Calculates binding enrichment for motif(s)

Perform a binomial test to determine if SNP Effect Matrices are bound more often than expected.

Usage

enrichSEMs(x, sem, background = NULL, seqs = NULL, nFlank = 0, genome = NULL)

Arguments

x: The scoring table produced by scoreBinding
sem: A SNPEffectMatrix or SNPEffectMatrixCollection object
background: A GRanges object or a list of DNA sequences to use as a background set for the binomial test. The length of each sequence must match the length of sequences in x. By default, will scramble the provided sequences.
seqs: The sequences scored in scoreBinding
nFlank: Number of flanking nucleotides added to the sequences. Defaults to the length of the longest motif. If no flanks were added (ie, sequences were scored rather than a GRanges), use nFlank = 0.
genome: A BSGenome object. Requried if background isn't specified.

Value

a list of matrices

Examples


# load SEMs
data(SEMC)

# note that this is a small example for demonstration purposes
# in actual enrichment analyses sets of 100+ ranges are recommended

# create a GRanges object
gr <- GenomicRanges::GRanges(
    seqnames = "chr12",
    ranges = 94136009
)

# calculate binding propensity
sb <- scoreBinding(gr, SEMC, BSgenome.Hsapiens.UCSC.hg19::Hsapiens)

enrichSEMs(sb, SEMC)
#> Building background set (this may take several minutes) ...
#>         SEM pvalue  padj n_bound n_bound_bg
#>      <char>  <num> <num>   <int>      <int>
#>   1: TFAP2B      1     1       0          0
#>   2:   ARNT      1     1       0          0
#>   3:   ATF1      1     1       0          0
#>   4:   ATF2      1     1       0          0
#>   5:   ATF3      1     1       0          0
#>  ---                                       
#> 219: ZBTB7A      1     1       0          0
#> 220:    ZFX      1     1       0          0
#> 221: ZNF281      1     1       0          0
#> 222:  ZNF18      1     1       0          0
#> 223: ZSCAN4      1     1       0          0