pairadise {PAIRADISE} | R Documentation |
Primary function of the PAIRADISE package. Analyzes matched pairs for differences in isoform expression. Uses parallel processing to speed up computation.
pairadise(pdat, nIter = 100, tol = 10^(-2), pseudocount = 0, seed = 12321, equal.variance = FALSE, numCluster = 2, BPPARAM = MulticoreParam(numCluster))
pdat |
A PDseDataSet object |
nIter |
Positive integer. Specifies the maximum number of iterations of the optimization algorithm allowed. Default is nIter = 100 |
tol |
Positive number. Specifies the tolerance level for terminating the optimization algorithm, defined as the difference in log-likelihood ratios between iterations. Default is tol = 10^(-2) |
pseudocount |
Positive number. Specifies a value for a pseudocount added to each count at the beginning of the analysis. Default is pseudocount = 0 |
seed |
An integer to set seed. |
equal.variance |
Are the group variances assumed equal? Default value is FALSE. |
numCluster |
Number of clusters to use for parallel computing. |
BPPARAM |
parallel parameters from package BiocParallel. |
This is the primary function of the PAIRADISE package that implements the PAIRADISE algorithm.
A PDseDataSet object contains outputs from PAIRADISE algorithm.
############################# ## Example: Simulated data ## ############################# set.seed(12345) data("sample_dataset") pdat <- PDseDataSetFromMat(sample_dataset) pdat <- pairadise(pdat, numCluster =4) results(pdat)