Package: SurvHiDim 0.1.1

SurvHiDim: High Dimensional Survival Data Analysis

High dimensional time to events data analysis with variable selection technique. Currently support LASSO, clustering and Bonferroni's correction.

Authors:Atanu Bhattacharjee [aut, cre, ctb], Akash Pawar [aut, ctb]

SurvHiDim_0.1.1.tar.gz
SurvHiDim_0.1.1.zip(r-4.5)SurvHiDim_0.1.1.zip(r-4.4)SurvHiDim_0.1.1.zip(r-4.3)
SurvHiDim_0.1.1.tgz(r-4.5-any)SurvHiDim_0.1.1.tgz(r-4.4-any)SurvHiDim_0.1.1.tgz(r-4.3-any)
SurvHiDim_0.1.1.tar.gz(r-4.5-noble)SurvHiDim_0.1.1.tar.gz(r-4.4-noble)
SurvHiDim_0.1.1.tgz(r-4.4-emscripten)SurvHiDim_0.1.1.tgz(r-4.3-emscripten)
SurvHiDim.pdf |SurvHiDim.html✨
SurvHiDim/json (API)

# Install 'SurvHiDim' in R:

install.packages('SurvHiDim', repos = c('https://atanubhattacharjee.r-universe.dev', 'https://cloud.r-project.org'))

Datasets:

hnscc - Hnscc High dimensional genomic data on head and neck cancer

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 scripts 184 downloads 11 exports 168 dependencies

Last updated 4 years agofrom:32210cd6fc. Checks:1 OK, 7 NOTE. Indexed: yes.

Target	Result	Latest binary
Doc / Vignettes	OK	Jan 27 2025
R-4.5-win	NOTE	Jan 27 2025
R-4.5-mac	NOTE	Jan 27 2025
R-4.5-linux	NOTE	Jan 27 2025
R-4.4-win	NOTE	Jan 27 2025
R-4.4-mac	NOTE	Jan 27 2025
R-4.3-win	NOTE	Jan 27 2025
R-4.3-mac	NOTE	Jan 27 2025

Exports:hdClust hdNetwork hidimLasso hidimSurv hidimSurvbon hidimSurvbonlas hidimSurvlas hidimsvc multicoxa multicoxb survdesc

Dependencies:abind askpass assertthat backports base64enc bit bit64 blob boot broom bslib cachem callr car carData cellranger cli clipr cluster codetools colorspace conflicted corrplot cowplot cpp11 crayon crosstalk curl data.table DBI dbplyr dendextend Deriv digest doBy dplyr DT dtplyr ellipse emmeans estimability evaluate factoextra FactoMineR fansi farver fastmap flashClust fontawesome forcats foreach Formula fs gargle generics ggplot2 ggpubr ggrepel ggsci ggsignif glmnet glue googledrive googlesheets4 gridExtra gtable haven highr hms htmltools htmlwidgets httpuv httr ids igraph isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval leaps lifecycle lme4 lubridate magrittr MASS Matrix MatrixModels memoise mgcv microbenchmark mime minqa modelr multcompView munsell mvtnorm nlme nloptr nnet numDeriv openssl pbkrtest pillar pkgconfig plyr polynom prettyunits processx progress promises ps purrr quantreg R6 ragg rappdirs rbibutils RColorBrewer Rcpp RcppEigen Rdpack readr readxl reformulas rematch rematch2 reprex reshape2 rlang rmarkdown rstatix rstudioapi rvest sass scales scatterplot3d selectr shape SparseM stringi stringr survival sys systemfonts textshaping tibble tidyr tidyselect tidyverse timechange tinytex tzdb useful utf8 uuid vctrs viridis viridisLite vroom withr xfun xml2 yaml

Citation

Readme and manuals

Help Manual

Help page	Topics
hdClust	hdClust
hdNetwork	hdNetwork
hidimLasso LASSO for high dimensional data	hidimLasso
hidimSurv Survival analysis on high dimensional data	hidimSurv
hidimSurvbon Uses bonferroni correction factor in survival analysis	hidimSurvbon
hidimSurvbonlas Two step filteration using bonferroni correction and LASSO	hidimSurvbonlas
hidimSurvlas Two step filteration without bonferroni correction	hidimSurvlas
hidimsvc Survival analysis on high dimensional by creating batches of variables	hidimsvc
hnscc High dimensional genomic data on head and neck cancer	hnscc
High dimensional multivariate cox proportional hazard data analysis	multicoxa
High dimensional multivariate cox proportional hazard data analysis	multicoxb
High dimensional univariate cox proportional hazard analysis.	survdesc

Usage by other packages (reverse dependencies)