PREDA_main: function performing the core of PREDA analysis
In PREDA: Position Related Data Analysis

Description Usage Arguments Details Value Author(s) See Also Examples

function performing the core of PREDA analysis

PREDA_main(inputDataForPREDA, outputGenomicAnnotationsForPREDA
=NULL, nperms = 10000, verbose = TRUE, parallelComputations =
FALSE, multTestCorrection = "fdr", permutePerChromosome = FALSE,
blocksize = 10, permuteStatisticSign = FALSE, smoothMethod =
"lokern_scaledBandwidth_repeated", force = FALSE,
lokern_scaledBandwidthFactor = 2, limit.analysis = NULL)

`inputDataForPREDA`	A Data for PREDA object
`outputGenomicAnnotationsForPREDA`	A GenomicAnnotationsForPREDA object. If NULL, GenomicsAnnotations for output data are obtained from inputDataForPREDA
`nperms`	Number of permutations performed in PREDA analysis.
`verbose`	Logical, if TRUE some messages are printed concenrning the advancement of the analysis.
`parallelComputations`	Logical, if TRUE Rmpi is used to spawn slave processes, thus using parallel computing to speedup the analysis.
`multTestCorrection`	Multiple testing correction that will be adopted to correct the statistic p-values. Possible values are "fdr", for benjamini and Hochberg multiple testing correction and "qvalue" for p-values correction performed with qvalue package.
`permutePerChromosome`	Logical, if TRUE data parmutations are perfored separatedly for each chromsoome. In most cases the default value (FALSE) is preferable to avoid biases related to specific chromosomes extreme alterations.
`blocksize`	A parameter used to tune parallel computations if parallelComputations is TRUE. This is actually the number of permutations performed on each slave process before every communication with master process. This is useftul to reduce the numebr of network communications when slow communicatinos are established among slave processes.
`permuteStatisticSign`	Logical, if TRUE statistics signs are permuted instead of permuting data along chromsomal position.
`smoothMethod`	The deafault smoothing metod used in the PREDA_main function is lokern smoothing with scaled bandwidth, using a scaling factor equal to 2. Possible values are "lokern", for standard lokern smoothing, "quantsmooth", "spline" and "runningmean.x", where x is a user defined value for the number of adjacent data points using for running mean smoothing.
`force`	Logical, if TRUE force skipping quantsmooth control on number of data points. Singe quantsmooth is very slow with a high number of inpuit data, a check stopping computation with more than 2000 data points in one or more chromosome was introduced. This aprameter allow skippin this security check.
`lokern_scaledBandwidthFactor`	Factor of scaling for lokern estimated bandwidths
`limit.analysis`	Vector (numeric or character representing analyses names) to limit the output of preda analysis to a subset of input analyses.