Description Usage Arguments Value Examples
Performs a twostep approach that (1) detects candidate regions, and (2) scores candidate regions with an exchangeable (across the genome) statistic and evaluates statistical significance using a permuation test on the pooled null distribution of scores.
1 2 3 4 5  dmrseq(bs, testCovariate, adjustCovariate = NULL, cutoff = 0.1,
minNumRegion = 5, smooth = TRUE, bpSpan = 1000, minInSpan = 30,
maxGapSmooth = 2500, maxGap = 1000, verbose = TRUE,
maxPerms = 10, matchCovariate = NULL, BPPARAM = bpparam(),
stat = "stat", block = FALSE, blockSize = 5000, chrsPerChunk = 1)

bs 
bsseq object containing the methylation values as well as the phenotype matrix that contains sample level covariates 
testCovariate 
Character value indicating which variable
(column name) in 
adjustCovariate 
an (optional) character value or vector
indicating which variables (column names) in 
cutoff 
scalar value that represents the absolute value (or a vector of two numbers representing a lower and upper bound) for the cutoff of the single CpG coefficient that is used to discover candidate regions. Default value is 0.10. 
minNumRegion 
positive integer that represents the minimum number of CpGs to consider for a candidate region. Default value is 5. Minimum value is 3. 
smooth 
logical value that indicates whether or not to smooth the CpG level signal when discovering candidate regions. Defaults to TRUE. 
bpSpan 
a positive integer that represents the length in basepairs
of the smoothing span window if 
minInSpan 
positive integer that represents the minimum number of
CpGs in a smoothing span window if 
maxGapSmooth 
integer value representing maximum number of basepairs
in between neighboring CpGs to be included in the same
cluster when performing smoothing (should generally be larger than

maxGap 
integer value representing maximum number of basepairs in between neighboring CpGs to be included in the same DMR. 
verbose 
logical value that indicates whether progress messages should be printed to stdout. Defaults value is TRUE. 
maxPerms 
a positive integer that represents the maximum number of permutations that will be used to generate the global null distribution of test statistics. Default value is 10. 
matchCovariate 
An (optional) character value
indicating which variable (column name) of 
BPPARAM 
a 
stat 
a character vector indicating the name of the column of the output to use as the regionlevel test statistic. Default value is 'stat' which is the region levelstatistic designed to be comparable across the genome. It is not recommended to change this argument, but it can be done for experimental purposes. Possible values are: 'L'  the number of loci in the region, 'area'  the sum of the smoothed loci statistics, 'beta'  the effect size of the region, 'stat'  the test statistic for the region, or 'avg'  the average smoothed loci statistic. 
block 
logical indicating whether to search for largescale (low
resolution) blocks of differential methylation (default is FALSE, which
means that local DMRs are desired). If TRUE, the parameters for

blockSize 
numeric value indicating the minimum number of basepairs
to be considered a block (only used if 
chrsPerChunk 
a positive integer value indicating the number of chromosomes per chunk. The default is 1, meaning that the data will be looped through one chromosome at a time. When pairing up multiple chromosomes per chunk, sizes (in terms of numbers of CpGs) will be taken into consideration to balance the sizes of each chunk. 
a GRanges
object that contains the results of the inference.
The object contains one row for each candidate region, sorted by qvalue
and then chromosome. The standard
GRanges
chr, start, and end are included, along with at least
7 metadata
columns, in the following order:
1. L = the number of CpGs contained in the region,
2. area = the sum of the smoothed beta values
3. beta = the coefficient value for the condition difference (there
will be more than one column here if a multigroup comparison
was performed),
4. stat = the test statistic for the condition difference,
5. pval = the permutation pvalue for the significance of the test
statistic, and
6. qval = the qvalue for the test statistic (adjustment
for multiple comparisons to control false discovery rate).
7. index = an IRanges
containing the indices of the region's
first CpG to last CpG.
1 2 3 4 5 6 7 8 9 10 
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