FLLat: Fused Lasso Latent Feature Model

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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.

Author
Gen Nowak [aut, cre], Trevor Hastie [aut], Jonathan R. Pollack [aut], Robert Tibshirani [aut], Nicholas Johnson [aut]
Date of publication
2015-09-16 12:47:04
Maintainer
Gen Nowak <gen.nowak@gmail.com>
License
GPL (>= 2)
Version
1.2

View on CRAN

Man pages

FLLat
Fused Lasso Latent Feature Model
FLLat.BIC
Optimal Tuning Parameters for the Fused Lasso Latent Feature...
FLLat.FDR
False Discovery Rate for the Fused Lasso Latent Feature Model
FLLat.PVE
Choosing the Number of Features for the Fused Lasso Latent...
plot.FLLat
Plots Results from the Fused Lasso Latent Feature Model
predict.FLLat
Predicted Values and Weights based on the Fused Lasso Latent...
simaCGH
Simulated aCGH Data

Files in this package

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