FLLat: Fused Lasso Latent Feature Model

Fits the Fused Lasso Latent Feature model, which is used for modeling multi-sample aCGH data to identify regions of copy number variation (CNV). Produces a set of features that describe the patterns of CNV and a set of weights that describe the composition of each sample. Also provides functions for choosing the optimal tuning parameters and the appropriate number of features, and for estimating the false discovery rate.

Install the latest version of this package by entering the following in R:
install.packages("FLLat")
AuthorGen Nowak [aut, cre], Trevor Hastie [aut], Jonathan R. Pollack [aut], Robert Tibshirani [aut], Nicholas Johnson [aut]
Date of publication2015-09-16 12:47:04
MaintainerGen Nowak <gen.nowak@gmail.com>
LicenseGPL (>= 2)
Version1.2

View on CRAN

Files

inst
inst/doc
inst/doc/FLLat_tutorial.rnw
inst/doc/FLLat_tutorial.R
inst/doc/FLLat_tutorial.pdf
src
src/L2L1VitExact.c
src/Lat_L2.cpp
src/gen_lat_func.h
src/gen_lat_func.cpp
src/FL.h
NAMESPACE
NEWS
data
data/simaCGH.RData
R
R/plot.PVE.R R/FLLat.BIC.R R/plot.FDR.R R/FLLat.PVE.R R/Max.Lam0.R R/predict.FLLat.R R/FLLat.FDR.R R/CheckPars.R R/FLLat.R R/plot.FLLat.R
vignettes
vignettes/FLLat_tutorial.rnw
MD5
build
build/vignette.rds
DESCRIPTION
man
man/plot.FLLat.Rd man/FLLat.FDR.Rd man/FLLat.PVE.Rd man/simaCGH.Rd man/FLLat.Rd man/FLLat.BIC.Rd man/predict.FLLat.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.