Package: MixRF
Title: A Random-Forest-Based Approach for Imputing Clustered Incomplete
Data
Version: 1.0
Date: 2016-04-05
Author: Jiebiao Wang and Lin S. Chen
Maintainer: Jiebiao Wang <randel.wang@gmail.com>
Description: It offers random-forest-based functions to impute clustered
incomplete data. The package is tailored for but not limited to imputing
multitissue expression data, in which a gene's expression is measured on the
collected tissues of an individual but missing on the uncollected tissues.
License: GPL
Depends: doParallel, randomForest, lme4, foreach
URL: https://github.com/randel/MixRF
BugReports: https://github.com/randel/MixRF/issues
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-06 02:05:06 UTC; JWang
Repository: CRAN
Date/Publication: 2016-04-06 09:43:04
Package: MonoInc
Type: Package
Title: Monotonic Increasing
Version: 1.1
Date: 2016-05-19
Author: Melyssa Minto, Michele Josey, and ClarLynda Williams-DeVane
Maintainer: Michele Josey <mjosey@nccu.edu>
Description: Various imputation methods are utilized in this package, where one can flag and impute non-monotonic data that is outside of a prespecified range.
License: GPL-3
Encoding: UTF-8
Depends: compare, doParallel, foreach, iterators, parallel
Imports: sitar
NeedsCompilation: no
Packaged: 2016-05-20 16:57:57 UTC; michelejosey
Repository: CRAN
Date/Publication: 2016-05-20 22:36:53
Package: OmicKriging
Type: Package
Title: Poly-Omic Prediction of Complex TRaits
Version: 1.4.0
Date: 2016-03-03
Author: Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily
Trubetskoy
Maintainer: Hae Kyung Im <haky@uchicago.edu>
Description: It provides functions to generate a correlation matrix
from a genetic dataset and to use this matrix to predict the phenotype of an
individual by using the phenotypes of the remaining individuals through
kriging. Kriging is a geostatistical method for optimal prediction or best
unbiased linear prediction. It consists of predicting the value of a
variable at an unobserved location as a weighted sum of the variable at
observed locations. Intuitively, it works as a reverse linear regression:
instead of computing correlation (univariate regression coefficients are
simply scaled correlation) between a dependent variable Y and independent
variables X, it uses known correlation between X and Y to predict Y.
License: GPL (>= 3)
Depends: R (>= 2.15.1), doParallel
Imports: ROCR, irlba, parallel, foreach
Collate: 'correlation_matrices.R' 'input_pheno_GT.R' 'omic_KRIGR.R'
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-03-07 16:26:39 UTC; haky
Repository: CRAN
Date/Publication: 2016-03-08 00:12:43
Package: REPTILE
Type: Package
Title: Regulatory DNA Element Prediction
Version: 1.0
Date: 2016-6-16
Author: Yupeng He
Description: Predicting regulatory DNA elements based on epigenomic signatures. This package is more of a set of building blocks than a direct solution. REPTILE regulatory prediction pipeline is built on this R package. See <https://github.com/yupenghe/REPTILE> for more information.
Maintainer: Yupeng He <yupeng.he.bioinfo@gmail.com>
URL: https://github.com/yupenghe/REPTILE
License: BSD_2_clause + file LICENSE
Depends: R (>= 3.2.2), foreach (>= 1.4.3), doParallel (>= 1.0.10)
Imports: optparse (>= 1.3.2), randomForest (>= 4.6-12), flux (>= 0.3-0)
NeedsCompilation: no
Packaged: 2016-06-21 06:36:30 UTC; yupeng
Repository: CRAN
Date/Publication: 2016-06-21 09:23:58
Package: Rlof
Version: 1.1.1
Date: 2015-09-16
Title: R Parallel Implementation of Local Outlier Factor(LOF)
Author: Yingsong Hu, Wayne Murray and Yin Shan, Australia.
Maintainer: Yingsong Hu <yingsonghu@hotmail.com>
Depends: R (>= 2.14.0), doParallel, foreach
Description: R parallel implementation of Local Outlier Factor(LOF) which uses multiple CPUs to significantly speed up the LOF computation for large datasets. (Note: The overall performance depends on the computers especially the number of the cores).It also supports multiple k values to be calculated in parallel, as well as various distance measures in addition to the default Euclidean distance.
License: GPL (>= 2)
Packaged: 2015-09-16 12:47:58 UTC; yingsong
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-09-17 07:51:00
Package: GenCAT
Type: Package
Title: Genetic Class Association Testing
Version: 1.0.3
Date: 2016-06-10
Author: Eric Reed, Sara Nunez, Jing Qian, Andrea Foulkes
Maintainer: Eric Reed <reeder@bu.edu>
Description: Implementation of the genetic class level association testing (GenCAT) method from SNP level association data. Refer to: "Qian J, Nunez S, Reed E, Reilly MP, Foulkes AS (2016) <DOI:10.1371/journal.pone.0148218> A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci. PLoS ONE 11(2): e0148218".
Suggests: snpStats, knitr
Depends: R (>= 2.10), stats, dplyr, doParallel, ggplot2, foreach, parallel, methods
License: GPL-2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-06-10 17:31:06 UTC; ericreed
Repository: CRAN
Date/Publication: 2016-06-10 23:12:38
Package: GiNA
Type: Package
Title: High Throughput Phenotyping
Version: 1.0.1
Date: 2016-03-29
Author: Luis Diaz-Garcia and Giovanny Covarrubias-Pazaran, with collaborations of Brandon Schlautman, Walter Salazar and Juan Zalapa.
Maintainer: Giovanny Covarrubias-Pazaran <covarrubiasp@wisc.edu>
Description: Performs image segmentation in fruit or seeds pictures in order to measure physical features in a high-throughput manner for genome-wide association (GWAS) and genomic selection programs.
Depends: R (>= 3.2.1), methods, stats, EBImage, png, parallel, doParallel, foreach
License: GPL-3
URL: http://www.wisc.edu
Packaged: 2016-04-09 15:29:30 UTC; cova_ruber
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-04-10 00:27:50
providing 
.