getUniverse | R Documentation |
'getUniverse' returns a 'GRanges' object with all the genomic regions in a data set, that can be used for AMR enrichment analysis
getUniverse(data.ranges, merge.window = 300, min.cpgs = 7, min.width = 1)
data.ranges |
A 'GRanges' object with genomic locations and corresponding beta values included as metadata. |
merge.window |
A single integer >= 1. All 'data.ranges' genomic locations within this distance will be merged (the default: 300). |
min.cpgs |
A single integer >= 1. All genomic regions containing less than 'min.cpgs' genomic locations are filtered out (the default: 7). |
min.width |
A single integer >= 1 (the default). Only regions with the width of at least 'min.width' are returned. |
In the provided data set 'getUniverse' merges and outputs all the genomic regions that satisfy filtering criteria, thus creating a 'GRanges' object to be used as a reference set of genomic regions for AMR enrichment analysis.
The output is a 'GRanges' object that contain all the genomic regions in 'data.ranges' object (in other words, all potential AMRs).
getAMR
for identification of AMRs,
plotAMR
for plotting AMRs, simulateAMR
and
simulateData
for the generation of simulated test data sets,
and 'ramr' vignettes for the description of usage and sample data.
data(ramr) universe <- getUniverse(ramr.data, min.cpgs=5, merge.window=1000) # identify AMRs amrs <- getAMR(ramr.data, ramr.samples, ramr.method="beta", min.cpgs=5, merge.window=1000, qval.cutoff=1e-3, cores=2) # AMR enrichment analysis using LOLA library(LOLA) # download LOLA region databases from http://databio.org/regiondb hg19.extdb.file <- system.file("LOLAExt", "hg19", package="LOLA") if (file.exists(hg19.extdb.file)) { hg19.extdb <- loadRegionDB(hg19.extdb.file) runLOLA(amrs, universe, hg19.extdb, cores=1, redefineUserSets=TRUE) }
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