Unsegmented block bootstrap
Michael Love
11/07/2021
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.
Timing on DHS peaks
First we use the DNase hypersensitivity peaks in A549 downloaded from AnnotationHub, and pre-processed as described in the nullrangesOldData package.
## see ?nullrangesData and browseVignettes('nullrangesData') for documentation## loading from cacheThe 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 1242.2211 1321.2643 1862.3647 1556.3895 2277.2006 3831.8649 10 b
## b_within 1072.7897 1126.3715 1535.6990 1158.8333 1764.1768 3238.7512 10 b
## p_across 234.5497 256.9680 270.4702 271.2444 283.5763 294.6041 10 a
## b_across 266.9635 286.2112 401.9607 304.1759 335.6808 1212.1928 10 aVisualize on synthetic data
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)
})
}
}
Within chromosome
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)
}
Across chromosome
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)
}
Session information
## R version 4.1.1 (2021-08-10)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.3 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.14-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.14-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] grid stats4 stats graphics grDevices utils datasets
## [8] methods base
##
## other attached packages:
## [1] microbenchmark_1.4.8 excluderanges_0.99.6
## [3] EnsDb.Hsapiens.v86_2.99.0 ensembldb_2.18.1
## [5] AnnotationFilter_1.18.0 GenomicFeatures_1.46.1
## [7] AnnotationDbi_1.56.1 patchwork_1.1.1
## [9] plyranges_1.14.0 nullrangesData_1.0.0
## [11] ExperimentHub_2.2.0 AnnotationHub_3.2.0
## [13] BiocFileCache_2.2.0 dbplyr_2.1.1
## [15] ggplot2_3.3.5 plotgardener_1.0.1
## [17] nullranges_1.0.1 InteractionSet_1.22.0
## [19] SummarizedExperiment_1.24.0 Biobase_2.54.0
## [21] MatrixGenerics_1.6.0 matrixStats_0.61.0
## [23] GenomicRanges_1.46.0 GenomeInfoDb_1.30.0
## [25] IRanges_2.28.0 S4Vectors_0.32.2
## [27] BiocGenerics_0.40.0
##
## loaded via a namespace (and not attached):
## [1] plyr_1.8.6 RcppHMM_1.2.2
## [3] lazyeval_0.2.2 splines_4.1.1
## [5] BiocParallel_1.28.0 TH.data_1.1-0
## [7] digest_0.6.28 yulab.utils_0.0.4
## [9] htmltools_0.5.2 fansi_0.5.0
## [11] magrittr_2.0.1 memoise_2.0.0
## [13] ks_1.13.2 Biostrings_2.62.0
## [15] sandwich_3.0-1 prettyunits_1.1.1
## [17] colorspace_2.0-2 blob_1.2.2
## [19] rappdirs_0.3.3 xfun_0.28
## [21] dplyr_1.0.7 crayon_1.4.2
## [23] RCurl_1.98-1.5 jsonlite_1.7.2
## [25] survival_3.2-13 zoo_1.8-9
## [27] glue_1.5.0 gtable_0.3.0
## [29] zlibbioc_1.40.0 XVector_0.34.0
## [31] strawr_0.0.9 DelayedArray_0.20.0
## [33] scales_1.1.1 mvtnorm_1.1-3
## [35] DBI_1.1.1 Rcpp_1.0.7
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## [39] gridGraphics_0.5-1 bit_4.0.4
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## [43] RColorBrewer_1.1-2 speedglm_0.3-3
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## [47] XML_3.99-0.8 farver_2.1.0
## [49] sass_0.4.0 utf8_1.2.2
## [51] DNAcopy_1.68.0 ggplotify_0.1.0
## [53] tidyselect_1.1.1 labeling_0.4.2
## [55] rlang_0.4.12 later_1.3.0
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## [59] tools_4.1.1 cachem_1.0.6
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## [75] biomaRt_2.50.0 compiler_4.1.1
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## [81] tibble_3.1.6 bslib_0.3.1
## [83] stringi_1.7.5 highr_0.9
## [85] lattice_0.20-45 ProtGenerics_1.26.0
## [87] Matrix_1.3-4 vctrs_0.3.8
## [89] pillar_1.6.4 lifecycle_1.0.1
## [91] BiocManager_1.30.16 jquerylib_0.1.4
## [93] data.table_1.14.2 bitops_1.0-7
## [95] httpuv_1.6.3 rtracklayer_1.54.0
## [97] R6_2.5.1 BiocIO_1.4.0
## [99] promises_1.2.0.1 KernSmooth_2.23-20
## [101] codetools_0.2-18 MASS_7.3-54
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## [105] withr_2.4.2 GenomicAlignments_1.30.0
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