R/zhangData.R

In CenterForStatistics-UGent/SPsimSeq: Semi-parametric simulation tool for bulk and single-cell RNA sequencing data

#' Neuroblastoma bulk RNA-seq data retrieved from Zhang et (2015).
#'
#' The data contains 498 neuroblastoma tumors. In short, unstranded
#' poly(A)+ RNA sequencing was performed on the HiSeq 2000 instrument (Illumina).
#' Paired-end reads with a length of 100 nucleotides were obtained. To quantify
#' the full transcriptome, raw fastq files were processed with Kallisto v0.42.4
#' (index build with GRCh38-Ensembl v85). The pseudo-alignment tool Kallisto
#' was chosen above other quantification methods as it is performing equally
#' good but faster. For this study, a subset of 172 tumors (samples) with
#' high-risk disease were selected, forming two groups: the MYCN amplified
#' ($n_1$ = 91) and MYCN non-amplified ($n_2$ = 81) tumours. Sometimes we refer
#' this dataset to as the Zhang data or the Zhang neuroblastoma data. In this
#' package, a subset of 5000 genes (randomly selected) are made available for illustration
#' purpose only.
#'
#' @docType data
#'
#' @format A list object
#'
#' @usage data(zhang.data.sub)
#'
#' @keywords datasets
#'
#' @references
#' 1. Zhang W, Yu Y, Hertwig F, Thierry-Mieg J, Zhang W, Thierry-Mieg D, Wang J, Furlanello C, Devanarayan V, Cheng J, et al. Comparison of RNA-seq and microarray-based models for clinical endpoint prediction. Genome Biol. 2015;16(133) https://doi.org/10.1186/s13059-015-0694-1
#' 2. Assefa, A. T., De Paepe, K., Everaert, C., Mestdagh, P., Thas, O., & Vandesompele, J. (2018). Differential gene expression analysis tools exhibit substandard performance for long non-coding RNA-sequencing data. GENOME BIOLOGY, 19.
#' \describe{
#'   \item{counts}{gene counts}
#'   \item{group}{MYCN (0 for MYCN non-amplified and 1 for MYCN amplified)}
#' }
#' @source \url{GEO accession GSE49711}
#' @examples
#' data("zhang.data.sub")
#' str(zhang.data.sub)
"zhang.data.sub"