tests/testthat/test_hypotesting.R
In SciDoPhenIA/phenomis: Analysis of single and multiple phenomic data sets
testthat::context("Testing 'hypotesting'")
testthat::test_that("ttest", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics", package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
# .twoSampCorTests
ttestLs <- phenomis:::.twoSampCorTests(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "ttest",
factorNameC = "gender",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(ttestLs[["feat.df"]]["Testosterone glucuronide", "ttest_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(ttestLs[["feat.df"]]["Testosterone glucuronide", "ttest_gender_Female.Male_BH"],
9.054552e-10,
tolerance = 1e-6)
testthat::expect_equivalent(ttestLs[["feat.df"]]["1,7-Dimethyluric acid", "ttest_gender_Female.Male_BH"],
0.5868704,
tolerance = 1e-6)
# se
sacurine.se <- hypotesting(sacurine.se,
test.c = "ttest",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Female.Male_BH"],
9.054552e-10,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1,7-Dimethyluric acid", "ttest_gender_Female.Male_BH"],
0.5868704,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "ttest",
factor_names.vc = "gender",
factor_levels.ls = list(factor1 = c("Male", "Female")),
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Male.Female_diff"],
-2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Male.Female_BH"],
9.054552e-10,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "wilcoxon",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "wilcoxon_gender_Female.Male_diff"],
1.919634,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "wilcoxon_gender_Female.Male_BH"],
3.957732e-12,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1-Methylxanthine", "wilcoxon_gender_Female.Male_BH"],
0.03904366,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "limma",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "limma_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "limma_gender_Female.Male_BH"],
1.221723e-11,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1-Methylxanthine", "limma_gender_Female.Male_BH"],
0.07010866,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se, "pearson", "age")
# mset
prometis.mset <- reading(system.file("extdata/prometis", package = "phenomis"), output.c = "set")
prometis.mset <- hypotesting(prometis.mset,
test.c = "ttest",
factor_names.vc = "gene",
figure.c = "none",
report.c = "none")
testthat::expect_identical(sapply(Biobase::fData(prometis.mset),
function(fdaDF) {
sum(fdaDF[, "ttest_gene_KO.WT_signif"])
}),
c(metabolomics = 2, proteomics = 7))
})
testthat::test_that("anova", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics",
package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
colData(sacurine.se)[, "ageGroup"] <- vapply(colData(sacurine.se)[, "age"],
function(x) {
if (x < 35) {
return("thirty")
} else if (x < 50) {
return("fourty")
} else {
return("fifty")}},
FUN.VALUE = character(1))
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "anova",
factorNameC = "ageGroup",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_BH"],
0.003023911,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_fourty.thirty_diff"],
-0.8841594,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_fifty.thirty_BH"],
0.01544621,
tolerance = 1e-6)
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "anova",
factorNameC = "ageGroup",
factorLevelsVc = c("thirty", "fourty", "fifty"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_thirty.fourty_diff"],
0.8841594,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_thirty.fourty_BH"],
0.01602643,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["Testosterone glucuronide", "anova_ageGroup_thirty.fifty_diff"],
-2.314257,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["Testosterone glucuronide", "anova_ageGroup_thirty.fifty_BH"],
9.217707e-05,
tolerance = 1e-6)
})
testthat::test_that("kruskal", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics",
package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
colData(sacurine.se)[, "ageGroup"] <- vapply(colData(sacurine.se)[, "age"],
function(x) {
if (x < 35) {
return("thirty")
} else if (x < 50) {
return("fourty")
} else {
return("fifty")}},
FUN.VALUE = character(1))
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "kruskal",
factorNameC = "ageGroup",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "testthat_",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "testthat_kruskal_ageGroup_fourty.thirty_BH"],
0.03497385,
tolerance = 1e-6)
})
testthat::test_that("anova2ways", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2ways
anova2ways.ls <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "prefix_",
figure.c = "none")
testthat::expect_equivalent(anova2ways.ls[["metric.mn"]]["v11", "prefix_anova2ways_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2ways.ls[["feat.df"]]["v6", "prefix_anova2ways_gene_WT.KO_BH"],
0.800139,
tolerance = 1e-6)
anova2ways.ls <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2ways.ls[["metric.mn"]]["v11", "anova2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
})
testthat::test_that("anova2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2waysInter
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene_WT.KO_BH"],
0.8032291,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene:sex_BH"],
0.9967691,
tolerance = 1e-6)
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
})
testthat::test_that("anova2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2waysInter
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene_WT.KO_BH"],
0.8032291,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene:sex_BH"],
0.9967691,
tolerance = 1e-6)
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_BH"],
0.9069173,
tolerance = 1e-6)
})
testthat::test_that("limma2ways", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .limma2ways
limma2waysLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysLs[["metric.mn"]]["v11", "limma2ways_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysLs[["feat.df"]]["v6", "limma2ways_gene_WT.KO_BH"],
0.9296763,
tolerance = 1e-6)
limma2waysLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "testing_",
figure.c = "none")
testthat::expect_equivalent(limma2waysLs[["metric.mn"]]["v11", "testing_limma2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2ways_sex_F.M_BH"],
0.9077522,
tolerance = 1e-6)
})
testthat::test_that("limma2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .limma2waysInter
limma2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysInterLs[["metric.mn"]]["v11", "limma2waysInter_gene_WT.KO_diff"],
0.3291035,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysInterLs[["feat.df"]]["v11", "limma2waysInter_gene_WT.KO_BH"],
0.009124355,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysInterLs[["feat.df"]]["v6", "limma2waysInter_gene:sex_BH"],
0.996654,
tolerance = 1e-6)
limma2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysInterLs[["metric.mn"]]["v11", "limma2waysInter_gene_KO.WT_diff"],
-0.3291035,
tolerance = 1e-6)
testthat::expect_error(phenomis:.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2waysInter_gene_KO.WT_diff"],
-0.3291035,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2waysInter_gene_KO.WT_BH"],
0.009124355,
tolerance = 1e-6)
})
SciDoPhenIA/phenomis documentation built on June 9, 2022, 11:54 p.m.
