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FLLat (version 1.2)

Fused Lasso Latent Feature Model

Description

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.

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Version

Install

install.packages('FLLat')

Monthly Downloads

442

Version

1.2

License

GPL (>= 2)

Maintainer

Last Published

September 16th, 2015

Functions in FLLat (1.2)

predict.FLLat

Predicted Values and Weights based on the Fused Lasso Latent
simaCGH

Simulated aCGH Data
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 Feature
plot.FLLat

Plots Results from the Fused Lasso Latent Feature Model
FLLat

Fused Lasso Latent Feature Model