tests/testthat/test_agregation.R
In prostarproteomics/DAPAR: Tools for the Differential Analysis of Proteins Abundance with R
context("Agregation peptides to proteins")
require(DAPARdata)
library(testthat)
test_that("metacombine()", {
met <- c('Quant. by direct id', 'Missing POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'STOP')
met <- c('Quant. by direct id')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quant. by direct id')
met <- c('Quant. by recovery')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quant. by recovery')
met <- c('Quant. by recovery', 'Quant. by direct id')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quantified')
met <- c('Quant. by recovery', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by direct id', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by direct id', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed POV', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Imputed POV')
met <- c('Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, "Imputed MEC")
met <- c('Imputed POV', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, "Imputed")
})
#
# #########################################################
# test_that("Build Adjacency Matrix with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
#
# matUnique <- matrix(rep(0,72), 9,8, dimnames=list(c(0:8), c("1212", "253", "360", "375", "1050", "1995", "595", "856")))
# matUnique[1,1] <- matUnique[2:3,2] <- matUnique[4,3] <- matUnique[5,4] <- matUnique[6,5] <- matUnique[7,6] <- matUnique[8,7] <- matUnique[9,8] <- 1
#
#
#
# matShared <-matrix(rep(0,100), 10,10, dimnames=list(c(0:9),NULL))
# matShared[1,1] <- matShared[2:3,2]<- matShared[4,3] <- matShared[5,4] <- matShared[6,5] <- matShared[7,6] <- matShared[8,7] <- matShared[9,8] <- matShared[10,9] <-matShared[10,10] <- 1
#
# computedMatUnique <- BuildAdjacencyMatrix(obj,
# "Protein.group.IDs",
# unique=TRUE)
# computedMatShared <- BuildAdjacencyMatrix(obj,
# "Protein.group.IDs",
# unique=FALSE)
# colnames(computedMatShared) <- NULL
#
# expect_equal(as(matUnique, "dgCMatrix"), computedMatUnique[,colnames(computedMatUnique)])
# expect_equal(as(matShared, "dgCMatrix"), computedMatShared)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Sum of shared peptides using sparse Matrices", {
#
# require(DAPARdata)
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
#
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# sumShared <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000, 0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839, 21.811, 23.116, 21.859, 22.157, 0.000,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299),byrow=TRUE, 10,6,
# dimnames=list(c("1212","253","360","375","1050","1995" ,"595", "856","115" ,"114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212","253","360","375","1050","1995" ,"595", "856","115" ,"114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# sumOfMatShared <- SumPeptides(computedMShared, Biobase::exprs(obj))
# expect_equal(as(sumShared, "dgeMatrix"), round(sumOfMatShared$matfin, digits = 3))
# expect_equal(as(peptSharedUsed, "dgeMatrix"), sumOfMatShared$nbpep)
# })
#
#
#
#
#
# #########################################################
# test_that("Sum of unique peptides with sparse Matrices", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# sumUnique <- matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 48.949,48.702,48.546,49.512,49.208,49.416,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"), c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# sumOfMatUnique <- SumPeptides(computedMUnique, Biobase::exprs(obj))
# expect_equal(as(sumUnique, "dgeMatrix"),round(sumOfMatUnique$matfin, digits=3))
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), sumOfMatUnique$nbpep)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Mean of unique peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# meanUnique <- matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 24.474,24.351,24.273,24.756,24.604,24.708,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000
# ),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
# meanOfMatUnique <- MeanPeptides(computedMUnique, exprs(obj))
# expect_equal(as(meanUnique, "dgeMatrix"), round(meanOfMatUnique$matfin, digits=3))
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), meanOfMatUnique$nbpep)
# })
#
#
#
#
#
# #########################################################
# test_that("Mean of SHARED peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# meanShared <-
# matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 24.474,24.351,24.273,24.756,24.604,24.708,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000,
# 31.092,31.104,31.195,31.208,31.213,31.299,
# 31.092,31.104,31.195,31.208,31.213,31.299),
# byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
# meanOfMatShared <- MeanPeptides(computedMShared, Biobase::exprs(obj))
# expect_equal(as(meanShared, "dgeMatrix"), round(meanOfMatShared$matfin, digits=3), tolerance=1e-5)
# expect_equal(as(peptSharedUsed, "dgeMatrix"),meanOfMatShared$nbpep)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Top 3 of SHARED peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# n <- 3
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# topnShared <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000, 0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839, 21.811, 23.116, 21.859, 22.157, 0.000,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299),
# byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# topnOfMatShared <- TopnPeptides(computedMShared, Biobase::exprs(obj), n)
# expect_equal(as(topnShared, "dgeMatrix"), topnOfMatShared$matfin, tolerance=1e-5)
# expect_equal(as(peptSharedUsed, "dgeMatrix"),topnOfMatShared$nbpep)
# })
#
#
#
#
#
#
#
#
# #########################################################
# test_that("Top 3 of UNIQUE peptides with sparse matrices", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# n <- 3
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# topnUnique <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000 ,0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839 ,21.811, 23.116, 21.859, 22.157, 0.000),
# byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c(1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# topnOfMatUnique <- TopnPeptides(computedMUnique, Biobase::exprs(obj), n)
# expect_equal(as(topnUnique, "dgeMatrix"), topnOfMatUnique$matfin , tolerance=1e-5)
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), topnOfMatUnique$nbpep)
# })
prostarproteomics/DAPAR documentation built on March 28, 2024, 4:44 a.m.
