RGBM v1.0-4

0

Monthly downloads

0th

Percentile

by Raghvendra Mall

LS-TreeBoost and LAD-TreeBoost for Gene Regulatory Network Reconstruction

Provides an implementation of Regularized LS-TreeBoost & LAD-TreeBoost algorithm for Regulatory Network inference from any type of expression data (Microarray/RNA-seq etc).

Functions in RGBM

Name Description
GBM
GBM.train
GBM.test
get_colids
apply_row_deviation
get_ko_experiments
consider_previous_information
first_GBM_step
add_names
get_filepaths
second_GBM_step
get_tf_indices
RGBM.test
RGBM.train
normalize_matrix_colwise
regulate_regulon_size
RGBM
regularized_GBM_step
null_model_refinement_step
select_ideal_k
transform_importance_to_weights
z_score_effect
v2l
test_regression_stump_R
train_regression_stump_R
No Results!

Last month downloads

Details

Type Package
Date 2017-02-21
Repository CRAN
License GPL (>= 3)
LazyLoad yes
NeedsCompilation yes
Packaged 2017-02-21 06:58:57 UTC; rmall
Date/Publication 2017-02-21 08:43:21

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/RGBM)](http://www.rdocumentation.org/packages/RGBM)