Depends: R (>= 2.0), wavethresh, fractal

Title: Bootstrap cis-QTL Method that Corrects for the Winner's Curse
Description: Identifies genome-related molecular traits with significant
evidence of genetic regulation and performs a bootstrap procedure to
correct estimated effect sizes for over-estimation present in cis-QTL
mapping studies (The "Winner's Curse"), described in Huang QQ *et al.*
Suggests: doMC, doParallel, qvalue, testthat

person("Stéphane", "Laurent", , "laurent_step@outlook.fr", role = c("aut", "cre"))
Description: Performs Boolean operations on volumes: union, difference and
intersection. The computations are done by the 'C++' library 'CGAL'
Imports: data.table, gmp, PolygonSoup, Rcpp (>= 1.0.9)

Package: Boptbd
Version: 1.0.5
Date: 2020-01-11
Title: Bayesian Optimal Block Designs
Authors@R: c(person("Dibaba Bayisa", "Gemechu", role = c("aut", "cre"), email = "dgemechu@nust.na"),
person("Legesse Kassa", "Debusho", role = "aut", email = "debuslk@unisa.ac.za"),
person("Linda", "Haines", role = "aut", email = "linda.haines@uct.ac.za"))
Author: Dibaba Bayisa Gemechu [aut, cre],
Legesse Kassa Debusho [aut],
Linda Haines [aut]
Maintainer: Dibaba Bayisa Gemechu <dgemechu@nust.na>
Depends: R (>= 3.4.0), MASS, Matrix, igraph, tcltk
Description: Computes Bayesian A- and D-optimal block designs under the linear mixed effects model settings
using block/array exchange algorithm of Debusho, Gemechu and Haines (2018) <doi:10.1080/03610918.2018.1429617> where the interest is in a
comparison of all possible elementary treatment contrasts. The package also provides an optional
method of using the graphical user interface (GUI) R package 'tcltk' to ensure that it is user friendly.
License: GPL-2
NeedsCompilation: no
Packaged: 2020-01-11 15:27:36 UTC; Dibaba B Gemechu
Repository: CRAN
Date/Publication: 2020-01-13 17:20:07 UTC

Title: Boruta -- a tool for finding significant attributes in
Author: Algorithm by Witold R. Rudnicki <W.Rudnicki@icm.edu.pl>, R
implementation by Miron B. Kursa <M.Kursa@icm.edu.pl>.
Description: Boruta is a feature selection algorithm based on a
randomForest predictor. It selects the full set of all
important attributes by comparing original attributes
importance with datum importance of their randomised copies.
Maintainer: Miron B. Kursa <M.Kursa@icm.edu.pl>