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context("Agregation peptides to proteins")
require(DAPARdata)
library(testthat)
test_that("metacombine()", {
met <- c('Quant. by direct id', 'Missing POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'STOP')
met <- c('Quant. by direct id')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quant. by direct id')
met <- c('Quant. by recovery')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quant. by recovery')
met <- c('Quant. by recovery', 'Quant. by direct id')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Quantified')
met <- c('Quant. by recovery', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by direct id', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by direct id', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Quant. by recovery', 'Quant. by direct id', 'Imputed POV', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Combined tags')
met <- c('Imputed POV')
tag <- metacombine(met, 'peptide')
expect_equal(tag, 'Imputed POV')
met <- c('Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, "Imputed MEC")
met <- c('Imputed POV', 'Imputed MEC')
tag <- metacombine(met, 'peptide')
expect_equal(tag, "Imputed")
})
#
# #########################################################
# test_that("Build Adjacency Matrix with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
#
# matUnique <- matrix(rep(0,72), 9,8, dimnames=list(c(0:8), c("1212", "253", "360", "375", "1050", "1995", "595", "856")))
# matUnique[1,1] <- matUnique[2:3,2] <- matUnique[4,3] <- matUnique[5,4] <- matUnique[6,5] <- matUnique[7,6] <- matUnique[8,7] <- matUnique[9,8] <- 1
#
#
#
# matShared <-matrix(rep(0,100), 10,10, dimnames=list(c(0:9),NULL))
# matShared[1,1] <- matShared[2:3,2]<- matShared[4,3] <- matShared[5,4] <- matShared[6,5] <- matShared[7,6] <- matShared[8,7] <- matShared[9,8] <- matShared[10,9] <-matShared[10,10] <- 1
#
# computedMatUnique <- BuildAdjacencyMatrix(obj,
# "Protein.group.IDs",
# unique=TRUE)
# computedMatShared <- BuildAdjacencyMatrix(obj,
# "Protein.group.IDs",
# unique=FALSE)
# colnames(computedMatShared) <- NULL
#
# expect_equal(as(matUnique, "dgCMatrix"), computedMatUnique[,colnames(computedMatUnique)])
# expect_equal(as(matShared, "dgCMatrix"), computedMatShared)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Sum of shared peptides using sparse Matrices", {
#
# require(DAPARdata)
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
#
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# sumShared <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000, 0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839, 21.811, 23.116, 21.859, 22.157, 0.000,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299),byrow=TRUE, 10,6,
# dimnames=list(c("1212","253","360","375","1050","1995" ,"595", "856","115" ,"114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212","253","360","375","1050","1995" ,"595", "856","115" ,"114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# sumOfMatShared <- SumPeptides(computedMShared, Biobase::exprs(obj))
# expect_equal(as(sumShared, "dgeMatrix"), round(sumOfMatShared$matfin, digits = 3))
# expect_equal(as(peptSharedUsed, "dgeMatrix"), sumOfMatShared$nbpep)
# })
#
#
#
#
#
# #########################################################
# test_that("Sum of unique peptides with sparse Matrices", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# sumUnique <- matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 48.949,48.702,48.546,49.512,49.208,49.416,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"), c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# sumOfMatUnique <- SumPeptides(computedMUnique, Biobase::exprs(obj))
# expect_equal(as(sumUnique, "dgeMatrix"),round(sumOfMatUnique$matfin, digits=3))
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), sumOfMatUnique$nbpep)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Mean of unique peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# meanUnique <- matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 24.474,24.351,24.273,24.756,24.604,24.708,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000
