=== Log started: 2026-03-04 21:59:52.527294 === Session info: R version 4.5.2 (2025-10-31) Platform: x86_64-conda-linux-gnu Running under: Ubuntu 24.04.4 LTS Matrix products: default BLAS/LAPACK: /home/shared/8TB_HDD_02/shedurkin/.local/share/r-miniconda/envs/r_enet_rscript/lib/libopenblasp-r0.3.30.so; LAPACK version 3.12.0 locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C time zone: America/Los_Angeles tzcode source: system (glibc) attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets [8] methods base other attached packages: [1] pbapply_1.7-4 doParallel_1.0.17 [3] iterators_1.0.14 foreach_1.5.2 [5] scales_1.4.0 genefilter_1.80.3 [7] ggfortify_0.4.18 vegan_2.7-1 [9] permute_0.9-8 factoextra_1.0.7 [11] caret_7.0-1 lattice_0.22-7 [13] glmnet_4.1-10 Matrix_1.7-4 [15] pheatmap_1.0.13 rvest_1.0.5 [17] corrplot_0.95 ggcorrplot_0.1.4.1 [19] reshape2_1.4.4 edgeR_3.40.2 [21] limma_3.54.2 WGCNA_1.73 [23] fastcluster_1.3.0 dynamicTreeCut_1.63-1 [25] ggraph_2.2.1 tidygraph_1.3.1 [27] psych_2.5.6 igraph_2.1.4 [29] DESeq2_1.38.3 SummarizedExperiment_1.28.0 [31] Biobase_2.58.0 MatrixGenerics_1.10.0 [33] matrixStats_1.5.0 GenomicRanges_1.50.2 [35] GenomeInfoDb_1.34.9 IRanges_2.32.0 [37] S4Vectors_0.36.2 BiocGenerics_0.44.0 [39] lubridate_1.9.4 forcats_1.0.1 [41] stringr_1.6.0 dplyr_1.1.4 [43] purrr_1.2.0 readr_2.1.6 [45] tidyr_1.3.1 tibble_3.3.0 [47] ggplot2_3.5.2 tidyverse_2.0.0 loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 shape_1.4.6.1 rstudioapi_0.17.1 [4] magrittr_2.0.4 farver_2.1.2 rmarkdown_2.29 [7] zlibbioc_1.44.0 vctrs_0.6.5 memoise_2.0.1 [10] RCurl_1.98-1.17 base64enc_0.1-3 htmltools_0.5.8.1 [13] pROC_1.18.5 Formula_1.2-5 parallelly_1.45.0 [16] htmlwidgets_1.6.4 plyr_1.8.9 impute_1.72.3 [19] cachem_1.1.0 lifecycle_1.0.4 pkgconfig_2.0.3 [22] R6_2.6.1 fastmap_1.2.0 future_1.58.0 [25] GenomeInfoDbData_1.2.9 digest_0.6.39 colorspace_2.1-2 [28] AnnotationDbi_1.60.2 geneplotter_1.76.0 Hmisc_5.2-3 [31] RSQLite_2.4.2 timechange_0.3.0 mgcv_1.9-4 [34] httr_1.4.7 polyclip_1.10-7 compiler_4.5.2 [37] bit64_4.6.0-1 withr_3.0.2 htmlTable_2.4.3 [40] backports_1.5.0 BiocParallel_1.32.6 viridis_0.6.5 [43] DBI_1.2.3 ggforce_0.5.0 lava_1.8.1 [46] MASS_7.3-65 DelayedArray_0.24.0 ModelMetrics_1.2.2.2 [49] tools_4.5.2 foreign_0.8-90 future.apply_1.20.0 [52] nnet_7.3-20 glue_1.8.0 nlme_3.1-168 [55] grid_4.5.2 checkmate_2.3.2 cluster_2.1.8.1 [58] recipes_1.3.1 generics_0.1.4 gtable_0.3.6 [61] tzdb_0.5.0 class_7.3-23 preprocessCore_1.60.2 [64] data.table_1.17.8 hms_1.1.4 xml2_1.5.0 [67] XVector_0.38.0 ggrepel_0.9.6 pillar_1.11.1 [70] splines_4.5.2 tweenr_2.0.3 survival_3.8-3 [73] bit_4.6.0 annotate_1.76.0 tidyselect_1.2.1 [76] GO.db_3.16.0 locfit_1.5-9.12 Biostrings_2.66.0 [79] knitr_1.50 gridExtra_2.3 xfun_0.54 [82] graphlayouts_1.2.2 hardhat_1.4.1 timeDate_4041.110 [85] stringi_1.8.7 evaluate_1.0.5 codetools_0.2-20 [88] cli_3.6.5 rpart_4.1.24 xtable_1.8-4 [91] dichromat_2.0-0.1 Rcpp_1.1.0 globals_0.18.0 [94] png_0.1-8 XML_3.99-0.18 gower_1.0.2 [97] blob_1.2.4 bitops_1.0-9 listenv_0.9.1 [100] viridisLite_0.4.2 ipred_0.9-15 prodlim_2025.04.28 [103] crayon_1.5.3 rlang_1.1.6 KEGGREST_1.38.0 [106] mnormt_2.1.1 Start time:2026-03-04 21:59:52.562552 Defining model functions Loading gene counts Loading miRNA counts Loading lncRNA counts Loading WGBS data Loading metadata table