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testthat::context("Testing 'hypotesting'")
testthat::test_that("ttest", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics", package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
# .twoSampCorTests
ttestLs <- phenomis:::.twoSampCorTests(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "ttest",
factorNameC = "gender",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(ttestLs[["feat.df"]]["Testosterone glucuronide", "ttest_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(ttestLs[["feat.df"]]["Testosterone glucuronide", "ttest_gender_Female.Male_BH"],
9.054552e-10,
tolerance = 1e-6)
testthat::expect_equivalent(ttestLs[["feat.df"]]["1,7-Dimethyluric acid", "ttest_gender_Female.Male_BH"],
0.5868704,
tolerance = 1e-6)
# se
sacurine.se <- hypotesting(sacurine.se,
test.c = "ttest",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Female.Male_BH"],
9.054552e-10,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1,7-Dimethyluric acid", "ttest_gender_Female.Male_BH"],
0.5868704,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "ttest",
factor_names.vc = "gender",
factor_levels.ls = list(factor1 = c("Male", "Female")),
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Male.Female_diff"],
-2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "ttest_gender_Male.Female_BH"],
9.054552e-10,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "wilcoxon",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "wilcoxon_gender_Female.Male_diff"],
1.919634,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "wilcoxon_gender_Female.Male_BH"],
3.957732e-12,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1-Methylxanthine", "wilcoxon_gender_Female.Male_BH"],
0.03904366,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se,
test.c = "limma",
factor_names.vc = "gender",
figure.c = "none",
report.c = "none")
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "limma_gender_Female.Male_diff"],
2.42603,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["Testosterone glucuronide", "limma_gender_Female.Male_BH"],
1.221723e-11,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(sacurine.se)["1-Methylxanthine", "limma_gender_Female.Male_BH"],
0.07010866,
tolerance = 1e-6)
sacurine.se <- hypotesting(sacurine.se, "pearson", "age")
# mset
prometis.mset <- reading(system.file("extdata/prometis", package = "phenomis"), output.c = "set")
prometis.mset <- hypotesting(prometis.mset,
test.c = "ttest",
factor_names.vc = "gene",
figure.c = "none",
report.c = "none")
testthat::expect_identical(sapply(Biobase::fData(prometis.mset),
function(fdaDF) {
sum(fdaDF[, "ttest_gene_KO.WT_signif"])
}),
c(metabolomics = 2, proteomics = 7))
})
testthat::test_that("anova", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics",
package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
colData(sacurine.se)[, "ageGroup"] <- vapply(colData(sacurine.se)[, "age"],
function(x) {
if (x < 35) {
return("thirty")
} else if (x < 50) {
return("fourty")
} else {
return("fifty")}},
FUN.VALUE = character(1))
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "anova",
factorNameC = "ageGroup",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_BH"],
0.003023911,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_fourty.thirty_diff"],
-0.8841594,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_fifty.thirty_BH"],
0.01544621,
tolerance = 1e-6)
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "anova",
factorNameC = "ageGroup",
factorLevelsVc = c("thirty", "fourty", "fifty"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_thirty.fourty_diff"],
0.8841594,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["1-Methylxanthine", "anova_ageGroup_thirty.fourty_BH"],
0.01602643,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["Testosterone glucuronide", "anova_ageGroup_thirty.fifty_diff"],
-2.314257,
tolerance = 1e-6)
testthat::expect_equivalent(feat.df["Testosterone glucuronide", "anova_ageGroup_thirty.fifty_BH"],
9.217707e-05,
tolerance = 1e-6)
})
testthat::test_that("kruskal", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics",
package = "phenomis"))
sacurine.se <- correcting(sacurine.se, figure.c = "none")
sacurine.se <- sacurine.se[, colData(sacurine.se)[, "sampleType"] != "pool"]
sacurine.se <- transforming(sacurine.se)
sacurine.se <- sacurine.se[, colnames(sacurine.se) != "HU_neg_096_b2"]
colData(sacurine.se)[, "ageGroup"] <- vapply(colData(sacurine.se)[, "age"],
function(x) {
if (x < 35) {
return("thirty")
} else if (x < 50) {
return("fourty")
} else {