# ),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
# meanOfMatUnique <- MeanPeptides(computedMUnique, exprs(obj))
# expect_equal(as(meanUnique, "dgeMatrix"), round(meanOfMatUnique$matfin, digits=3))
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), meanOfMatUnique$nbpep)
# })
#
#
#
#
#
# #########################################################
# test_that("Mean of SHARED peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# meanShared <-
# matrix(c(25.278,24.996,24.487,25.502,25.025,24.691,
# 24.474,24.351,24.273,24.756,24.604,24.708,
# 24.088,23.866,24.335,24.532,24.674,24.766,
# 24.607,24.836,24.414,24.455,24.608,24.921,
# 0.000,0.000,0.000,0.000,22.180,21.932,
# 24.684,24.302,24.255,24.937,24.614,24.584,
# 27.113,27.180,27.270,27.380,27.351,27.383,
# 21.839,21.811,23.116,21.859,22.157,0.000,
# 31.092,31.104,31.195,31.208,31.213,31.299,
# 31.092,31.104,31.195,31.208,31.213,31.299),
# byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
# meanOfMatShared <- MeanPeptides(computedMShared, Biobase::exprs(obj))
# expect_equal(as(meanShared, "dgeMatrix"), round(meanOfMatShared$matfin, digits=3), tolerance=1e-5)
# expect_equal(as(peptSharedUsed, "dgeMatrix"),meanOfMatShared$nbpep)
# })
#
#
#
#
#
#
# #########################################################
# test_that("Top 3 of SHARED peptides with sparse Matrix", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# n <- 3
# protID <- "Protein.group.IDs"
#
# computedMShared <- BuildAdjacencyMatrix(obj, protID, unique=FALSE)
# topnShared <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000, 0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839, 21.811, 23.116, 21.859, 22.157, 0.000,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299,
# 31.092, 31.104, 31.195, 31.208, 31.213, 31.299),
# byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptSharedUsed <- matrix(c( 1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 10,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856", "115", "114"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# topnOfMatShared <- TopnPeptides(computedMShared, Biobase::exprs(obj), n)
# expect_equal(as(topnShared, "dgeMatrix"), topnOfMatShared$matfin, tolerance=1e-5)
# expect_equal(as(peptSharedUsed, "dgeMatrix"),topnOfMatShared$nbpep)
# })
#
#
#
#
#
#
#
#
# #########################################################
# test_that("Top 3 of UNIQUE peptides with sparse matrices", {
#
# data(Exp1_R2_pept)
# obj <- Exp1_R2_pept[1:10]
# n <- 3
# protID <- "Protein.group.IDs"
#
# computedMUnique <- BuildAdjacencyMatrix(obj, protID, unique=TRUE)
# topnUnique <- matrix(c( 25.278, 24.996, 24.487, 25.502, 25.025, 24.691,
# 48.949, 48.702, 48.546, 49.512, 49.208, 49.416,
# 24.088, 23.866, 24.335, 24.532, 24.674, 24.766,
# 24.607, 24.836, 24.414, 24.455, 24.608, 24.921,
# 0.000, 0.000, 0.000 ,0.000, 22.180, 21.932,
# 24.684, 24.302, 24.255, 24.937, 24.614, 24.584,
# 27.113, 27.180, 27.270, 27.380, 27.351, 27.383,
# 21.839 ,21.811, 23.116, 21.859, 22.157, 0.000),
# byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("Intensity.D.R1", "Intensity.D.R2", "Intensity.D.R3", "Intensity.E.R1", "Intensity.E.R2", "Intensity.E.R3")))
#
# peptUniqueUsed <- matrix(c(1,1,1,1,1,1,
# 2,2,2,2,2,2,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1,
# 1,1,1,1,1,1),byrow=TRUE, 8,6,
# dimnames=list(c("1212", "253", "360", "375", "1050", "1995", "595", "856"),
# c("nb.pep.used.Intensity.D.R1", "nb.pep.used.Intensity.D.R2", "nb.pep.used.Intensity.D.R3", "nb.pep.used.Intensity.E.R1", "nb.pep.used.Intensity.E.R2", "nb.pep.used.Intensity.E.R3")))
#
#
# topnOfMatUnique <- TopnPeptides(computedMUnique, Biobase::exprs(obj), n)
# expect_equal(as(topnUnique, "dgeMatrix"), topnOfMatUnique$matfin , tolerance=1e-5)
# expect_equal(as(peptUniqueUsed, "dgeMatrix"), topnOfMatUnique$nbpep)
# })
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