Extract the per-variant posterior fine-mapping payload as either
a data.frame (default) or a GRanges. Returns identity columns
(variant_id, chrom, pos, A1, A2), context (N, MAF), the
posterior effect columns (beta = posterior_mean, se = posterior_sd),
pip, and credible-set membership columns (cs_95, etc.). Rows
are filtered by PIP by default – set signalCutoff = 0 to return
every variant.
Usage
topLoci(x, signalCutoff = 0.025, ...)
# S4 method for class 'FineMappingResultBase'
topLoci(
x,
signalCutoff = 0.025,
studyName = NULL,
context = NULL,
trait = NULL,
method = NULL,
region = NULL,
minPurity = NULL,
raw = FALSE
)Arguments
- x
A
QtlFineMappingResultorGwasFineMappingResult.- signalCutoff
Numeric (length 1). Drop rows where
pip <= signalCutoff. Default0.025. UsesignalCutoff = 0to keep every variant.- ...
Class-specific selection arguments.
- studyName
Character (length 1) or
NULL. Restrict the selection to this study;NULLmatches all studies.- context
Character (length 1) or
NULL. Restrict the selection to this context;NULLmatches all contexts.- trait
Character (length 1) or
NULL. Restrict the selection to this trait;NULLmatches all traits.- method
Character (length 1) or
NULL. Restrict the selection to this fine-mapping / weight method;NULLmatches all methods.- region
Character (length 1,
"chr:start-end") orNULL. Restrict variants to this region;NULLuses the full cis window / all regions.- minPurity
Numeric or
NULL. Minimum credible-set purity to retain;NULLapplies no purity filter.- raw
Logical (length 1).
FALSE(default) returns the posterior view described above.TRUEhands back the stored canonical table verbatim – adata.frame, not aGRanges– so neither the projection norsignalCutoffapplies.
Value
A GRanges, one range per retained variant, carrying the
per-variant columns in mcols(); when the selectors match more than
one entry the row-identity columns are carried there too. Take a table
with as.data.frame() (which adds the standard
seqnames/start/... columns) or
as.data.frame(S4Vectors::mcols(.)) for the per-variant columns
alone. raw = TRUE returns the stored data.frame instead.
Examples
data(qtlFineMappingExample)
topLoci(qtlFineMappingExample)
#> GRanges object with 15 ranges and 31 metadata columns:
#> seqnames ranges strand | study context trait
#> <Rle> <IRanges> <Rle> | <character> <character> <character>
#> [1] chr22 32596246 * | study_1 context_1 gene_1
#> [2] chr22 32724254 * | study_1 context_1 gene_1
#> [3] chr22 32724508 * | study_1 context_1 gene_1
#> [4] chr22 32728910 * | study_1 context_1 gene_1
#> [5] chr22 32729588 * | study_1 context_1 gene_1
#> ... ... ... ... . ... ... ...
#> [11] chr22 32743285 * | study_1 context_1 gene_1
#> [12] chr22 32745710 * | study_1 context_1 gene_1
#> [13] chr22 32745749 * | study_1 context_1 gene_1
#> [14] chr22 32752021 * | study_1 context_1 gene_1
#> [15] chr22 32755495 * | study_1 context_1 gene_1
#> blockId method dataType dataSource standardized
#> <character> <character> <character> <character> <character>
#> [1] <NA> susie <NA> <NA> <NA>
#> [2] <NA> susie <NA> <NA> <NA>
#> [3] <NA> susie <NA> <NA> <NA>
#> [4] <NA> susie <NA> <NA> <NA>
#> [5] <NA> susie <NA> <NA> <NA>
#> ... ... ... ... ... ...
#> [11] <NA> susie <NA> <NA> <NA>
#> [12] <NA> susie <NA> <NA> <NA>
#> [13] <NA> susie <NA> <NA> <NA>
#> [14] <NA> susie <NA> <NA> <NA>
#> [15] <NA> susie <NA> <NA> <NA>
#> variant_id chrom pos A1 A2
#> <character> <character> <integer> <character> <character>
#> [1] chr22:32596246:T:C chr22 32596246 C T
#> [2] chr22:32724254:T:C chr22 32724254 C T
#> [3] chr22:32724508:C:A chr22 32724508 A C
#> [4] chr22:32728910:G:A chr22 32728910 A G
#> [5] chr22:32729588:T:C chr22 32729588 C T
#> ... ... ... ... ... ...
