SimpSim.S

Standard deviation of simulated gene expression data from true patterns in <code><a rd-options="" href="/link/SimpSim.P?package=CoGAPS&version=2.6.0" data-mini-rdoc="CoGAPS::SimpSim.P">SimpSim.P</a></code> and amplitude in <code><a rd-options="" href="/link/SimpSim.A?package=CoGAPS&version=2.6.0" data-mini-rdoc="CoGAPS::SimpSim.A">SimpSim.A</a></code>.

datasets

Coordinated Gene Activity in Pattern Sets (CoGAPS)
implements a Bayesian MCMC matrix factorization algorithm,
GAPS, and links it to gene set statistic methods to infer biological
process activity.  It can be used to perform sparse matrix factorization on
any data, and when this data represents biomolecules, to do gene set
analysis.

Elana J Fertig

CoGAPS

Coordinated Gene Activity in Pattern Sets

SimpSim.S function

Matrix with 30 genes by 20 samples of containing standard deviation of simulated gene expression data.

Format

Standard deviation of simulated gene expression data from true patterns in <code><a href="SimpSim.P" rd-options="">SimpSim.P</a></code> and amplitude in <code><a href="SimpSim.A" rd-options="">SimpSim.A</a></code>.

SimpSim.S: Simulated data

Description

Usage

Arguments

Format