"),
person(given = "NIEHS",
role = "fnd",
comment = "P30 ES007048"),
person(given = "NIEHS",
role = "fnd",
comment = "P01 HL115606"))
Tools to create binary dosage from either VCF
or GEN files, merge binary dosage files, and read
binary dosage files.
knitr, rmarkdown, testthat (>= 2.1.0), covr
John Morrison [aut, cre],
NIEHS [fnd] (P01 CA196559),
NIEHS [fnd] (R01 CA201407),
NIEHS [fnd] (P30 ES007048),
NIEHS [fnd] (P01 HL115606)

Variable Selection for Binary Data Using the EM Algorithm
person("John", "Snyder", email = "jcs8v6@mail.missouri.edu", role = c("aut", "cre"))
Implements variable selection for high dimensional datasets with a binary response
variable using the EM algorithm.  Both probit and logit models are supported.  Also included
is a useful function to generate high dimensional data with correlated variables.