if (!require("BiocManager"))
install.packages("BiocManager")
BiocManager::install("glmSparseNet")
library(futile.logger)
library(ggplot2)
library(glmSparseNet)
library(survival)
# Some general options for futile.logger the debugging package
.Last.value <- flog.layout(layout.format('[~l] ~m'))
.Last.value <- glmSparseNet:::show.message(FALSE)
# Setting ggplot2 default theme as minimal
theme_set(ggplot2::theme_minimal())
data('cancer', package = 'survival')
xdata <- survival::ovarian[,c('age', 'resid.ds')]
ydata <- data.frame(
time = survival::ovarian$futime,
status = survival::ovarian$fustat
)
(group cutoff is median calculated relative risk)
res.age <- separate2GroupsCox(c(age = 1, 0), xdata, ydata)
## Call: survfit(formula = survival::Surv(time, status) ~ group, data = prognostic.index.df)
##
## n events median 0.95LCL 0.95UCL
## Low risk 13 4 NA 638 NA
## High risk 13 8 464 268 NA
A individual is attributed to low-risk group if its calculated relative risk (using Cox Proportional model) is below or equal the median risk.
The opposite for the high-risk groups, populated with individuals above the median relative-risk.
res.age.40.60 <-
separate2GroupsCox(c(age = 1, 0),
xdata,
ydata,
probs = c(.4, .6)
)
## Call: survfit(formula = survival::Surv(time, status) ~ group, data = prognostic.index.df)
##
## n events median 0.95LCL 0.95UCL
## Low risk 11 3 NA 563 NA
## High risk 10 7 359 156 NA
A individual is attributed to low-risk group if its calculated relative risk (using Cox Proportional model) is below the median risk.
The opposite for the high-risk groups, populated with individuals above the median relative-risk.
This is a special case where you want to use a cutoff that includes some sample on both high and low risks groups.
res.age.60.40 <- separate2GroupsCox(
chosen.btas = c(age = 1, 0),
xdata,
ydata,
probs = c(.6, .4),
stop.when.overlap = FALSE
)
## Warning in separate2GroupsCox(chosen.btas = c(age = 1, 0), xdata, ydata, : The cutoff values given to the function allow for some over samples in both groups, with:
## high risk size (15) + low risk size (16) not equal to xdata/ydata rows (31 != 26)
##
## We are continuing with execution as parameter stop.when.overlap is FALSE.
## note: This adds duplicate samples to ydata and xdata xdata
## Kaplan-Meier results
## Call: survfit(formula = survival::Surv(time, status) ~ group, data = prognostic.index.df)
##
## n events median 0.95LCL 0.95UCL
## Low risk 16 5 NA 638 NA
## High risk 15 9 475 353 NA
A individual is attributed to low-risk group if its calculated relative risk (using Cox Proportional model) is below the median risk.
The opposite for the high-risk groups, populated with individuals above the median relative-risk.