Species prefix and code:POR,Peve WGBS column name handling Filtering datasets filtering low count features Ensuring integer counts Filtered dimensions: Genes: 471 x 31 miRNA: 46 x 31 lncRNA: 8317 x 31 WGBS: 19570 x 31 Ensuring all dfs have identical column names and orders Applying variance stabilization Predictor set dimensions:31 Predictor set dimensions:27933 Gene set dimensions:31 Gene set dimensions:471 === Data Validation and Cleaning === Predictor matrix: 31 samples x 27933 features Columns with NaN: 0 Columns with Inf: 0 Columns with NA: 9498 Constant columns (sd = 0): 0 Total problematic columns: 9498 Problematic columns by type: Other: 9498 Removed 9498 problematic predictors. Remaining: 18435 Response matrix: 31 samples x 471 genes Genes with NaN/Inf/NA/constant values: 0 Samples available: 31 Cleaned data dimensions: Predictors: 31 samples x 18435 features Genes: 31 samples x 471 genes Pre-flight test: fitting one gene sequentially to verify data compatibility... Pre-flight passed: gene 'OG_08920', R2 = 0.9997, 109 non-zero coefficients === Data validation complete === === PART 1: Elastic Net with Bootstrapped Train/Test Splits === --- Round 1: 10 bootstrap replicates across all 471 genes --- Round1: Running 10 replicates across 10 cores... Round1: 0/10 (0.0%) Round1: 10/10 (100.0%) Round 1 results: 195/471 genes with mean R2 >= 0.50 --- Round 2: 10 bootstrap replicates on 195 well-predicted genes --- Round2: Running 10 replicates across 10 cores... Round2: 0/10 (0.0%) Round2: 10/10 (100.0%) Round 2 performance summary: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.1818 0.5657 0.6604 0.6667 0.7749 0.9407 Bootstrapping completed in 7.38 minutes === PART 1.5: R-squared Bootstrap Plots === Plotting Round 1 R² (all genes)... Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_R2_round1-allgenes.png Plotting Round 2 R² (well-predicted genes)... Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_R2_round2-well-predictedgenes.png === PART 2: Stability Selection for Predictor Reliability === This step assesses how reliably each predictor is selected across random subsamples of the data, providing a robust measure of predictor importance. Unlike permutation testing, stability selection avoids the degenerate null distribution problem that arises with sparse penalized regression. Running stability selection for 195 well-predicted genes Calculating stability selection for 195 genes with 10 subsample iterations each Total predictors per gene: 18435 Using 10 core(s) for gene-level parallelization Complementary pairs: each iteration produces 2 fits (20 total fits per gene) StabSel: Running in parallel mode across 195 genes... StabSel: 0/195 (0.0%) StabSel: 195/195 (100.0%) === Stability Selection Summary === Total predictor-gene combinations: 3594825 Predictors ever selected (in at least 1 fit): 75651 (2.10%) Average predictors with any selection per gene: 388.0 Subsample iterations per gene: 10 (producing 20 complementary-pair fits) Stability selection completed in 2.20 minutes Applying PFER bound with selection threshold pi = 0.60 PFER bound applied with selection threshold pi = 0.60 Theoretical guarantee: E(false selections) <= PFER_bound per gene Per-gene PFER diagnostics: OG_00246: PFER <= 2.207 | Stable predictors: 41 | Avg selected/fit: 90.2 | p = 