#> [11] chr22:32743285:A:C chr22 32743285 C A
#> [12] chr22:32745710:T:C chr22 32745710 C T
#> [13] chr22:32745749:T:C chr22 32745749 C T
#> [14] chr22:32752021:A:G chr22 32752021 G A
#> [15] chr22:32755495:C:T chr22 32755495 T C
#> N af posterior_effect posterior_se theta pip
#> <numeric> <numeric> <numeric> <numeric> <numeric> <numeric>
#> [1] 415 NA -0.01284643 0.0324407 0 0.1444970
#> [2] 415 NA 0.00601338 0.0283820 0 0.0442663
#> [3] 415 NA 0.00601338 0.0283820 0 0.0442663
#> [4] 415 NA 0.00534990 0.0268018 0 0.0394963
#> [5] 415 NA 0.00464131 0.0249437 0 0.0345102
#> ... ... ... ... ... ... ...
#> [11] 415 NA 0.00893074 0.0340197 0 0.0663491
#> [12] 415 NA 0.01059700 0.0372659 0 0.0769631
#> [13] 415 NA 0.00480686 0.0251396 0 0.0363655
#> [14] 415 NA 0.00480683 0.0251392 0 0.0363659
#> [15] 415 NA 0.00490735 0.0255981 0 0.0365497
#> logBF cs_95 cs_70 cs_50 cs_95_purity cs_70_purity
#> <numeric> <character> <character> <character> <numeric> <numeric>
#> [1] 6.53015 susie_0 susie_0 susie_0 0.000000 0.000000
#> [2] 15.67566 susie_1 susie_1 susie_1 0.625503 0.938229
#> [3] 15.67566 susie_1 susie_1 susie_1 0.625503 0.938229
#> [4] 15.56140 susie_1 susie_1 susie_0 0.625503 0.938229
#> [5] 15.42615 susie_1 susie_1 susie_0 0.625503 0.938229
#> ... ... ... ... ... ... ...
#> [11] 16.0811 susie_1 susie_1 susie_1 0.625503 0.938229
#> [12] 16.2296 susie_1 susie_1 susie_1 0.625503 0.938229
#> [13] 15.4787 susie_1 susie_1 susie_0 0.625503 0.938229
#> [14] 15.4787 susie_1 susie_1 susie_0 0.625503 0.938229
#> [15] 15.4837 susie_1 susie_1 susie_0 0.625503 0.938229
#> cs_50_purity within_cs_pip gene event grange_start
#> <numeric> <numeric> <character> <character> <integer>
#> [1] 0.000000 NA <NA> <NA> <NA>
#> [2] 0.940595 0.0441714 <NA> <NA> <NA>
#> [3] 0.940595 0.0441714 <NA> <NA> <NA>
#> [4] 0.000000 0.0394021 <NA> <NA> <NA>
#> [5] 0.000000 0.0344176 <NA> <NA> <NA>
#> ... ... ... ... ... ...
#> [11] 0.940595 0.0662558 <NA> <NA> <NA>
#> [12] 0.940595 0.0768644 <NA> <NA> <NA>
#> [13] 0.000000 0.0362743 <NA> <NA> <NA>
#> [14] 0.000000 0.0362754 <NA> <NA> <NA>
#> [15] 0.000000 0.0364562 <NA> <NA> <NA>
#> grange_end
#> <integer>
#> [1] <NA>
#> [2] <NA>
#> [3] <NA>
#> [4] <NA>
#> [5] <NA>
#> ... ...
#> [11] <NA>
#> [12] <NA>
#> [13] <NA>
#> [14] <NA>
#> [15] <NA>
#> -------
#> seqinfo: 1 sequence from an unspecified genome; no seqlengths