return("fifty")}},
FUN.VALUE = character(1))
feat.df <- phenomis:::.anovas(data.mn = t(assay(sacurine.se)),
samp.df = colData(sacurine.se),
feat.df = rowData(sacurine.se),
test.c = "kruskal",
factorNameC = "ageGroup",
factorLevelsVc = "default",
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "testthat_",
figure.c = "none")[["feat.df"]]
testthat::expect_equivalent(feat.df["1-Methylxanthine", "testthat_kruskal_ageGroup_fourty.thirty_BH"],
0.03497385,
tolerance = 1e-6)
})
testthat::test_that("anova2ways", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2ways
anova2ways.ls <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "prefix_",
figure.c = "none")
testthat::expect_equivalent(anova2ways.ls[["metric.mn"]]["v11", "prefix_anova2ways_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2ways.ls[["feat.df"]]["v6", "prefix_anova2ways_gene_WT.KO_BH"],
0.800139,
tolerance = 1e-6)
anova2ways.ls <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2ways.ls[["metric.mn"]]["v11", "anova2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2ways",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
})
testthat::test_that("anova2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2waysInter
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene_WT.KO_BH"],
0.8032291,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene:sex_BH"],
0.9967691,
tolerance = 1e-6)
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
})
testthat::test_that("anova2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .anova2waysInter
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene_WT.KO_BH"],
0.8032291,
tolerance = 1e-6)
testthat::expect_equivalent(anova2waysInterLs[["feat.df"]]["v6", "anova2waysInter_gene:sex_BH"],
0.9967691,
tolerance = 1e-6)
anova2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(anova2waysInterLs[["metric.mn"]]["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "anova2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "anova2waysInter_sex_F.M_BH"],
0.9069173,
tolerance = 1e-6)
})
testthat::test_that("limma2ways", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .limma2ways
limma2waysLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysLs[["metric.mn"]]["v11", "limma2ways_sex_M.F_diff"],
-0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysLs[["feat.df"]]["v6", "limma2ways_gene_WT.KO_BH"],
0.9296763,
tolerance = 1e-6)
limma2waysLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "testing_",
figure.c = "none")
testthat::expect_equivalent(limma2waysLs[["metric.mn"]]["v11", "testing_limma2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_error(phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "limma2ways",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2ways_sex_F.M_diff"],
0.03642992,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2ways_sex_F.M_BH"],
0.9077522,
tolerance = 1e-6)
})
testthat::test_that("limma2waysInter", {
metabo.se <- reading(system.file("extdata/prometis/metabolomics",
package = "phenomis"))
## .limma2waysInter
limma2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1Vc = c("WT", "KO"),
factor2Vc = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysInterLs[["metric.mn"]]["v11", "limma2waysInter_gene_WT.KO_diff"],
0.3291035,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysInterLs[["feat.df"]]["v11", "limma2waysInter_gene_WT.KO_BH"],
0.009124355,
tolerance = 1e-6)
testthat::expect_equivalent(limma2waysInterLs[["feat.df"]]["v6", "limma2waysInter_gene:sex_BH"],
0.996654,
tolerance = 1e-6)
limma2waysInterLs <- phenomis:::.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = "default",
factor2 = "default"),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none")
testthat::expect_equivalent(limma2waysInterLs[["metric.mn"]]["v11", "limma2waysInter_gene_KO.WT_diff"],
-0.3291035,
tolerance = 1e-6)
testthat::expect_error(phenomis:.anovas2ways(data.mn = t(assay(metabo.se)),
samp.df = colData(metabo.se),
feat.df = rowData(metabo.se),
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
factor_levels.ls = list(factor1 = c("WT", "OK"),
factor2 = c("M", "F")),
adjust.c = "BH",
adjust_thresh.n = 0.05,
prefix.c = "",
figure.c = "none"))
metabo.se <- hypotesting(metabo.se,
test.c = "limma2waysInter",
factor_names.vc = c("gene", "sex"),
figure.c = "interactive",
report.c = "none")
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2waysInter_gene_KO.WT_diff"],
-0.3291035,
tolerance = 1e-6)
testthat::expect_equivalent(rowData(metabo.se)["v11", "limma2waysInter_gene_KO.WT_BH"],
0.009124355,
tolerance = 1e-6)
})
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