sarksFilters: Smoothing window and Gini impurity filter settings

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

Description

Sarks methodology involves testing a range of different filter parameter values; sarksFilters builds set of filters with all combinations of desired halfWindow, spatialLength, and minGini values.

Usage

sarksFilters(halfWindow, spatialLength, minGini = 1.1)

Arguments

halfWindow	integer vector of halfWindow values to test.
spatialLength	integer vector of spatialLength values to test; use a single 0 value to disable spatial smoothing.
minGini	numeric vector giving minimum Gini impurity value(s) for suffix position to be analyzed; use a value above 1 to calculate minimum Gini impurity based on median of observed Gini impurities so as to constrain variance under permutation testing to less than minGini multiples of median variance.

Value

R representation of java object containing specified combinations of filter parameters for running permutation tests.

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=c(4, 8), spatialLength=c(0, 5), minGini=1.1)

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