Package: OmicKriging
Type: Package
Title: OmicKriging for Phenotypic Prediction
Version: 1.3
Date: 2013-09-26
Author: Hae Kyung Im, Heather E. Wheeler, Keston Aquino Michaels, Vassily
Trubetskoy
Maintainer: Hae Kyung Im <haky@uchicago.edu>
Description: This package 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
Collate: 'correlation_matrices.R' 'input_pheno_GT.R' 'omic_KRIGR.R'
Packaged: 2014-06-17 15:56:33 UTC; vasya
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-06-18 15:01:15

Title: Poly-Omic Prediction of Complex TRaits
Description: It provides functions to generate a correlation matrix

Title: Open-Source Software for 'Omic' Data Analysis and Visualization
A tool for interactive exploration of the results from 'omics'
experiments to facilitate novel discoveries from high-throughput biology. The
software includes R functions for the 'bioinformatician' to deposit study
metadata and the outputs from statistical analyses (e.g. differential
expression, enrichment). These results are then exported to an interactive
JavaScript dashboard that can be interrogated on the user's local machine or
deployed online to be explored by collaborators. The dashboard includes
'sortable' tables, interactive plots including network visualization, and
fine-grained filtering based on statistical significance.
person("Terrence", "Ernst", role = c("aut"),
person("John", "Blischak", role = c("aut", "cre"),
person("Paul", "Nordlund", role = c("aut"),
person("Justin", "Moore", role = c("aut"),
comment = "UpSet-related functions and web application"),
comment = "Barcode functionality and web application"),
person("Akshay", "Bhamidipati", role = c("aut"),
person("Brett", "Engelmann", role = c("aut"),
person("Marco", "Curado", role = c("aut"),
comment = "Improved plotting capabilities"),
person("Joe", "LoGrasso", role = c("aut"),
person(given = "AbbVie Inc.", role = c("cph", "fnd"))
Imports: data.table (>= 1.12.4), graphics, jsonlite, stats, tools,
Suggests: faviconPlease, ggplot2, opencpu, plotly, tinytest (>= 1.2.3),
Author: Terrence Ernst [aut] (Web application),
Justin Moore [aut] (UpSet-related functions and web application),
Joe Dalen [aut] (Barcode functionality and web application),
Akshay Bhamidipati [aut] (Web application),
Marco Curado [aut] (Improved plotting capabilities),
Joe LoGrasso [aut] (Support for plotly),