tests/testthat/test-createMAE.R

In ELMER: Inferring Regulatory Element Landscapes and Transcription Factor Networks Using Cancer Methylomes

context("Testing Multi Assay Experiment creation")
# 
# test_that("The creation of a using matrices and no TCGA data with equal colnames in DNA methylation and Gene Expression", {
#   # NON TCGA example: matrices has diffetrent column names
#   gene.exp <- DataFrame(sample1 = c("ENSG00000141510"=2.3,"ENSG00000171862"=5.4),
#                         sample2 = c("ENSG00000141510"=1.6,"ENSG00000171862"=2.3)
#   )
#   dna.met <- DataFrame(sample1 = c("cg14324200"=0.5,"cg23867494"=0.1),
#                        sample2 =  c("cg14324200"=0.3,"cg23867494"=0.9)
#   )
#   sample.info <- DataFrame(sample.type = c("Normal", "Tumor"))
#   rownames(sample.info) <- colnames(gene.exp)
#   
#   suppressMessages({
#     mae <- createMAE(exp = gene.exp, met = dna.met, colData  = sample.info, genome = "hg38") 
#   })
#   expect_equal(metadata(mae)$genome,"hg38")
#   expect_false(metadata(mae)$TCGA)
#   expect_equal(dim(getExp(mae)),c(2,2))
#   expect_equal(dim(getMet(mae)),c(2,2))
#   expect_equal(assay(getMet(mae)),as.matrix(dna.met))
#   expect_equal(assay(getExp(mae)),as.matrix(gene.exp))
#   expect_equal(colData(mae),sample.info)
#   expect_true(all(sampleMap(mae)$assay %in% c("DNA methylation","Gene expression")))
# })  
# 
# test_that("The creation of a using matrices and no TCGA data with different colnames in DNA methylation and Gene Expression", {
#   # NON TCGA example: matrices has diffetrent column names
#   gene.exp <- DataFrame(sample1.exp = c("ENSG00000141510"=2.3,"ENSG00000171862"=5.4),
#                         sample2.exp = c("ENSG00000141510"=1.6,"ENSG00000171862"=2.3)
#   )
#   dna.met <- DataFrame(sample1.met = c("cg14324200"=0.5,"cg23867494"=0.1),
#                        sample2.met =  c("cg14324200"=0.3,"cg23867494"=0.9)
#   )
#   sample.info <- DataFrame(sample.type = c("Normal", "Tumor"))
#   rownames(sample.info) <- c("sample1","sample2")
#   sampleMap <- DataFrame(primary = c("sample1","sample1","sample2","sample2"), 
#                          colname = c("sample1.exp","sample1.met","sample2.exp","sample2.met"))
#   
#   suppressMessages({
#     mae <- createMAE(exp = gene.exp, met = dna.met, 
#                      sampleMap = sampleMap, colData = sample.info, genome = "hg19") 
#   })
#   expect_equal(metadata(mae)$genome,"hg19")
#   expect_false(metadata(mae)$TCGA)
#   expect_equal(dim(getExp(mae)),c(2,2))
#   expect_equal(dim(getMet(mae)),c(2,2))
#   expect_equal(assay(getMet(mae)),as.matrix(dna.met))
#   expect_equal(assay(getExp(mae)),as.matrix(gene.exp))
#   expect_equal(colData(mae),sample.info)
#   expect_true(all(sampleMap(mae)$assay %in% c("DNA methylation","Gene expression")))
#   expect_true(all(c("external_gene_name","ensembl_gene_id") %in% colnames(values(getExp(mae)))))
# })
# 
# test_that("The creation of a using Summarized Experiment objects and TCGA data", {
#   # NON TCGA example: matrices has diffetrent column names
#   gene.exp <- DataFrame(sample1.exp = c("ENSG00000141510"=2.3,"ENSG00000171862"=5.4),
#                         sample2.exp = c("ENSG00000141510"=1.6,"ENSG00000171862"=2.3)
#   )
#   dna.met <- DataFrame(sample1.met = c("cg14324200"=0.5,"cg23867494"=0.1),
#                        sample2.met =  c("cg14324200"=0.3,"cg23867494"=0.9)
#   )
#   sample.info <- DataFrame(sample.type = c("Normal", "Tumor"))
#   rownames(sample.info) <- c("sample1","sample2")
#   sampleMap <- DataFrame(primary = c("sample1","sample1","sample2","sample2"), 
#                          colname = c("sample1.exp","sample1.met","sample2.exp","sample2.met"))
#   
#   suppressMessages({
#     mae <- createMAE(exp = gene.exp, met = dna.met, 
#                      sampleMap = sampleMap, colData = sample.info, genome = "hg19") 
#   })
#   expect_equal(metadata(mae)$genome,"hg19")
#   expect_false(metadata(mae)$TCGA)
#   expect_equal(dim(getExp(mae)),c(2,2))
#   expect_equal(dim(getMet(mae)),c(2,2))
#   expect_equal(assay(getMet(mae)),as.matrix(dna.met))
#   expect_equal(assay(getExp(mae)),as.matrix(gene.exp))
#   expect_equal(colData(mae),sample.info)
#   expect_true(all(sampleMap(mae)$assay %in% c("DNA methylation","Gene expression")))
#   expect_true(all(c("external_gene_name","ensembl_gene_id") %in% colnames(values(getExp(mae)))))
#   
# })
# 
# test_that("The creation of a using Summarized Experiment objects and TCGA data", {
#   
#   # TCGA example using TCGAbiolinks
#   # Testing creating MultyAssayExperiment object
#   # Load library
#   # Consisering it is TCGA and SE
#   data <- ELMER:::getdata("elmer.data.example") # Get data from ELMER.data
#   
#   suppressMessages({
#     mae <- createMAE(exp = getExp(data), 
#                      met =  getMet(data), 
#                      TCGA = TRUE, genome = "hg19")
#   })
#   expect_equal(metadata(mae)$genome,"hg19")
#   expect_true(metadata(mae)$TCGA)
#   expect_true(all(sampleMap(mae)$assay %in% c("DNA methylation","Gene expression")))
#   expect_true(all(c("external_gene_name","ensembl_gene_id") %in% colnames(values(getExp(mae)))))
#   expect_equal(dim(getMet(mae)),c(101,234))
#   expect_equal(dim(getExp(mae)),c(1026,234))
#   
#   
#   suppressMessages({
#     mae <- createMAE(exp = getExp(data), 
#                      met =  getMet(data), 
#                      TCGA = TRUE, 
#                      genome = "hg38")
#   })
#   expect_equal(metadata(mae)$genome,"hg38")
#   expect_true(metadata(mae)$TCGA)
#   expect_true(all(sampleMap(mae)$assay %in% c("DNA methylation","Gene expression")))
#   expect_true(all(c("external_gene_name","ensembl_gene_id") %in% colnames(values(getExp(mae)))))
#   expect_equal(dim(getMet(mae)),c(101,234))
#   expect_equal(dim(getExp(mae)),c(1026,234))
#   
#   # Consisering it is TCGA and not SE
#   
#   suppressMessages({
#     mae <- createMAE(exp = assay(getExp(data)), met =  assay(getMet(data)), 
#                      TCGA = TRUE, genome = "hg19")
#   })
#   expect_equal(metadata(mae)$genome,"hg19")
#   
#   suppressMessages({
#     mae <- createMAE(exp = assay(getExp(data)), 
#                      met =  assay(getMet(data)), 
#                      TCGA = TRUE, genome = "hg38")
#   })
#   expect_equal(metadata(mae)$genome,"hg38")
#   
#   # Consisering it is not TCGA and SE
#   # DNA methylation and gene expression Objects should have same sample names in columns
#   not.tcga.exp <- assay(getExp(data)) 
#   colnames(not.tcga.exp) <- substr(colnames(not.tcga.exp),1,15)
#   not.tcga.met <- assay(getMet(data)) 
#   colnames(not.tcga.met) <- substr(colnames(not.tcga.met),1,15)
#   
#   phenotype.data <- data.frame(row.names = colnames(not.tcga.exp), 
#                                samples = colnames(not.tcga.exp), 
#                                group = c(rep("group1", length(colnames(not.tcga.exp)) / 2 ), 
#                                          rep("group2", length(colnames(not.tcga.exp)) /2 )))
#   
#   suppressMessages({
#     mae <- createMAE(exp = not.tcga.exp, met =  not.tcga.met,
#                      TCGA = FALSE, genome = "hg19", colData = phenotype.data)
#   })
#   
# })