18435 OG_00355: PFER <= 2.691 | Stable predictors: 39 | Avg selected/fit: 99.6 | p = 18435 OG_00430: PFER <= 2.192 | Stable predictors: 38 | Avg selected/fit: 89.9 | p = 18435 OG_00460: PFER <= 1.258 | Stable predictors: 20 | Avg selected/fit: 68.1 | p = 18435 OG_00514: PFER <= 2.212 | Stable predictors: 27 | Avg selected/fit: 90.3 | p = 18435 OG_00572: PFER <= 2.866 | Stable predictors: 52 | Avg selected/fit: 102.8 | p = 18435 OG_00807: PFER <= 3.199 | Stable predictors: 69 | Avg selected/fit: 108.6 | p = 18435 OG_00843: PFER <= 2.437 | Stable predictors: 33 | Avg selected/fit: 94.8 | p = 18435 OG_01023: PFER <= 2.894 | Stable predictors: 42 | Avg selected/fit: 103.3 | p = 18435 OG_01117: PFER <= 2.124 | Stable predictors: 46 | Avg selected/fit: 88.5 | p = 18435 OG_01121: PFER <= 2.658 | Stable predictors: 49 | Avg selected/fit: 99.0 | p = 18435 OG_01155: PFER <= 2.789 | Stable predictors: 41 | Avg selected/fit: 101.4 | p = 18435 OG_01177: PFER <= 1.891 | Stable predictors: 33 | Avg selected/fit: 83.5 | p = 18435 OG_01317: PFER <= 2.402 | Stable predictors: 45 | Avg selected/fit: 94.1 | p = 18435 OG_01353: PFER <= 2.756 | Stable predictors: 37 | Avg selected/fit: 100.8 | p = 18435 OG_01354: PFER <= 2.531 | Stable predictors: 43 | Avg selected/fit: 96.6 | p = 18435 OG_01486: PFER <= 2.844 | Stable predictors: 42 | Avg selected/fit: 102.4 | p = 18435 OG_01489: PFER <= 2.850 | Stable predictors: 31 | Avg selected/fit: 102.5 | p = 18435 OG_01579: PFER <= 2.197 | Stable predictors: 27 | Avg selected/fit: 90.0 | p = 18435 OG_01608: PFER <= 2.547 | Stable predictors: 49 | Avg selected/fit: 96.9 | p = 18435 OG_01611: PFER <= 2.718 | Stable predictors: 40 | Avg selected/fit: 100.1 | p = 18435 OG_01630: PFER <= 2.173 | Stable predictors: 39 | Avg selected/fit: 89.5 | p = 18435 OG_01727: PFER <= 2.967 | Stable predictors: 60 | Avg selected/fit: 104.6 | p = 18435 OG_01747: PFER <= 1.923 | Stable predictors: 32 | Avg selected/fit: 84.2 | p = 18435 OG_01999: PFER <= 1.900 | Stable predictors: 40 | Avg selected/fit: 83.7 | p = 18435 OG_02000: PFER <= 1.571 | Stable predictors: 36 | Avg selected/fit: 76.1 | p = 18435 OG_02012: PFER <= 3.030 | Stable predictors: 50 | Avg selected/fit: 105.7 | p = 18435 OG_02090: PFER <= 2.494 | Stable predictors: 48 | Avg selected/fit: 95.9 | p = 18435 OG_02102: PFER <= 2.664 | Stable predictors: 50 | Avg selected/fit: 99.1 | p = 18435 OG_02124: PFER <= 2.531 | Stable predictors: 39 | Avg selected/fit: 96.6 | p = 18435 OG_02149: PFER <= 1.909 | Stable predictors: 20 | Avg selected/fit: 83.9 | p = 18435 OG_02184: PFER <= 3.007 | Stable predictors: 53 | Avg selected/fit: 105.3 | p = 18435 OG_02190: PFER <= 2.827 | Stable predictors: 54 | Avg selected/fit: 102.1 | p = 18435 OG_02219: PFER <= 2.883 | Stable predictors: 44 | Avg selected/fit: 103.1 | p = 18435 OG_02220: PFER <= 2.381 | Stable predictors: 47 | Avg selected/fit: 93.7 | p = 18435 OG_02260: PFER <= 1.228 | Stable predictors: 26 | Avg selected/fit: 67.3 | p = 18435 OG_02358: PFER <= 2.397 | Stable predictors: 40 | Avg selected/fit: 94.0 | p = 18435 OG_03267: PFER <= 3.002 | Stable predictors: 47 | Avg selected/fit: 105.2 | p = 18435 OG_03298: PFER <= 2.321 | Stable predictors: 41 | Avg selected/fit: 92.5 | p = 18435 OG_03330: PFER <= 2.351 | Stable predictors: 40 | Avg selected/fit: 93.1 | p = 18435 OG_03628: PFER <= 2.311 | Stable predictors: 32 | Avg selected/fit: 92.3 | p = 18435 OG_03780: PFER <= 1.810 | Stable predictors: 35 | Avg selected/fit: 81.7 | p = 18435 OG_03850: PFER <= 1.659 | Stable predictors: 20 | Avg selected/fit: 78.2 | p = 18435 OG_04209: PFER <= 2.197 | Stable predictors: 38 | Avg selected/fit: 90.0 | p = 18435 OG_04238: PFER <= 2.105 | Stable predictors: 56 | Avg selected/fit: 88.1 | p = 18435 OG_04243: PFER <= 2.600 | Stable predictors: 40 | Avg selected/fit: 97.9 | p = 18435 OG_04247: PFER <= 0.844 | Stable predictors: 19 | Avg selected/fit: 55.8 | p = 18435 OG_04327: PFER <= 2.251 | Stable predictors: 30 | Avg selected/fit: 91.1 | p = 18435 OG_04538: PFER <= 2.053 | Stable predictors: 39 | Avg selected/fit: 87.0 | p = 18435 OG_04547: PFER <= 2.494 | Stable predictors: 51 | Avg selected/fit: 95.9 | p = 18435 OG_04560: PFER <= 1.960 | Stable predictors: 51 | Avg selected/fit: 85.0 | p = 18435 OG_04723: PFER <= 2.562 | Stable predictors: 32 | Avg selected/fit: 97.2 | p = 18435 OG_04756: PFER <= 2.177 | Stable predictors: 26 | Avg selected/fit: 89.6 | p = 18435 OG_04789: PFER <= 1.824 | Stable predictors: 22 | Avg selected/fit: 82.0 | p = 18435 OG_04799: PFER <= 3.348 | Stable predictors: 55 | Avg selected/fit: 111.1 | p = 18435 OG_05121: PFER <= 2.437 | Stable predictors: 45 | Avg selected/fit: 94.8 | p = 18435 OG_05308: PFER <= 2.621 | Stable predictors: 42 | Avg selected/fit: 98.3 | p = 18435 OG_05366: PFER <= 2.316 | Stable predictors: 37 | Avg selected/fit: 92.4 | p = 18435 OG_05367: PFER <= 2.129 | Stable predictors: 40 | Avg selected/fit: 88.6 | p = 18435 OG_05498: PFER <= 2.729 | Stable predictors: 32 | Avg selected/fit: 100.3 | p = 18435 OG_05514: PFER <= 1.891 | Stable predictors: 27 | Avg selected/fit: 83.5 | p = 18435 OG_05637: PFER <= 3.111 | Stable predictors: 38 | Avg selected/fit: 107.1 | p = 18435 OG_05713: PFER <= 2.889 | Stable predictors: 49 | Avg selected/fit: 103.2 | p = 18435 OG_05718: PFER <= 2.453 | Stable predictors: 46 | Avg selected/fit: 95.1 | p = 18435 OG_05749: PFER <= 2.043 | Stable predictors: 35 | Avg selected/fit: 86.8 | p = 18435 OG_05856: PFER <= 2.412 | Stable predictors: 42 | Avg selected/fit: 94.3 | p = 18435 OG_05874: PFER <= 1.775 | Stable predictors: 40 | Avg selected/fit: 80.9 | p = 18435 OG_05875: PFER <= 1.749 | Stable predictors: 39 | Avg selected/fit: 80.3 | p = 18435 OG_06152: PFER <= 1.969 | Stable predictors: 41 | Avg selected/fit: 85.2 | p = 18435 OG_06181: PFER <= 2.251 | Stable predictors: 49 | Avg selected/fit: 91.1 | p = 18435 OG_06198: PFER <= 2.321 | Stable predictors: 41 | Avg selected/fit: 92.5 | p = 18435 OG_06279: PFER <= 2.067 | Stable predictors: 38 | Avg selected/fit: 87.3 | p = 18435 OG_06599: PFER <= 2.911 | Stable predictors: 54 | Avg selected/fit: 103.6 | p = 18435 OG_06607: PFER <= 2.296 | Stable predictors: 36 | Avg selected/fit: 92.0 | p = 18435 OG_06616: PFER <= 2.286 | Stable predictors: 39 | Avg selected/fit: 91.8 | p = 18435 OG_06670: PFER <= 2.729 | Stable predictors: 43 | Avg selected/fit: 100.3 | p = 18435 OG_06717: PFER <= 1.753 | Stable predictors: 32 | Avg selected/fit: 80.4 | p = 18435 OG_06719: PFER <= 2.029 | Stable predictors: 28 | Avg selected/fit: 86.5 | p = 18435 OG_06754: PFER <= 2.589 | Stable predictors: 48 | Avg selected/fit: 97.7 | p = 