CoGAPS {CoGAPS} | R Documentation |
CoGAPS Matrix Factorization Algorithm
CoGAPS(D, S, nFactor = 7, nEquil = 1000, nSample = 1000, nOutputs = 1000, nSnapshots = 0, alphaA = 0.01, alphaP = 0.01, maxGibbmassA = 100, maxGibbmassP = 100, seed = -1, messages = TRUE, singleCellRNASeq = FALSE, whichMatrixFixed = "N", fixedPatterns = matrix(0), checkpointInterval = 0, checkpointFile = "gaps_checkpoint.out", ...)
D |
data matrix |
S |
uncertainty matrix (std devs for chi-squared of Log Likelihood) |
nFactor |
number of patterns (basis vectors, metagenes), which must be greater than or equal to the number of rows of FP |
nEquil |
number of iterations for burn-in |
nSample |
number of iterations for sampling |
nOutputs |
how often to print status into R by iterations |
nSnapshots |
the number of individual samples to capture |
alphaA |
sparsity parameter for A domain |
alphaP |
sparsity parameter for P domain |
maxGibbmassA |
limit truncated normal to max size |
maxGibbmassP |
limit truncated normal to max size |
seed |
a positive seed is used as-is, while any negative seed tells the algorithm to pick a seed based on the current time |
messages |
display progress messages |
singleCellRNASeq |
indicates if the data is single cell RNA-seq data |
whichMatrixFixed |
character to indicate whether A or P matric contains the fixed patterns |
fixedPatterns |
matrix of fixed values in either A or P matrix |
checkpointInterval |
time (in seconds) between creating a checkpoint |
checkpointFile |
name of the checkpoint file |
... |
keeps backwards compatibility with arguments from older versions |
calls the C++ MCMC code and performs Bayesian matrix factorization returning the two matrices that reconstruct the data matrix
list with A and P matrix estimates
data(SimpSim) result <- CoGAPS(SimpSim.D, SimpSim.S, nFactor=3, nOutputs=250)