get_ko_experiments


  N-by-p initial perturbation matrix. It directly corresponds to E matrix, e.g. if K[i,j] is equal to 1, it means that gene j was knocked-out in experiment i. Single gene knock-out experiments are rows of K with only one value 1. Colnames of K is set to be the set of all genes.  By default it&#39;s a matrix of zeros of the same size as E, e.g. unknown initial perturbation state of genes.


This function provides the indices of all those samples (out of N) where it is known apriori that a gene was either knocked-out or was knocked-down. This information is useful for the <code><a rd-options="" href="/link/null_model_refinement_step?package=RGBM&version=1.0-4" data-mini-rdoc="RGBM::null_model_refinement_step">null_model_refinement_step</a></code> which utilizes the <code><a rd-options="" href="/link/z_score_effect?package=RGBM&version=1.0-4" data-mini-rdoc="RGBM::z_score_effect">z_score_effect</a></code> technique (with the help of this information).

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

Raghvendra Mall

RGBM

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

get_ko_experiments function

This function provides the indices of all those samples (out of N) where it is known apriori that a gene was either knocked-out or was knocked-down. This information is useful for the <code><a rd-options='' href='null_model_refinement_step'>null_model_refinement_step</a></code> which utilizes the <code><a rd-options='' href='z_score_effect'>z_score_effect</a></code> technique (with the help of this information).

get_ko_experiments:

Description

Usage

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See Also