Package: kmcut 1.1.0
kmcut: Optimized Kaplan Meier analysis and identification and validation of prognostic biomarkers
The purpose of the package is to identify prognostic biomarkers and an optimal numeric cutoff for each biomarker that can be used to stratify a group of test subjects (samples) into two sub-groups with significantly different survival (better vs. worse). The package was developed for the analysis of gene expression data, such as RNA-seq. However, it can be used with any quantitative variable that has a sufficiently large proportion of unique values.
Authors:
kmcut_1.1.0.tar.gz
kmcut_1.1.0.zip(r-4.5)kmcut_1.1.0.zip(r-4.4)kmcut_1.1.0.zip(r-4.3)
kmcut_1.1.0.tgz(r-4.4-any)kmcut_1.1.0.tgz(r-4.3-any)
kmcut_1.1.0.tar.gz(r-4.5-noble)kmcut_1.1.0.tar.gz(r-4.4-noble)
kmcut_1.1.0.tgz(r-4.4-emscripten)kmcut_1.1.0.tgz(r-4.3-emscripten)
kmcut.pdf |kmcut.html✨
kmcut/json (API)
NEWS
# Install 'kmcut' in R: |
install.packages('kmcut', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:kmcut-1.1.0(bioc 3.21)kmcut-1.0.0(bioc 3.20)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
softwarestatisticalmethodgeneexpressionsurvival
Last updated 2 months agofrom:da83cfdc6a. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 29 2024 |
R-4.5-win | OK | Nov 29 2024 |
R-4.5-linux | OK | Nov 29 2024 |
R-4.4-win | OK | Nov 29 2024 |
R-4.4-mac | OK | Nov 29 2024 |
R-4.3-win | OK | Nov 29 2024 |
R-4.3-mac | OK | Nov 29 2024 |
Exports:create_se_objectextract_columnsextract_rowskm_opt_pcutkm_opt_scutkm_qcutkm_ucutkm_val_cuttranspose_tableucox_batchucox_pred
Dependencies:abindaskpassBiobaseBiocGenericscodetoolscrayoncurlDelayedArraydoParallelforeachgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangeshttrIRangesiteratorsjsonlitelatticeMatrixMatrixGenericsmatrixStatsmimeopensslpracmaR6S4ArraysS4VectorsSparseArraySummarizedExperimentsurvivalsysUCSC.utilsXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create SummarizedExperiment object | create_se_object |
Extract a sub-set of columns | extract_columns |
Extract a sub-set of rows | extract_rows |
Find and evaluate optimal stratification cutoffs | km_opt_pcut |
Find optimal stratification cutoffs | km_opt_scut |
Apply quantile-based stratification cutoffs | km_qcut |
Apply user-supplied stratification cutoff | km_ucut |
Validate stratification cutoffs on test data | km_val_cut |
Transpose a data table | transpose_table |
Fit Cox regression models in batch mode | ucox_batch |
Fit and validate Cox regression models | ucox_pred |