# 
# test_that("Number of probes in MAE matches the distal probes", {
#   library(TCGAbiolinks)
#   library(dplyr)
#   gcimp.samples <- TCGAquery_subtype("lgg") %>% dplyr::filter(base::grepl("G-CIMP",Supervised.DNA.Methylation.Cluster,ignore.case = T))
#   #-----------------------------------
#   # 2 - Get data
#   # ----------------------------------
#   #-----------------------------------
#   # 2.1 - DNA Methylation
#   # ----------------------------------
#   query <- GDCquery(project = "TCGA-LGG", 
#                     data.category = "DNA Methylation",
#                     platform = "Illumina Human Methylation 450", 
#                     barcode =  gcimp.samples$patient[1:3])
#   GDCdownload(query)
#   met <- GDCprepare(query, save = FALSE)
#   #-----------------------------------
#   # 2 - Expression
#   # ----------------------------------
#   query <- GDCquery(project = "TCGA-LGG", 
#                     data.category = "Transcriptome Profiling", 
#                     data.type = "Gene Expression Quantification", 
#                     workflow.type = "HTSeq - FPKM-UQ",
#                     barcode =   gcimp.samples$patient[1:3])
#   GDCdownload(query)
#   exp <- GDCprepare(query, save = FALSE)
#   for(genome in c("hg38","hg19")){
#     distal.probe <- get.feature.probe(genome = genome, met.platform = "450K")
#     mae <- createMAE(exp           = exp, 
#                      met           = met,
#                      genome        = genome, 
#                      met.platform  = "450K", 
#                      linearize.exp = TRUE, 
#                      met.na.cut    = 1.1,
#                      filter.probes = distal.probe, 
#                      TCGA          = TRUE) 
#     
#     expect_equal(length(distal.probe),nrow(getMet(mae)))
#     expect_equal(metadata(mae)$genome,genome)
#     expect_true("TN" %in% colnames(colData(mae)))
#   }
#   unlink("GDCdata",recursive = TRUE, force = TRUE)
# })
# 
# test_that("Adding mutation column is working", {
#   data <- tryCatch(ELMER:::getdata("elmer.data.example"), error = function(e) {
#     message(e)
#     data(elmer.data.example, envir = environment())
#   })
#   suppressMessages({
#     data <- createMAE(exp = getExp(data), 
#                      met =  getMet(data), 
#                      TCGA = TRUE, 
#                      genome = "hg38")
#   })
#   data <- addMutCol(data, "LUSC","LDHD")
#   expect_true("LDHD" %in% colnames(colData(data)))
#   expect_true("WT" %in% colData(data)$LDHD)
#   expect_true("Mutant" %in% colData(data)$LDHD)
#   expect_true("Normal" %in% colData(data)$LDHD)
# })