In this vignette, we demonstrate the unsegmented block bootstrap functionality implemented in nullranges. “Unsegmented” refers to the fact that this implementation does not consider segmentation of the genome for sampling of blocks, see the segmented block bootstrap vignette for the alternative implementation.
First we use the DNase hypersensitivity peaks in A549 downloaded from AnnotationHub, and pre-processed as described in the nullrangesData package.
The following chunk of code evaluates various types of bootstrap/permutation schemes, first within chromosome, and then across chromosome (the default). The default type
is bootstrap, and the default for withinChrom
is FALSE
(bootstrapping with blocks moving across chromosomes).
set.seed(5) # reproducibility
library(microbenchmark)
blockLength <- 5e5
microbenchmark(
list=alist(
p_within=bootRanges(dhs, blockLength=blockLength,
type="permute", withinChrom=TRUE),
b_within=bootRanges(dhs, blockLength=blockLength,
type="bootstrap", withinChrom=TRUE),
p_across=bootRanges(dhs, blockLength=blockLength,
type="permute", withinChrom=FALSE),
b_across=bootRanges(dhs, blockLength=blockLength,
type="bootstrap", withinChrom=FALSE)
), times=10)
## Unit: milliseconds
## expr min lq mean median uq max neval cld
## p_within 980.5564 1023.8027 1076.8785 1068.1294 1140.0632 1172.357 10 b
## b_within 905.4653 928.8574 1066.3188 944.3148 958.8301 2081.844 10 b
## p_across 230.3390 252.2741 273.5545 268.1419 306.2476 313.606 10 a
## b_across 282.5991 301.1342 438.2609 337.2092 342.1123 1445.015 10 a
We create some synthetic ranges in order to visualize the different options of the unsegmented bootstrap implemented in nullranges.
library(GenomicRanges)
seq_nms <- rep(c("chr1","chr2","chr3"),c(4,5,2))
gr <- GRanges(seqnames=seq_nms,
IRanges(start=c(1,101,121,201,
101,201,216,231,401,
1,101),
width=c(20, 5, 5, 30,
20, 5, 5, 5, 30,
80, 40)),
seqlengths=c(chr1=300,chr2=450,chr3=200),
chr=factor(seq_nms))
The following function uses functionality from plotgardener to plot the ranges. Note in the plotting helper function that chr
will be used to color ranges by chromosome of origin.
suppressPackageStartupMessages(library(plotgardener))
plotGRanges <- function(gr) {
pageCreate(width = 5, height = 2, xgrid = 0,
ygrid = 0, showGuides = FALSE)
for (i in seq_along(seqlevels(gr))) {
chrom <- seqlevels(gr)[i]
chromend <- seqlengths(gr)[[chrom]]
suppressMessages({
p <- pgParams(chromstart = 0, chromend = chromend,
x = 0.5, width = 4*chromend/500, height = 0.5,
at = seq(0, chromend, 50),
fill = colorby("chr", palette=palette.colors))
prngs <- plotRanges(data = gr, params = p,
chrom = chrom,
y = 0.25 + (i-1)*.7,
just = c("left", "bottom"))
annoGenomeLabel(plot = prngs, params = p, y = 0.30 + (i-1)*.7)
})
}
}
Visualizing two permutations of blocks within chromosome:
for (i in 1:2) {
gr_prime <- bootRanges(gr, blockLength=100, type="permute", withinChrom=TRUE)
plotGRanges(gr_prime)
}
Visualizing two bootstraps within chromosome:
for (i in 1:2) {
gr_prime <- bootRanges(gr, blockLength=100, withinChrom=TRUE)
plotGRanges(gr_prime)
}
Visualizing two permutations of blocks across chromosome. Here we use larger blocks than previously.
