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#' Lung-cancer cell lines data in cancer cell line encyclopedia (CCLE) dataset
#'
#' The omics data is a subset of the dataset provided by cancer cell line
#' encyclopedia (CCLE) project (Barretina et al., 2012;
#' \url{https://sites.broadinstitute.org/ccle/}).
#'
#' @details This data consists of one response variable and ten genes
#' evaluated under three different platforms.
#'
#' The response variable measures the log-transformed activity area of taking
#' Vandertanib, a drug targeting on EGFR gene for lung cancer.
#'
#' The three platforms are DNA copy number variation (CNV), methylation and mRNA
#' expression.
#'
#' Among the 10 genes, 7 of them (EGFR, EREG, HRAS, KRAS, PTPN11, STAT3, and
#' TGFA) are involved in the protein-protein interaction network of EGFR
#' (\href{https://string-db.org}{https://string-db.org}) and the rest (ACTB,
#' GAPDH, and PPIA) are arbitrarily chosen housekeeping genes and play the role
#' of negative control.
#'
#' Detailed pre-processing procedure is available in Chang et al. (2021).
#'
#' @docType data
#'
#' @usage data(omics)
#'
#' @format A list contains two objects:
#' \describe{
#' \item{omics}{a 3-dimensional array with size (3, 10, 68)}
#' \item{Y}{a 68-length vector representing the response variable}
#' }
#'
#' @keywords datasets
#'
#' @references Barretina, J., Caponigro, G., Stransky, N. et al.
#' The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer
#' drug sensitivity. Nature 483, 603–607 (2012).
#' (\href{https://www.nature.com/articles/nature11003}{Link})
#'
#' @references Sheng-Mao Chang, Meng Yang, Wenbin Lu, Yu-Jyun Huang, Yueyang Huang, Hung Hung,
#' Jeffrey C Miecznikowski, Tzu-Pin Lu, Jung-Ying Tzeng,
#' Gene-set integrative analysis of multi-omics data using tensor-based association test,
#' Bioinformatics, 2021;, btab125,
#' (\href{https://academic.oup.com/bioinformatics/advance-article-abstract/doi/10.1093/bioinformatics/btab125/6154849}{Link}))
#'
#' @source \href{https://string-db.org}{https://string-db.org}
#'
#' @examples
#' data(omics)
#' names(omics)
#' dim(omics$omics)
#' # 3 10 68
"omics"
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