Check results for 'evanverse'

using R Under development (unstable) (2026-03-18 r89649)
using platform: x86_64-apple-darwin20
R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 14.2.0
running under: macOS Ventura 13.3.1
using session charset: UTF-8 * current time: 2026-03-31 01:10:39 UTC
checking for file ‘evanverse/DESCRIPTION’ ... OK
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this is package ‘evanverse’ version ‘0.5.1’
package encoding: UTF-8
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checking whether package ‘evanverse’ can be installed ... [5s/5s] OK See the install log for details.
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checking tests ... [29s/35s] ERROR Running ‘testthat.R’ [29s/34s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(evanverse) > > test_check("evanverse") /Volumes/Temp/tmp/RtmpO1O5Pk/file1109e4e11bf33 +-- a.R /Volumes/Temp/tmp/RtmpO1O5Pk/file1109e530a654 ! P(1000, 999) exceeds double range and will return Inf. ! P(1000, 999) exceeds double range and will return Inf. i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. v Saved to '/Volumes/Temp/tmp/RtmpO1O5Pk/file1109e7ae09ef4.rds' i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. v Saved to '/Volumes/Temp/tmp/RtmpO1O5Pk/file1109e130cc475.rds' i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. Saving _problems/test-download-399.R v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/cp_test_69790/sequential/my_blues.json' v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/cp_json_69790/qualitative/qual_trio.json' v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/cp_ow_69790/sequential/blues.json' v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/cp_owt_69790/sequential/blues.json' i Overwriting existing palette: "blues" v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/cp_owt_69790/sequential/blues.json' v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/rm_test_69790/sequential/to_remove.json' v Removed "to_remove" from sequential v Palette saved: '/Volumes/Temp/tmp/RtmpO1O5Pk/rm_auto_69790/diverging/find_me.json' v Removed "find_me" from diverging v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 ! Failed to parse JSON: '/Volumes/Temp/tmp/RtmpO1O5Pk/pal_test_69790/sequential/broken.json' v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v CRAN mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/CRAN> v CRAN mirror set to: <https://mirrors.ustc.edu.cn/CRAN> v CRAN mirror set to: <https://mirrors.westlake.edu.cn/CRAN> v Bioconductor mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/bioconductor> v Bioconductor mirror set to: <https://mirrors.ustc.edu.cn/bioconductor> v CRAN mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/CRAN> v Bioconductor mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/bioconductor> v CRAN mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/CRAN> v Bioconductor mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/bioconductor> v CRAN mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/CRAN> v Bioconductor mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/bioconductor> v CRAN mirror set to: <https://cloud.r-project.org> v Bioconductor mirror set to: <https://bioconductor.org> v CRAN mirror set to: <https://mirrors.tuna.tsinghua.edu.cn/CRAN> v Installed: stats v Installed: stats v Installed: stats v Installed: utils v Installed: cli x Power: 47.8% (very low) | Two-sample t-test n = 30 per group, effect size = 0.500, alpha = 0.050 With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. x Power: 47.8% (very low) | Two-sample t-test n = 30 per group, effect size = 0.500, alpha = 0.050 With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Statistical Power Analysis -------------------------------------------------- -- Parameters -- Test: Two-sample t-test n: 30 per group Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- x Power (1−β): 47.79% (very low) -- Interpretation -- With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Recommendation -- i To reach 80% power, increase n from 30 to 64 per group. -- Statistical Power Analysis -------------------------------------------------- -- Parameters -- Test: Two-sample t-test n: 30 per group Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- x Power (1−β): 47.79% (very low) -- Interpretation -- With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Recommendation -- i To reach 80% power, increase n from 30 to 64 per group. v n = 64 per group (128 total) | Two-sample t-test Target power = 80%, effect size = 0.500, alpha = 0.050 To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). v n = 64 per group (128 total) | Two-sample t-test Target power = 80%, effect size = 0.500, alpha = 0.050 To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Sample Size Estimation ------------------------------------------------------ -- Parameters -- Test: Two-sample t-test Target power: 80% (0.8000) Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- v n per group: 64 v n total: 128 -- Interpretation -- To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Recommendation -- i Recruit 10–20% extra to account for dropout, missing data, or protocol violations. -- Sample Size Estimation ------------------------------------------------------ -- Parameters -- Test: Two-sample t-test Target power: 80% (0.8000) Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- v n per group: 64 v n total: 128 -- Interpretation -- To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Recommendation -- i Recruit 10–20% extra to account for dropout, missing data, or protocol violations. t.test | p < 0.001* | A n=30, B n=30 t.test | p < 0.001* | A n=30, B n=30 -- Two-group Comparison -------------------------------------------------------- -- Parameters -- Test: Welch two-sample t-test Direction: A - B Alternative: two.sided alpha: 0.050 Paired: FALSE -- Result -- v p < 0.001 (significant at alpha = 0.05) Welch Two Sample t-test data: value by group t = -4.7184, df = 56.741, p-value = 1.594e-05 alternative hypothesis: true difference in means between group A and group B is not equal to 0 95 percent confidence interval: -1.4961113 -0.6045215 sample estimates: mean in group A mean in group B 0.08245817 1.13277458 -- Descriptive statistics -- # A tibble: 2 x 7 group n mean sd median min max <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> 1 A 30 0.0825 0.924 0.257 -2.21 1.60 2 B 30 1.13 0.795 0.943 -0.377 2.98 -- Normality (Shapiro-Wilk) -- A: n = 30, p = 0.170 B: n = 30, p = 0.948 → Medium samples (min n = 30). Data reasonably normal (all Shapiro p ≥ 0.01). -- Two-group Comparison -------------------------------------------------------- -- Parameters -- Test: Welch two-sample t-test Direction: A - B Alternative: two.sided alpha: 0.050 Paired: FALSE -- Result -- v p < 0.001 (significant at alpha = 0.05) Welch Two Sample t-test data: value by group t = -4.7184, df = 56.741, p-value = 1.594e-05 alternative hypothesis: true difference in means between group A and group B is not equal to 0 95 percent confidence interval: -1.4961113 -0.6045215 sample estimates: mean in group A mean in group B 0.08245817 1.13277458 -- Descriptive statistics -- # A tibble: 2 x 7 group n mean sd median min max <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> 1 A 30 0.0825 0.924 0.257 -2.21 1.60 2 B 30 1.13 0.795 0.943 -0.377 2.98 -- Normality (Shapiro-Wilk) -- A: n = 30, p = 0.170 B: n = 30, p = 0.948 → Medium samples (min n = 30). Data reasonably normal (all Shapiro p ≥ 0.01). One-way ANOVA | p < 0.001* | A n=25, B n=25, C n=25 One-way ANOVA | p < 0.001* | A n=25, B n=25, C n=25 -- One-way Comparison ---------------------------------------------------------- -- Parameters -- Test: One-way ANOVA alpha: 0.050 -- Omnibus Test -- v p < 0.001 (significant at alpha = 0.05) eta_squared = 0.357, omega_squared = 0.336 Df Sum Sq Mean Sq F value Pr(>F) group 2 30.11 15.054 19.99 1.24e-07 *** Residuals 72 54.21 0.753 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -- Descriptive statistics -- # A tibble: 3 x 7 group n mean sd median min max <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> 1 A 25 -0.289 0.774 -0.308 -1.67 1.27 2 B 25 0.661 0.955 0.848 -1.77 2.20 3 C 25 1.25 0.865 1.46 -0.537 2.56 -- Normality (Shapiro-Wilk) -- A: n = 25, p = 0.267 B: n = 25, p = 0.211 C: n = 25, p = 0.264 -> Small samples (min n = 25). Data appears normal (all Shapiro p ≥ 0.05). -- Variance (Levene's test) -- p = 0.467 | equal variances: TRUE -- Post-hoc (tukey) -- # A tibble: 3 x 6 group2 group1 diff lwr upr `p adj` <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 B A 0.950 0.362 1.54 0.000687 2 C A 1.54 0.951 2.13 0.0000000721 3 C B 0.588 0.000817 1.18 0.0496 -- One-way Comparison ---------------------------------------------------------- -- Parameters -- Test: One-way ANOVA alpha: 0.050 -- Omnibus Test -- v p < 0.001 (significant at alpha = 0.05) eta_squared = 0.357, omega_squared = 0.336 Df Sum Sq Mean Sq F value Pr(>F) group 2 30.11 15.054 19.99 1.24e-07 *** Residuals 72 54.21 0.753 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -- Descriptive statistics -- # A tibble: 3 x 7 group n mean sd median min max <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl> 1 A 25 -0.289 0.774 -0.308 -1.67 1.27 2 B 25 0.661 0.955 0.848 -1.77 2.20 3 C 25 1.25 0.865 1.46 -0.537 2.56 -- Normality (Shapiro-Wilk) -- A: n = 25, p = 0.267 B: n = 25, p = 0.211 C: n = 25, p = 0.264 -> Small samples (min n = 25). Data appears normal (all Shapiro p ≥ 0.05). -- Variance (Levene's test) -- p = 0.467 | equal variances: TRUE -- Post-hoc (tukey) -- # A tibble: 3 x 6 group2 group1 diff lwr upr `p adj` <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 