0．1Instalation

if (!require("BiocManager")) install.packages("BiocManager")

1需要包

library(无益的.logger) library(ggplot2) library(glmSparseNet) library(survival) #无益的一些通用选项。记录调试包。最后。值<- flag .layout(布局。format('[~l] ~m'))。value <- glmSparseNet:::show.message(FALSE) #设置ggplot2默认主题为最小theme_set(ggplot2::theme_minimal())

Data ('cancer'， package = 'survival') xdata <- survival::ovarian[，c('age'， ' resido .ds')] ydata <- Data .frame(time = survival::ovarian$futime, status = survival::ovarian$fustat)

res.age <- separate2GroupsCox(c(age = 1,0)， xdata, ydata)

##调用:survfit(公式=生存::Surv(时间，状态)~组，数据=预后。index.df) ## ## n事件中位数0.95LCL 0.95UCL ##低风险13 4 NA 638 NA ##高风险13 8 464 268 NA

res.age.40.60 <- separate2GroupsCox(c(年龄= 1,0)，xdata, ydata, probs = c(。4， .6))

##调用:survfit(公式=生存率::Surv(时间，状态)~组，数据=预后。index.df) ## ## n事件中位数0.95LCL 0.95UCL ##低风险11 3 NA 563 NA ##高风险10 7 359 156 NA

res.age.60.40 <- separate2GroupsCox(选中。Btas = c(年龄= 1,0)，xdata, ydata, probs = c(。6， .4)， stop.when.overlap = FALSE)

## separate2GroupsCox中的警告(已选)btas = c(age = 1,0)， xdata, ydata，:给函数的截止值允许在两组中都有一些过样本，##高风险大小(15)+低风险大小(16)不等于xdata/ydata行(31 != 26)## ##我们继续执行参数stop. whenoverlap为FALSE。##注意:这将为ydata和xdata xdata添加重复的示例

## Kaplan-Meier结果

##调用:survfit(公式=生存率::Surv(时间，状态)~组，数据=预后。index.df) ## ## n事件中位数0.95LCL 0.95UCL ##低风险16 5 NA 638 NA ##高风险15 9 475 353 NA

2会话信息

sessionInfo ()

