InteRD1 function

The InteRD1 estimate from reference ensemble

The InteRD1 estimate from reference ensemble

This function provides a reference-based deconvolution by resembling all estimated cell-type proportions based on each reference set.

InteRD1(bulk.data,list_marker,cell_type_unique,comb_used, lambda_option,tol=1e-06)

Arguments

  • bulk.data: The ExpressionSet object for a target bulk data.
  • list_marker: A list of pre-specified marker genes corresponding to each cell type.
  • cell_type_unique: A list of cell types. It should match the order in list.marker.
  • comb_used: A list of pre-estimated cell type proportions based on different references.
  • lambda_option: A sequence of values for the tuning parameter.
  • tol: A tolerance value for convergence. The default is 1e-06

Returns

A list containing estimated cell type proportions corresponding to each tuning value, named est; and a sequence of goodness-of-fit values corresponding to each tuning value, named metrics. The smaller the better; and a list of weights corresponding to each tuning value, named weights_list.

Examples

##read data library(InteRD) readRDSFromWeb<-function(ref) {readRDS(gzcon(url(ref)))} urlremote<-"https://github.com/chencxxy28/Data/raw/main/data_InteRD/" pseudo.seger<-readRDSFromWeb(paste0(urlremote,"pseudo.seger.rds")) comb<-readRDSFromWeb(paste0(urlremote,"comb_seger.rds")) list_marker<-readRDSFromWeb(paste0(urlremote,"list_markerbaron20.rds")) lambda_option<-0 cell_type_unique<-c("alpha","beta","delta","gamma") InteRD1.output<-InteRD1(bulk.data =pseudo.seger,list_marker, cell_type_unique,comb_used=comb,lambda_option,tol=1e-02) InteRD1<-InteRD.predict.prop(InteRD.output=InteRD1.output)
  • Maintainer: Chixiang Chen
  • License: Artistic-2.0
  • Last published: 2022-08-12