R/datasets.R

In elmerfer/MIXTURE: MIXTURE: a nu-SVR based recursive feature extraction mdoel with noise constraints for molecular signature deconvolution of bulk tumor tissues

#' LM22
#'
#' A dataset containing the molecular signatureprofiles of 22 cell types. taken from 
#' [Newman et al.](http://www.nature.com/nmeth/journal/v12/n5/abs/nmeth.3337.html)
#'
#' \itemize{
#'   \item B cells naive
#'   \item B cells memory
#'   \item Plasma cells
#'   \item T cells CD8
#'   \item T cells CD4 naive
#'   \item T cells CD4 memory resting
#'   \item T cells CD4 memory activated
#'   \item T cells follicular helper
#'   \item T cells regulatory (Tregs)
#'   \item T cells gamma delta
#'   \item NK cells resting
#'   \item NK cells activated
#'   \item Monocytes
#'   \item Macrophages M0
#'   \item Macrophages M1
#'   \item Macrophages M2
#'   \item Dendritic cells resting
#'   \item Dendritic cells activated
#'   \item Mast cells resting
#'   \item Mast cells activated
#'   \item Eosinophils
#'   \item Neutrophils
#' }
#'
#' @docType data
#' @keywords datasets
#' @name LM22
#' @usage data(LM22)
#' @format A data frame with 547 rows (genes) and 22 variables (cell types). The rownames contains the GeneSymbols and the colnames the cell types
#' @references \url{https://cibersort.stanford.edu/}
NULL

#' TIL10
#'
#' A dataset containing the molecular signatureprofiles of 10 cell types. taken from 
#' [Finotello al.](https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-019-0638-6)
#'
#' \itemize{
#'   \item B cells
#'   \item Macrophages M1
#'   \item Macrophages M2   
#'   \item Monocytes
#'   \item Neutrophyls
#'   \item NK cells
#'   \item T cells CD4
#'   \item T cells CD8
#'   \item T cells regulatory (Tregs)
#'   \item Dendritic cells
#' }
#'
#' @docType data
#' @keywords datasets
#' @name TIL10
#' @usage data(TIL10)
#' @format A data frame with 170 rows (genes) and 10 variables (cell types). The rownames contains the GeneSymbols and the colnames the cell types
#' @references \url{https://icbi-lab.github.io/immunedeconv/}
NULL

#' TIL9
#'
#' A dataset containing the molecular signature profiles of 9 cell types. taken from 
#' [Yen-Jung Chiu et al.](https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-019-0613-5)
#  'https://static-content.springer.com/esm/art%3A10.1186%2Fs12920-019-0613-5/MediaObjects/12920_2019_613_MOESM2_ESM.xlsx
#' \itemize{
#'   \item T CD4
#'   \item NK cells
#'   \item Macrophages M2   
#'   \item Macrophages M1   
#'   \item Dendritic Cells
#'   \item T helper
#'   \item T cells regulatory (Tregs)
#'   \item T cells CD8
#'   \item T cells CD8 memory
#' }
#'
#' @docType data
#' @keywords datasets
#' @name TIL9
#' @usage data(TIL9)
#' @format A data frame with 547 rows (genes) and 22 variables (cell types). The rownames contains the GeneSymbols and the colnames the cell types
#' @references \url{https://static-content.springer.com/esm/art%3A10.1186%2Fs12920-019-0613-5/MediaObjects/12920_2019_613_MOESM2_ESM.xlsx}
NULL

#' immuCC
#' 
#' A dataset containing the mouse molecular signature profile of 25 cell typoes taken from
#' [Chen, Z. et al.](https://www.nature.com/articles/srep40508) 
#' \itemize{
#' \item Mast.Cells 
#' \item Neutrophil.Cells
#' \item Eosinophil.Cells
#' \item B.Cells.Memory
#' \item B.Cells.Naive
#' \item Plasma.Cells
#' \item T.Cells.CD8.Actived
#' \item T.Cells.CD8.Naive
#' \item T.Cells.CD8.Memory
#' \item M0.Macrophage
#' \item M1.Macrophage
#' \item M2.Macrophage
#' \item Treg.Cells
#' \item T.Cells.CD4.Memory
#' \item T.Cells.CD4.Naive
#' \item T.Cells.CD4.Follicular
#' \item Th1.Cells
#' \item Th17.Cells
#' \item Th2.Cells
#' \item Monocyte
#' \item GammaDelta.T.Cells
#' \item NK.Resting
#' \item NK.Actived
#' \item DC.Actived
#' \item DC.Immature
#' }
#' @docType data
#' @keywords datasets
#' @name ImmuCC
#' @usage data(ImmuCC)
#' @format A data frame with 511 rows (genes) and 25 variables (cell types). The rownames contains the GeneSymbols and the colnames the cell types
NULL