sessionInfo()
## R version 4.3.0 RC (2023-04-13 r84257)
## Platform: x86_64-apple-darwin20 (64-bit)
## Running under: macOS Monterey 12.6.4
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-x86_64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
##
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## time zone: America/New_York
## tzcode source: internal
##
## attached base packages:
## [1] grid parallel stats4 stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] VennDiagram_1.7.3 reshape2_1.4.4
## [3] forcats_1.0.0 glmSparseNet_1.18.0
## [5] glmnet_4.1-7 Matrix_1.5-4
## [7] TCGAutils_1.20.0 curatedTCGAData_1.22.1
## [9] MultiAssayExperiment_1.26.0 SummarizedExperiment_1.30.1
## [11] Biobase_2.60.0 GenomicRanges_1.52.0
## [13] GenomeInfoDb_1.36.0 IRanges_2.34.0
## [15] S4Vectors_0.38.1 BiocGenerics_0.46.0
## [17] MatrixGenerics_1.12.0 matrixStats_0.63.0
## [19] futile.logger_1.4.3 survival_3.5-5
## [21] ggplot2_3.4.2 dplyr_1.1.2
## [23] BiocStyle_2.28.0
##
## loaded via a namespace (and not attached):
## [1] jsonlite_1.8.4 shape_1.4.6
## [3] magrittr_2.0.3 magick_2.7.4
## [5] GenomicFeatures_1.52.0 farver_2.1.1
## [7] rmarkdown_2.21 BiocIO_1.10.0
## [9] zlibbioc_1.46.0 vctrs_0.6.2
## [11] memoise_2.0.1 Rsamtools_2.16.0
## [13] RCurl_1.98-1.12 rstatix_0.7.2
## [15] htmltools_0.5.5 S4Arrays_1.0.4
## [17] progress_1.2.2 AnnotationHub_3.8.0
## [19] lambda.r_1.2.4 curl_5.0.0
## [21] broom_1.0.4 pROC_1.18.2
## [23] sass_0.4.6 bslib_0.4.2
## [25] plyr_1.8.8 zoo_1.8-12
## [27] futile.options_1.0.1 cachem_1.0.8
## [29] GenomicAlignments_1.36.0 mime_0.12
## [31] lifecycle_1.0.3 iterators_1.0.14
## [33] pkgconfig_2.0.3 R6_2.5.1
## [35] fastmap_1.1.1 GenomeInfoDbData_1.2.10
## [37] shiny_1.7.4 digest_0.6.31
## [39] colorspace_2.1-0 AnnotationDbi_1.62.1
## [41] ExperimentHub_2.8.0 RSQLite_2.3.1
## [43] ggpubr_0.6.0 filelock_1.0.2
## [45] labeling_0.4.2 km.ci_0.5-6
## [47] fansi_1.0.4 abind_1.4-5
## [49] httr_1.4.6 compiler_4.3.0
## [51] bit64_4.0.5 withr_2.5.0
## [53] backports_1.4.1 BiocParallel_1.34.1
## [55] carData_3.0-5 DBI_1.1.3
## [57] highr_0.10 ggsignif_0.6.4
## [59] biomaRt_2.56.0 rappdirs_0.3.3
## [61] DelayedArray_0.26.2 rjson_0.2.21
## [63] tools_4.3.0 interactiveDisplayBase_1.38.0
## [65] httpuv_1.6.11 glue_1.6.2
## [67] restfulr_0.0.15 promises_1.2.0.1
## [69] generics_0.1.3 gtable_0.3.3
## [71] KMsurv_0.1-5 tzdb_0.4.0
## [73] tidyr_1.3.0 survminer_0.4.9
## [75] data.table_1.14.8 hms_1.1.3
## [77] car_3.1-2 xml2_1.3.4
## [79] utf8_1.2.3 XVector_0.40.0
## [81] BiocVersion_3.17.1 foreach_1.5.2
## [83] pillar_1.9.0 stringr_1.5.0
## [85] later_1.3.1 splines_4.3.0
## [87] BiocFileCache_2.8.0 lattice_0.21-8
## [89] rtracklayer_1.60.0 bit_4.0.5
## [91] tidyselect_1.2.0 Biostrings_2.68.0
## [93] knitr_1.42 gridExtra_2.3
## [95] bookdown_0.34 xfun_0.39
## [97] stringi_1.7.12 yaml_2.3.7
## [99] evaluate_0.21 codetools_0.2-19
## [101] tibble_3.2.1 BiocManager_1.30.20
## [103] cli_3.6.1 xtable_1.8-4
## [105] munsell_0.5.0 jquerylib_0.1.4
## [107] survMisc_0.5.6 Rcpp_1.0.10
## [109] GenomicDataCommons_1.24.0 dbplyr_2.3.2
## [111] png_0.1-8 XML_3.99-0.14
## [113] ellipsis_0.3.2 readr_2.1.4
## [115] blob_1.2.4 prettyunits_1.1.1
## [117] bitops_1.0-7 scales_1.2.1
## [119] purrr_1.0.1 crayon_1.5.2
## [121] rlang_1.1.1 KEGGREST_1.40.0
## [123] rvest_1.0.3 formatR_1.14