for (i in 1:2) {
gr_prime <- bootRanges(gr, blockLength=200, type="permute", withinChrom=FALSE)
plotGRanges(gr_prime)
}
Visualizing two bootstraps across chromosome:
for (i in 1:2) {
gr_prime <- bootRanges(gr, blockLength=200, withinChrom=FALSE)
plotGRanges(gr_prime)
}
## R version 4.2.1 (2022-06-23 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows Server x64 (build 20348)
##
## Matrix products: default
##
## locale:
## [1] LC_COLLATE=C
## [2] LC_CTYPE=English_United States.utf8
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C
## [5] LC_TIME=English_United States.utf8
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] microbenchmark_1.4.9 purrr_0.3.5
## [3] ggridges_0.5.4 tidyr_1.2.1
## [5] EnsDb.Hsapiens.v86_2.99.0 ensembldb_2.22.0
## [7] AnnotationFilter_1.22.0 GenomicFeatures_1.50.0
## [9] AnnotationDbi_1.60.0 patchwork_1.1.2
## [11] plyranges_1.18.0 nullrangesData_1.3.0
## [13] ExperimentHub_2.6.0 AnnotationHub_3.6.0
## [15] BiocFileCache_2.6.0 dbplyr_2.2.1
## [17] ggplot2_3.3.6 plotgardener_1.4.0
## [19] nullranges_1.4.0 InteractionSet_1.26.0
## [21] SummarizedExperiment_1.28.0 Biobase_2.58.0
## [23] MatrixGenerics_1.10.0 matrixStats_0.62.0
## [25] GenomicRanges_1.50.0 GenomeInfoDb_1.34.0
## [27] IRanges_2.32.0 S4Vectors_0.36.0
## [29] BiocGenerics_0.44.0
##
## loaded via a namespace (and not attached):
## [1] RcppHMM_1.2.2 lazyeval_0.2.2
## [3] splines_4.2.1 BiocParallel_1.32.0
## [5] TH.data_1.1-1 digest_0.6.30
## [7] yulab.utils_0.0.5 htmltools_0.5.3
## [9] fansi_1.0.3 magrittr_2.0.3
## [11] memoise_2.0.1 ks_1.13.5
## [13] Biostrings_2.66.0 sandwich_3.0-2
## [15] prettyunits_1.1.1 jpeg_0.1-9
## [17] colorspace_2.0-3 blob_1.2.3
## [19] rappdirs_0.3.3 xfun_0.34
## [21] dplyr_1.0.10 crayon_1.5.2
## [23] RCurl_1.98-1.9 jsonlite_1.8.3
## [25] survival_3.4-0 zoo_1.8-11
## [27] glue_1.6.2 gtable_0.3.1
## [29] zlibbioc_1.44.0 XVector_0.38.0
## [31] strawr_0.0.9 DelayedArray_0.24.0
## [33] scales_1.2.1 mvtnorm_1.1-3
## [35] DBI_1.1.3 Rcpp_1.0.9
## [37] xtable_1.8-4 progress_1.2.2
## [39] gridGraphics_0.5-1 bit_4.0.4
## [41] mclust_6.0.0 httr_1.4.4
## [43] RColorBrewer_1.1-3 speedglm_0.3-4
## [45] ellipsis_0.3.2 pkgconfig_2.0.3
## [47] XML_3.99-0.12 farver_2.1.1
## [49] sass_0.4.2 utf8_1.2.2
## [51] DNAcopy_1.72.0 ggplotify_0.1.0
## [53] tidyselect_1.2.0 labeling_0.4.2
## [55] rlang_1.0.6 later_1.3.0
## [57] munsell_0.5.0 BiocVersion_3.16.0
## [59] tools_4.2.1 cachem_1.0.6
## [61] cli_3.4.1 generics_0.1.3
## [63] RSQLite_2.2.18 evaluate_0.17
## [65] stringr_1.4.1 fastmap_1.1.0
## [67] yaml_2.3.6 knitr_1.40
## [69] bit64_4.0.5 KEGGREST_1.38.0
## [71] mime_0.12 pracma_2.4.2
## [73] xml2_1.3.3 biomaRt_2.54.0
## [75] compiler_4.2.1 filelock_1.0.2
## [77] curl_4.3.3 png_0.1-7
## [79] interactiveDisplayBase_1.36.0 tibble_3.1.8
## [81] bslib_0.4.0 stringi_1.7.8
## [83] highr_0.9 lattice_0.20-45
## [85] ProtGenerics_1.30.0 Matrix_1.5-1
## [87] vctrs_0.5.0 pillar_1.8.1
## [89] lifecycle_1.0.3 BiocManager_1.30.19
## [91] jquerylib_0.1.4 data.table_1.14.4
## [93] bitops_1.0-7 httpuv_1.6.6
## [95] rtracklayer_1.58.0 R6_2.5.1
## [97] BiocIO_1.8.0 promises_1.2.0.1
## [99] KernSmooth_2.23-20 codetools_0.2-18
## [101] MASS_7.3-58.1 assertthat_0.2.1
## [103] rjson_0.2.21 withr_2.5.0
## [105] GenomicAlignments_1.34.0 Rsamtools_2.14.0
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