Package: crso
Title: Cancer Rule Set Optimization ('crso')
Version: 0.1.1
Author: Michael Klein <michael.klein@yale.edu>
Maintainer: Michael Klein <michael.klein@yale.edu>
Description: 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'.
Depends: R (>= 3.5.0), foreach
Imports: stats, utils
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-07-04 20:36:20 UTC; michaelklein
Repository: CRAN
Date/Publication: 2019-07-07 17:00:03 UTC

Title: Tidying and Analyzing 'Coursera' Research Export Data
family = "Hadavand", email ="hadavand.a@gmail.com",
role = c("aut", "cre")), person(given = "Jeff",
person(given = "John", family = "Muschelli", role = "aut"))
Description: Tidies and performs preliminary analysis of 'Coursera' research
export data. These export data can be downloaded by anyone who has classes
on Coursera and wants to analyze the data. Coursera is one of the leading
providers of MOOCs and was launched in January 2012. With over 25 million
learners, Coursera is the most popular provider in the world being followed
by EdX, the MOOC provider that was a result of a collaboration between
Harvard University and MIT, with over 10 million users. Coursera has over
150 university partners from 29 countries and offers a total of 2000+
courses from computer science to philosophy. Besides, Coursera offers 180+
specialization, Coursera's credential system, and four fully online Masters
degrees. For more information about Coursera check Coursera's
Imports: dplyr, purrr, readr, digest, tidytext, tibble, rcorpora, knitr