CoGAPS calls the C++ MCMC code through gapsRun and performs Bayesian
matrix factorization returning the two matrices that reconstruct
the data matrix and then calls calcCoGAPSStat to estimate gene set
activity with nPerm set to 500gapsMapRun calls the C++ MCMC code and performs Bayesian
matrix factorization returning the two matrices that reconstruct
the data matrix; as opposed to gapsRun, this method takes an
additional input specifying set patterns in the P matrixplotAtoms a simple plot of the number of atoms
from one of the vectors returned with atom numberscalcZ calculates the Z-score for each element based
on input mean and standard deviation matricesresiduals calculate residuals and produce heatmapgapsMapTestRun calls the C++ MCMC code and performs Bayesian
matrix factorization returning the two matrices that reconstruct
the data matrix; as opposed to gapsRun, this method takes an
additional input specifying set patterns in the P matrix.
Test procedures allow for the returning of the matrix
and atomic information for A and P during each step of the equilibration and sampling.plotP plots the P matrix in a line plot
with error barsplotDiag plots a series of diagnostic plotsbinaryA creates a binarized heatmap of the A matrix
in which the value is 1 if the value in Amean is greater than
threshold * Asd and 0 otherwisegapsIntraPattern generates statistics for the similarity
of gene expression vectors within a patterngapsRun calls the C++ MCMC code and performs Bayesian
matrix factorization returning the two matrices that reconstruct
the data matrixgapsInterPattern calculates statistics for measuring
the distance between patterns based on genes associated with
the patternsgapsTestRun calls the C++ MCMC code and performs Bayesian
matrix factorization returning the two matrices that reconstruct
the data matrix. Test procedures allow for the returning of the matrix
and atomic information for A and P during each step of the equilibration and sampling. .