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'.

Version: 0.1.1
Depends: R (≥ 3.5.0), foreach
Imports: stats, utils
Suggests: knitr, rmarkdown
Published: 2019-07-07
Author: Michael Klein
Maintainer: Michael Klein <michael.klein at yale.edu>
License: GPL-2
NeedsCompilation: no
CRAN checks: crso results

Downloads:

Reference manual: crso.pdf
Vignettes: CRSO-vignette
Package source: crso_0.1.1.tar.gz
Windows binaries: r-devel: crso_0.1.1.zip, r-release: crso_0.1.1.zip, r-oldrel: crso_0.1.1.zip
OS X binaries: r-release: crso_0.1.1.tgz, r-oldrel: crso_0.1.1.tgz

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