Package: crso 0.1.1
crso: Cancer Rule Set Optimization ('crso')
An algorithm for identifying candidate driver combinations in cancer. CRSO is based on a theoretical model of cancer in which a cancer rule is defined to be a collection of two or more events (i.e., alterations) that are minimally sufficient to cause cancer. A cancer rule set is a set of cancer rules that collectively are assumed to account for all of ways to cause cancer in the population. In CRSO every event is designated explicitly as a passenger or driver within each patient. Each event is associated with a patient-specific, event-specific passenger penalty, reflecting how unlikely the event would have happened by chance, i.e., as a passenger. CRSO evaluates each rule set by assigning all samples to a rule in the rule set, or to the null rule, and then calculating the total statistical penalty from all unassigned event. CRSO uses a three phase procedure find the best rule set of fixed size K for a range of Ks. A core rule set is then identified from among the best rule sets of size K as the rule set that best balances rule set size and statistical penalty. Users should consult the 'crso' vignette for an example walk through of a full CRSO run. The full description, of the CRSO algorithm is presented in: Klein MI, Cannataro V, Townsend J, Stern DF and Zhao H. "Identifying combinations of cancer driver in individual patients." BioRxiv 674234 [Preprint]. June 19, 2019. <doi:10.1101/674234>. Please cite this article if you use 'crso'.
Authors:
crso_0.1.1.tar.gz
crso_0.1.1.zip(r-4.5)crso_0.1.1.zip(r-4.4)crso_0.1.1.zip(r-4.3)
crso_0.1.1.tgz(r-4.4-any)crso_0.1.1.tgz(r-4.3-any)
crso_0.1.1.tar.gz(r-4.5-noble)crso_0.1.1.tar.gz(r-4.4-noble)
crso_0.1.1.tgz(r-4.4-emscripten)crso_0.1.1.tgz(r-4.3-emscripten)
crso.pdf |crso.html✨
crso/json (API)
| # Install 'crso' in R: |
| install.packages('crso', repos = c('https://michaelklein916.r-universe.dev', 'https://cloud.r-project.org')) |
- skcm.list - Example data set derived from TCGA skin cutaneous melanoma (SKCM) data.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:4e4ab3a370. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 16 2024 |
| R-4.5-win | OK | Sep 16 2024 |
| R-4.5-linux | OK | Sep 16 2024 |
| R-4.4-win | OK | Sep 16 2024 |
| R-4.4-mac | OK | Sep 16 2024 |
| R-4.3-win | OK | Sep 16 2024 |
| R-4.3-mac | OK | Sep 16 2024 |
Exports:buildRuleLibraryevaluateListOfIMsgetBestRsListgetCoreKgetCoreRSgetGCDsgetGCEsgetGCRsgetPoolSizesgetRulesAsStringsmakeFilteredImListmakePhaseOneOrderedRMmakePhaseThreeImListmakePhaseTwoImListmakeSubCoreList
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Make full rule library of all rules that satisfy minimum coverage threshold. | buildRuleLibrary |
| Evaluate list of rule set matrices | evaluateListOfIMs |
| Get list of best rule sets of size K for all K | getBestRsList |
| Determine core K from phase 3 tpl and til | getCoreK |
| Get core rules from phase 3 tpl and til | getCoreRS |
| Get Generalized Core Duos | getGCDs |
| Get Generalized Core Events | getGCEs |
| Get Generalized Core Rules | getGCRs |
| Get pool sizes for phase 2 | getPoolSizes |
| Represent binary rule matrix as strings | getRulesAsStrings |
| Make filtered im list from phase 3 im list | makeFilteredImList |
| Order rules according to phase one importance ranking | makePhaseOneOrderedRM |
| Make phase 3 im list from phase 2 im list | makePhaseThreeImList |
| Output list of top rule sets for each k in 1:k.max | makePhaseTwoImList |
| Get list of core rules from random subsets of samples | makeSubCoreList |
| Example data set derived from TCGA skin cutaneous melanoma (SKCM) data. | skcm.list |