18435 OG_06998: PFER <= 3.053 | Stable predictors: 54 | Avg selected/fit: 106.1 | p = 18435 OG_07000: PFER <= 1.896 | Stable predictors: 50 | Avg selected/fit: 83.6 | p = 18435 OG_07183: PFER <= 2.011 | Stable predictors: 40 | Avg selected/fit: 86.1 | p = 18435 OG_07252: PFER <= 1.303 | Stable predictors: 20 | Avg selected/fit: 69.3 | p = 18435 OG_07331: PFER <= 3.294 | Stable predictors: 52 | Avg selected/fit: 110.2 | p = 18435 OG_07389: PFER <= 1.964 | Stable predictors: 28 | Avg selected/fit: 85.1 | p = 18435 OG_07620: PFER <= 1.905 | Stable predictors: 31 | Avg selected/fit: 83.8 | p = 18435 OG_07641: PFER <= 2.336 | Stable predictors: 35 | Avg selected/fit: 92.8 | p = 18435 OG_07807: PFER <= 1.714 | Stable predictors: 25 | Avg selected/fit: 79.5 | p = 18435 OG_07892: PFER <= 1.797 | Stable predictors: 47 | Avg selected/fit: 81.4 | p = 18435 OG_07958: PFER <= 2.291 | Stable predictors: 30 | Avg selected/fit: 91.9 | p = 18435 OG_08143: PFER <= 1.497 | Stable predictors: 22 | Avg selected/fit: 74.3 | p = 18435 OG_08144: PFER <= 1.714 | Stable predictors: 31 | Avg selected/fit: 79.5 | p = 18435 OG_08347: PFER <= 2.626 | Stable predictors: 41 | Avg selected/fit: 98.4 | p = 18435 OG_08432: PFER <= 2.301 | Stable predictors: 45 | Avg selected/fit: 92.1 | p = 18435 OG_08497: PFER <= 2.062 | Stable predictors: 34 | Avg selected/fit: 87.2 | p = 18435 OG_08528: PFER <= 2.794 | Stable predictors: 40 | Avg selected/fit: 101.5 | p = 18435 OG_08622: PFER <= 2.479 | Stable predictors: 48 | Avg selected/fit: 95.6 | p = 18435 OG_08793: PFER <= 1.356 | Stable predictors: 21 | Avg selected/fit: 70.7 | p = 18435 OG_08842: PFER <= 1.810 | Stable predictors: 30 | Avg selected/fit: 81.7 | p = 18435 OG_08856: PFER <= 2.928 | Stable predictors: 42 | Avg selected/fit: 103.9 | p = 18435 OG_08920: PFER <= 2.816 | Stable predictors: 49 | Avg selected/fit: 101.9 | p = 18435 OG_09247: PFER <= 1.766 | Stable predictors: 21 | Avg selected/fit: 80.7 | p = 18435 OG_09310: PFER <= 2.889 | Stable predictors: 45 | Avg selected/fit: 103.2 | p = 18435 OG_09423: PFER <= 2.301 | Stable predictors: 44 | Avg selected/fit: 92.1 | p = 18435 OG_09597: PFER <= 2.207 | Stable predictors: 48 | Avg selected/fit: 90.2 | p = 18435 OG_09598: PFER <= 2.015 | Stable predictors: 34 | Avg selected/fit: 86.2 | p = 18435 OG_09806: PFER <= 1.775 | Stable predictors: 33 | Avg selected/fit: 80.9 | p = 18435 OG_09896: PFER <= 2.053 | Stable predictors: 41 | Avg selected/fit: 87.0 | p = 18435 OG_09969: PFER <= 2.086 | Stable predictors: 54 | Avg selected/fit: 87.7 | p = 18435 OG_10002: PFER <= 1.864 | Stable predictors: 40 | Avg selected/fit: 82.9 | p = 18435 OG_10007: PFER <= 2.177 | Stable predictors: 54 | Avg selected/fit: 89.6 | p = 18435 OG_10008: PFER <= 2.391 | Stable predictors: 51 | Avg selected/fit: 93.9 | p = 18435 OG_10121: PFER <= 2.520 | Stable predictors: 33 | Avg selected/fit: 96.4 | p = 18435 OG_10183: PFER <= 2.058 | Stable predictors: 56 | Avg selected/fit: 87.1 | p = 18435 OG_10205: PFER <= 2.653 | Stable predictors: 28 | Avg selected/fit: 98.9 | p = 18435 OG_10265: PFER <= 1.923 | Stable predictors: 16 | Avg selected/fit: 84.2 | p = 18435 OG_10332: PFER <= 1.784 | Stable predictors: 39 | Avg selected/fit: 81.1 | p = 18435 OG_10509: PFER <= 2.407 | Stable predictors: 53 | Avg selected/fit: 94.2 | p = 