Calculate risk/non-risk binding propensity for all SEM motifs and variants provided

Usage

scoreVariants(
  x,
  sem,
  genome,
  refCol = NULL,
  altCol = NULL,
  varId = NULL,
  rc = TRUE
)

Arguments

x: VRanges object
sem: a list of SNPEffectMatrix objects
genome: A BSgenome object for the genome build to use. ie. BSgenome.Hsapiens.UCSC.hg19::Hsapiens
refCol: If providing a GRanges, the meta data column name with the reference (ref) allele. Ignored if providing a VRanges object.
altCol: If providing a GRanges, the meta data column name with the alternative (alt) allele. Ignored if providing a VRanges object.
varId: A column name in the meta data of x to use as a unique id.
rc: plot the reverse complement SEMs

Value

a SEMScores object with slots for the ranges of the provided variants with an added sequence column with the sequence scored, the SEM metadata, and the resulting scoring table. These slots are accessible with the getRanges(), semData(), and scores() accessor functions respectively.

The scoring table will contain the following columns:

varId: a unique identifier for the sequence scored
SEM: the identifier for the SEM
rc: the orientation of the sequence (fwd or rev)
score: the unnormalized SEM score
scoreNorm: the SEM score normalized to it's corresponding baseline
index: the index of the motif with the highest SEM score within the sequence scored
seq: the motif sequence with the highest SEM scores within the sequence scored

Examples

library(VariantAnnotation)

# load default SEMs

# create a VRanges object
x <- VRanges(
    seqnames = "chr12",
    ranges = 94136009,
    ref = "G", alt = "C"
)

# calculate binding propensity
scoreVariants(x, SEMC, BSgenome.Hsapiens.UCSC.hg19::Hsapiens)
#> An object of class SEMScores
#> ranges(1): 
#> semData(12): transcription_factor, ensembl_id ... dnase_ENCODE_accession, PWM_source
#> scores(446):
#>                   varId            SEM     rc           refSeq           altSeq
#>                  <char>         <char> <char>           <char>           <char>
#>   1: chr12:94136009:G>C            AHR    fwd      TTTGAGGCATC      TTCAGGCATCT
#>   2: chr12:94136009:G>C            AHR    rev      TTTGAGGCATC      TTTCAGGCATC
#>   3: chr12:94136009:G>C AHR:ARNT:HIF1A    fwd        GGCTTTGAG        GGCTTTCAG
#>   4: chr12:94136009:G>C AHR:ARNT:HIF1A    rev        GGCTTTGAG        TTTCAGGCA
#>   5: chr12:94136009:G>C         ARID3A    fwd           TTTGAG           TTCAGG
#>  ---                                                                           
#> 442: chr12:94136009:G>C         ZNF217    rev         CTTTGAGG         CTTTCAGG
#> 443: chr12:94136009:G>C         ZNF281    fwd  GGAGAAGGCTTTGAG  AAGGAGAAGGCTTTC
#> 444: chr12:94136009:G>C         ZNF281    rev  GGCTTTGAGGCATCT  GGCTTTCAGGCATCT
#> 445: chr12:94136009:G>C         ZSCAN4    fwd GCTTTGAGGCATCTGC GCTTTCAGGCATCTGC
#> 446: chr12:94136009:G>C         ZSCAN4    rev GCTTTGAGGCATCTGC GCTTTCAGGCATCTGC
#>        refScore   altScore    refNorm    altNorm refVarIndex altVarIndex
#>           <num>      <num>      <num>      <num>       <int>       <int>
#>   1:  -1.495324  -1.393158 -0.4349553 -0.3934902          17          18
#>   2:  -1.354220  -1.158371 -0.3768978 -0.2862997          17          17
#>   3:  -1.304220  -1.308236 -0.3888573 -0.3905561          14          14
#>   4:  -1.266234  -1.086663 -0.3725524 -0.2893862          14          17
#>   5:  -1.400445  -1.428525 -0.4994304 -0.5090790          17          18
#>  ---                                                                    
#> 442:  -1.202679  -1.517704 -0.4025273 -0.5197292          16          16
#> 443:  -4.347612  -4.740351 -0.9355197 -0.9508865           8           6
#> 444:  -5.713722  -4.886938 -0.9749858 -0.9556316          14          14
#> 445: -15.439087 -13.002975 -0.9998307 -0.9990837          15          15
#> 446: -14.469707 -12.918336 -0.9996685 -0.9990284          15          15