B A 0.950 0.362 1.54 0.000687 2 C A 1.54 0.951 2.13 0.0000000721 3 C B 0.588 0.000817 1.18 0.0496 Chi-square test | p = 0.3156 | 3x2 | V = 0.152 (small) Chi-square test | p = 0.3156 | 3x2 | V = 0.152 (small) -- Categorical Association Test ------------------------------------------------ -- Parameters -- Test: Chi-square test Variables: treatment × response Table size: 3x2 alpha: 0.050 -- Result -- i p = 0.3156 (not significant at alpha = 0.05) Pearson's Chi-squared test data: cont_table X-squared = 2.3064, df = 2, p-value = 0.3156 -- Effect Size (Cramer's V) -- V: 0.152 Interpretation: small -- Observed Frequencies -- No Yes A 12 24 B 16 17 C 10 21 -- Expected Frequencies -- No Yes A 13.68 22.32 B 12.54 20.46 C 11.78 19.22 -- Pearson Residuals -- No Yes A -0.45 0.36 B 0.98 -0.76 C -0.52 0.41 → |residual| > 2 indicates significant deviation from independence -- Method Selection -- Table size: 3x2 Total N: 100 Min expected freq: 11.78 Cells with freq < 5: 0 Decision: All expected frequencies adequate: using standard chi-square test -- Categorical Association Test ------------------------------------------------ -- Parameters -- Test: Chi-square test Variables: treatment × response Table size: 3x2 alpha: 0.050 -- Result -- i p = 0.3156 (not significant at alpha = 0.05) Pearson's Chi-squared test data: cont_table X-squared = 2.3064, df = 2, p-value = 0.3156 -- Effect Size (Cramer's V) -- V: 0.152 Interpretation: small -- Observed Frequencies -- No Yes A 12 24 B 16 17 C 10 21 -- Expected Frequencies -- No Yes A 13.68 22.32 B 12.54 20.46 C 11.78 19.22 -- Pearson Residuals -- No Yes A -0.45 0.36 B 0.98 -0.76 C -0.52 0.41 → |residual| > 2 indicates significant deviation from independence -- Method Selection -- Table size: 3x2 Total N: 100 Min expected freq: 11.78 Cells with freq < 5: 0 Decision: All expected frequencies adequate: using standard chi-square test i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 3 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 10 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. pearson | 4 vars | 0/6 significant pairs (alpha = 0.05) pearson | 4 vars | 0/6 significant pairs (alpha = 0.05) i Found 0 significant pairs out of 6 tests. -- Correlation Analysis -------------------------------------------------------- -- Parameters -- Method: pearson Missing obs: pairwise.complete.obs P-adjust: none Variables: 4 alpha: 0.050 -- Descriptive Statistics -- variable n mean sd median min max x1 50 0.064934373 1.0686820 -0.14079713 -2.183967 2.215461 x2 50 -0.001664339 0.8130295 -0.06993174 -2.102329 2.387233 x3 50 -0.033696299 1.1076103 0.01153808 -1.995387 2.600142 x4 50 0.066717211 0.9896570 -0.02757658 -2.621345 2.246255 -- Correlation Summary -- Min: -0.136 Max: 0.262 Mean |r|: 0.143 -- Significant Pairs -- i Based on unadjusted p-values. 0 out of 6 pairs significant at alpha = 0.05 -- Correlation Analysis -------------------------------------------------------- -- Parameters -- Method: pearson Missing obs: pairwise.complete.obs P-adjust: none Variables: 4 alpha: 0.050 -- Descriptive Statistics -- variable n mean sd median min max x1 50 0.064934373 1.0686820 -0.14079713 -2.183967 2.215461 x2 50 -0.001664339 0.8130295 -0.06993174 -2.102329 2.387233 x3 50 -0.033696299 1.1076103 0.01153808 -1.995387 2.600142 x4 50 0.066717211 0.9896570 -0.02757658 -2.621345 2.246255 -- Correlation Summary -- Min: -0.136 Max: 0.262 Mean |r|: 0.143 -- Significant Pairs -- i Based on unadjusted p-values. 0 out of 6 pairs significant at alpha = 0.05 i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Created directory: '/Volumes/Temp/tmp/RtmpO1O5Pk/evanverse_dest_1109e5155b8d4/nested' [ FAIL 1 | WARN 0 | SKIP 9 | PASS 906 ] ══ Skipped tests (9) ═══════════════════════════════════════════════════════════ • On CRAN (8): 'test-download.R:94:3', 'test-download.R:190:3', 'test-download.R:200:3', 'test-download.R:341:3', 'test-download.R:425:3', 'test-pkg.R:362:3', 'test-pkg.R:373:3', 'test-pkg.R:385:3' • {GEOquery} cannot be loaded (1): 'test-download.R:408:3' ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test-download.R:399:3'): download_geo orchestrates helpers and returns correct list structure ── Error: Please install GEOquery: BiocManager::install('GEOquery') Backtrace: ▆ 1. ├─base::suppressWarnings(download_geo("GSE99999", dest_dir = tmp)) at test-download.R:399:3 2. │ └─base::withCallingHandlers(...) 3. └─evanverse::download_geo("GSE99999", dest_dir = tmp) 4. └─cli::cli_abort(...) 5. └─rlang::abort(...) [ FAIL 1 | WARN 0 | SKIP 9 | PASS 906 ] Error: ! Test failures. Execution halted
checking for unstated dependencies in vignettes ... OK
checking package vignettes ... OK
checking re-building of vignette outputs ... [22s/23s] OK
checking PDF version of manual ... [7s/7s] OK
DONE Status: 1 ERROR
using check arguments '--no-clean-on-error '