18435 OG_10516: PFER <= 1.654 | Stable predictors: 30 | Avg selected/fit: 78.1 | p = 18435 OG_10522: PFER <= 2.043 | Stable predictors: 30 | Avg selected/fit: 86.8 | p = 18435 OG_10675: PFER <= 2.723 | Stable predictors: 41 | Avg selected/fit: 100.2 | p = 18435 OG_10758: PFER <= 1.779 | Stable predictors: 38 | Avg selected/fit: 81.0 | p = 18435 OG_10759: PFER <= 2.077 | Stable predictors: 33 | Avg selected/fit: 87.5 | p = 18435 OG_10936: PFER <= 2.889 | Stable predictors: 38 | Avg selected/fit: 103.2 | p = 18435 OG_11038: PFER <= 1.815 | Stable predictors: 37 | Avg selected/fit: 81.8 | p = 18435 OG_11215: PFER <= 1.033 | Stable predictors: 27 | Avg selected/fit: 61.7 | p = 18435 OG_11245: PFER <= 2.594 | Stable predictors: 50 | Avg selected/fit: 97.8 | p = 18435 OG_11379: PFER <= 1.587 | Stable predictors: 24 | Avg selected/fit: 76.5 | p = 18435 OG_11429: PFER <= 1.449 | Stable predictors: 30 | Avg selected/fit: 73.1 | p = 18435 OG_11642: PFER <= 3.042 | Stable predictors: 56 | Avg selected/fit: 105.9 | p = 18435 OG_11813: PFER <= 2.448 | Stable predictors: 37 | Avg selected/fit: 95.0 | p = 18435 OG_11831: PFER <= 2.386 | Stable predictors: 30 | Avg selected/fit: 93.8 | p = 18435 OG_11957: PFER <= 2.402 | Stable predictors: 38 | Avg selected/fit: 94.1 | p = 18435 OG_11984: PFER <= 2.967 | Stable predictors: 49 | Avg selected/fit: 104.6 | p = 18435 OG_12031: PFER <= 2.301 | Stable predictors: 34 | Avg selected/fit: 92.1 | p = 18435 OG_12107: PFER <= 3.427 | Stable predictors: 60 | Avg selected/fit: 112.4 | p = 18435 OG_12108: PFER <= 2.134 | Stable predictors: 50 | Avg selected/fit: 88.7 | p = 18435 OG_12109: PFER <= 2.072 | Stable predictors: 38 | Avg selected/fit: 87.4 | p = 18435 OG_12162: PFER <= 2.207 | Stable predictors: 37 | Avg selected/fit: 90.2 | p = 18435 OG_12165: PFER <= 2.610 | Stable predictors: 41 | Avg selected/fit: 98.1 | p = 18435 OG_12166: PFER <= 2.139 | Stable predictors: 57 | Avg selected/fit: 88.8 | p = 18435 OG_12242: PFER <= 2.129 | Stable predictors: 42 | Avg selected/fit: 88.6 | p = 18435 OG_12248: PFER <= 1.379 | Stable predictors: 23 | Avg selected/fit: 71.3 | p = 18435 OG_12318: PFER <= 1.824 | Stable predictors: 32 | Avg selected/fit: 82.0 | p = 18435 OG_12331: PFER <= 3.512 | Stable predictors: 60 | Avg selected/fit: 113.8 | p = 18435 OG_12424: PFER <= 1.637 | Stable predictors: 25 | Avg selected/fit: 77.7 | p = 18435 OG_12447: PFER <= 2.712 | Stable predictors: 57 | Avg selected/fit: 100.0 | p = 18435 OG_12496: PFER <= 2.557 | Stable predictors: 43 | Avg selected/fit: 97.1 | p = 18435 OG_12518: PFER <= 2.301 | Stable predictors: 40 | Avg selected/fit: 92.1 | p = 18435 OG_12568: PFER <= 1.887 | Stable predictors: 43 | Avg selected/fit: 83.4 | p = 18435 OG_12722: PFER <= 1.633 | Stable predictors: 23 | Avg selected/fit: 77.6 | p = 18435 OG_12785: PFER <= 1.758 | Stable predictors: 25 | Avg selected/fit: 80.5 | p = 18435 OG_12880: PFER <= 1.706 | Stable predictors: 38 | Avg selected/fit: 79.3 | p = 18435 OG_13013: PFER <= 2.594 | Stable predictors: 49 | Avg selected/fit: 97.8 | p = 18435 OG_13016: PFER <= 2.489 | Stable predictors: 52 | Avg selected/fit: 95.8 | p = 18435 OG_13050: PFER <= 1.254 | Stable predictors: 17 | Avg selected/fit: 68.0 | p = 18435 OG_13066: PFER <= 2.331 | Stable predictors: 38 | Avg selected/fit: 92.7 | p = 18435 