## R版本4.2.0 RC (2022-04-21 r82226) ##平台:x86_64-pc-linux-gnu(64位)##运行在Ubuntu 20.04.4 LTS ## ##矩阵产品:默认## BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas。/home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack。所以## ## locale: ## [1] LC_CTYPE=en_US。UTF-8 LC_NUMERIC= c# # [3] LC_TIME=en_GB LC_COLLATE= c# # [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_phone = c# # [11] LC_MEASUREMENT=en_US。UTF-8 LC_IDENTIFICATION=C ## ##附加的基本包:##[1]网格并行stats4统计图形grDevices utils ##[8]数据集方法基础## ##其他附加包:# # # # [1] VennDiagram_1.7.3 reshape2_1.4.4 [3] forcats_0.5.1 glmSparseNet_1.15.0 # # [5] glmnet_4.1-4 Matrix_1.4-1 # # [7] TCGAutils_1.17.0 curatedTCGAData_1.17.1 # # [9] MultiAssayExperiment_1.23.0 SummarizedExperiment_1.27.0 # # [11] Biobase_2.57.0 GenomicRanges_1.49.0 # # [13] GenomeInfoDb_1.33.0 IRanges_2.31.0 # # [15] S4Vectors_0.35.0 BiocGenerics_0.43.0 # # [17] MatrixGenerics_1.9.0 matrixStats_0.62.0 # # [19] futile.logger_1.4.3 survival_3.3-1 # # [21] ggplot2_3.3.5 dplyr_1.0.8 # # [23]BiocStyle_2.25.0 ## ##通过命名空间加载(并且没有附加):# # # # [1] backports_1.4.1 AnnotationHub_3.5.0 [3] BiocFileCache_2.5.0 plyr_1.8.7 # # [5] splines_4.2.0 BiocParallel_1.31.0 # # [7] digest_0.6.29 foreach_1.5.2 # # [9] htmltools_0.5.2 magick_2.7.3 # # [11] fansi_1.0.3 magrittr_2.0.3 # # [13] memoise_2.0.1 tzdb_0.3.0 # # [15] Biostrings_2.65.0 readr_2.1.2 # # [17] prettyunits_1.1.1 colorspace_2.0-3 # # [19] blob_1.2.3 rvest_1.0.2 # # [21] rappdirs_0.3.3 xfun_0.30 # # [23] crayon_1.5.1 rcurl_1.98 - 1.6 # # [25] jsonlite_1.8.0 zoo_1.8-10 # # [27] iterators_1.0.14glue_1.6.2 ## [29] survminer_0.4.9 GenomicDataCommons_1.21.0 ## [31] gtable_0.3.0 zlibbioc_1.43.0 ## [33] XVector_0.37.0 DelayedArray_0.23.0 ## [35] car_3.0-12 shape_1.4.6 ## [37] abind_1.4-5 scales_1.2.0 ## [39] futile.options_1.0.1 DBI_1.1.2 ## [41] rstatix_0.7.0 Rcpp_1.0.8.3 ## [43] xtable_1.8-4 progress_1.2.2 ## [45] bit_4.0.4 km.ci_0.5-6 ## [47] httr_1.4.2 ellipsis_0.3.2 ## [49] pkgconfig_2.0.3 XML_3.99-0.9 ## [51] farver_2.1.0 sass_0.4.1 ## [53] dbplyr_2.1.1 utf8_1.2.2 ## [55] tidyselect_1.1.2 labeling_0.4.2 ## [57] rlang_1.0.2 later_1.3.0 ## [59] AnnotationDbi_1.59.0 munsell_0.5.0 ## [61] BiocVersion_3.16.0 tools_4.2.0 ## [63] cachem_1.0.6 cli_3.3.0 ## [65] generics_0.1.2 RSQLite_2.2.12 ## [67] ExperimentHub_2.5.0 broom_0.8.0 ## [69] evaluate_0.15 stringr_1.4.0 ## [71] fastmap_1.1.0 yaml_2.3.5 ## [73] knitr_1.38 bit64_4.0.5 ## [75] survMisc_0.5.6 purrr_0.3.4 ## [77] KEGGREST_1.37.0 mime_0.12 ## [79] formatR_1.12 xml2_1.3.3 ## [81] biomaRt_2.53.0 compiler_4.2.0 ## [83] filelock_1.0.2 curl_4.3.2 ## [85] png_0.1-7 interactiveDisplayBase_1.35.0 ## [87] ggsignif_0.6.3 tibble_3.1.6 ## [89] bslib_0.3.1 stringi_1.7.6 ## [91] highr_0.9 GenomicFeatures_1.49.0 ## [93] lattice_0.20-45 KMsurv_0.1-5 ## [95] vctrs_0.4.1 pillar_1.7.0 ## [97] lifecycle_1.0.1 BiocManager_1.30.17 ## [99] jquerylib_0.1.4 data.table_1.14.2 ## [101] bitops_1.0-7 httpuv_1.6.5 ## [103] rtracklayer_1.57.0 R6_2.5.1 ## [105] BiocIO_1.7.0 bookdown_0.26 ## [107] promises_1.2.0.1 gridExtra_2.3 ## [109] codetools_0.2-18 lambda.r_1.2.4 ## [111] assertthat_0.2.1 rjson_0.2.21 ## [113] withr_2.5.0 GenomicAlignments_1.33.0 ## [115] Rsamtools_2.13.0 GenomeInfoDbData_1.2.8 ## [117] hms_1.1.1 tidyr_1.2.0 ## [119] rmarkdown_2.14 carData_3.0-5 ## [121] ggpubr_0.4.0 pROC_1.18.0 ## [123] shiny_1.7.1 restfulr_0.0.13