permutationDistribution: Estimating distribution of maximum smoothed sequence scores...

In sarks: Suffix Array Kernel Smoothing for discovery of correlative sequence motifs and multi-motif domains

Description

Run permutation test using the specified number of repetitions, keeping track of maximum observed windowed and spatially-windowed smoothed scores for each combination of filter parameters for each permutation.

Usage

permutationDistribution(sarks, reps, filters, seed = NULL)

Arguments

sarks	Sarks object to test.
reps	integer specifying how many repetitions to test.
filters	output from sarksFilters function indicating what combinations of filter parameters halfWindow, spatialLength, and minGini to use.
seed	optional seed for random number generator (use in case reproducibility of output is desired).

Value

named list with three elements: ‘windowed’ containing a data.frame with the maximum smoothed scores for each permutation at each combination of filter parameter values, ‘spatial’ containing a data.frame with the maximum spatially-smoothed scores for each permutation and each filter parameter specification, and ‘.java’ containing the R representation of the java object encoding this information.

References

Wylie, D.C., Hofmann, H.A., and Zemelman, B.V. (2019) SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing, Bioinformatics, Vol. 35(20), 3944-3952

https://academic.oup.com/bioinformatics/article-abstract/35/20/3944/5418797

Examples

data(simulatedSeqs, simulatedScores)
sarks <- Sarks(simulatedSeqs, simulatedScores, 4, 0, 1)
filters <- sarksFilters(halfWindow=4, spatialLength=0, minGini=1.1)
permDist <- permutationDistribution(sarks, 250, filters, seed=123)

sarks documentation built on Nov. 8, 2020, 6:54 p.m.