OG_13197: PFER <= 1.946 | Stable predictors: 45 | Avg selected/fit: 84.7 | p = 18435 OG_13201: PFER <= 2.321 | Stable predictors: 55 | Avg selected/fit: 92.5 | p = 18435 OG_13239: PFER <= 2.336 | Stable predictors: 48 | Avg selected/fit: 92.8 | p = 18435 OG_13334: PFER <= 2.712 | Stable predictors: 36 | Avg selected/fit: 100.0 | p = 18435 OG_13428: PFER <= 1.587 | Stable predictors: 33 | Avg selected/fit: 76.5 | p = 18435 OG_13451: PFER <= 2.453 | Stable predictors: 34 | Avg selected/fit: 95.1 | p = 18435 OG_13466: PFER <= 1.937 | Stable predictors: 34 | Avg selected/fit: 84.5 | p = 18435 OG_13481: PFER <= 2.531 | Stable predictors: 45 | Avg selected/fit: 96.6 | p = 18435 OG_13484: PFER <= 2.301 | Stable predictors: 44 | Avg selected/fit: 92.1 | p = 18435 OG_15738: PFER <= 1.918 | Stable predictors: 34 | Avg selected/fit: 84.1 | p = 18435 OG_15796: PFER <= 1.745 | Stable predictors: 34 | Avg selected/fit: 80.2 | p = 18435 OG_15816: PFER <= 2.236 | Stable predictors: 37 | Avg selected/fit: 90.8 | p = 18435 OG_15877: PFER <= 2.536 | Stable predictors: 40 | Avg selected/fit: 96.7 | p = 18435 OG_16000: PFER <= 2.144 | Stable predictors: 34 | Avg selected/fit: 88.9 | p = 18435 OG_16145: PFER <= 1.667 | Stable predictors: 29 | Avg selected/fit: 78.4 | p = 18435 OG_16159: PFER <= 1.950 | Stable predictors: 23 | Avg selected/fit: 84.8 | p = 18435 OG_16192: PFER <= 2.822 | Stable predictors: 50 | Avg selected/fit: 102.0 | p = 18435 OG_16380: PFER <= 2.025 | Stable predictors: 34 | Avg selected/fit: 86.4 | p = 18435 OG_16489: PFER <= 2.653 | Stable predictors: 53 | Avg selected/fit: 98.9 | p = 18435 OG_16592: PFER <= 2.316 | Stable predictors: 47 | Avg selected/fit: 92.4 | p = 18435 OG_16654: PFER <= 1.896 | Stable predictors: 36 | Avg selected/fit: 83.6 | p = 18435 OG_16665: PFER <= 1.714 | Stable predictors: 35 | Avg selected/fit: 79.5 | p = 18435 OG_16747: PFER <= 1.575 | Stable predictors: 30 | Avg selected/fit: 76.2 | p = 18435 OG_16856: PFER <= 0.922 | Stable predictors: 19 | Avg selected/fit: 58.3 | p = 18435 OG_16944: PFER <= 2.934 | Stable predictors: 43 | Avg selected/fit: 104.0 | p = 18435 OG_16980: PFER <= 1.758 | Stable predictors: 37 | Avg selected/fit: 80.5 | p = 18435 OG_17058: PFER <= 3.065 | Stable predictors: 44 | Avg selected/fit: 106.3 | p = 18435 OG_17106: PFER <= 2.894 | Stable predictors: 48 | Avg selected/fit: 103.3 | p = 18435 OG_17176: PFER <= 1.236 | Stable predictors: 27 | Avg selected/fit: 67.5 | p = 18435 OG_17479: PFER <= 1.710 | Stable predictors: 22 | Avg selected/fit: 79.4 | p = 18435 OG_17483: PFER <= 1.877 | Stable predictors: 46 | Avg selected/fit: 83.2 | p = 18435 OG_17556: PFER <= 2.474 | Stable predictors: 24 | Avg selected/fit: 95.5 | p = 18435 OG_17666: PFER <= 1.762 | Stable predictors: 33 | Avg selected/fit: 80.6 | p = 18435 OG_17751: PFER <= 1.806 | Stable predictors: 36 | Avg selected/fit: 81.6 | p = 18435 OG_17800: PFER <= 1.771 | Stable predictors: 32 | Avg selected/fit: 80.8 | p = 18435 OG_17961: PFER <= 1.997 | Stable predictors: 28 | Avg selected/fit: 85.8 | p = 18435 OG_18057: PFER <= 1.288 | Stable predictors: 25 | Avg selected/fit: 68.9 | p = 18435 OG_18285: PFER <= 1.941 | Stable predictors: 27 | Avg selected/fit: 84.6 | p = 18435 === Stable Predictor Summary (Selection Prob >= 60%) === Number of stable predictor-gene associations: 7555 Number of genes with at least one stable predictor: 195 Breakdown of EVER-SELECTED predictors by type: # A tibble: 3 × 4 Predictor_Type N_ever_selected N_stable Pct_stable 1 Other 22670 909 4.01 2 lncRNA 52759 6635 12.6 3 miRNA 222 11 4.95 Breakdown of STABLE predictors by type: # A tibble: 3 × 5 Predictor_Type N_stable N_unique_predictors N_genes_affected 1 Other 909 790 168 2 lncRNA 6635 3693 195 3 miRNA 11 8 11 # ℹ 1 more variable: Mean_Selection_Prob === PART 3: Generating Visualizations and Output Files === Creating summary plots... Creating per-gene stability selection plots... Saving stability selection results... Enhancing top predictors table with stability information... === PART 3.5: Stacked Bar Charts and Heatmaps === Building composition data (with significance filtering)... Building composition data (without significance filtering)... Generating stacked bar charts (stable predictors only)... Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_alphabetical_sig.png Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_predominant_sig.png Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_r2_sig.png Generating stacked bar charts (all non-zero predictors)... Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_alphabetical_nosig.png Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_predominant_nosig.png Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_stacked_bar_r2_nosig.png Generating predictor-type heatmaps... Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_predictor_heatmap_sig.png Saved: ../output/26.6-ElasticNet-stability-selection-2/Peve/Peve_predictor_heatmap_nosig.png === ANALYSIS COMPLETE === End time:2026-03-04 22:12:31.618657 Timing summary: - Bootstrapping: 7.38 minutes - Stability selection: 2.20 minutes - Total runtime: 9.58 minutes Output files generated: 1. Peve_stabsel_results_full.csv - All predictor-gene selection probabilities 2. Peve_stable_predictors.csv - Stable associations only (>= 60%) 3. Peve_gene_summary.csv - Summary per gene 4. Peve_predictor_type_summary.csv - Summary by predictor type 5. Peve_top_predictors_with_stability.csv - Top predictors with stability info 6. Peve_R2_round1*.png - R² per gene with error bars (all genes) 7. Peve_R2_round2*.png - R² per gene with error bars (well-predicted) 8. Peve_stacked_bar_*.png - Predictor type composition (3 orderings x 2 versions) 9. Peve_predictor_heatmap_*.png - Predictor type heatmap (2 versions) 10. Various per-gene plots in ../output/26.6-ElasticNet-stability-selection-2/Peve/ Key statistics: - Total genes analyzed: 471 - Well-predicted genes (R2 > 0.50): 195 - Stable predictor-gene associations: 7555 - Bootstrap replicates: 10 (round 1), 10 (round 2) - Subsample iterations: 10 (producing 20 complementary-pair fits) - Selection threshold: 60% - Cores used: 10 Statistical notes: - Predictor reliability assessed via stability selection (Meinshausen & Bühlmann, 2010; Shah & Samworth, 2013) - Error control: PFER bound (expected false selections per gene) - Selection threshold: pi = 0.60 - No separate multiple testing correction needed (PFER bound is simultaneous) Log file saved to: ../output/26.6-ElasticNet-stability-selection-2/Peve/ElasticNet_stabsel_log_20260304_215952.txt === END OF SCRIPT === === Log closed: 2026-03-04 22:12:31.627852 ===