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 nullrangesData package.

library(nullrangesData)
dhs <- DHSA549Hg38()
library(nullranges)

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 807.0003 826.1563 844.4300 833.8830 857.4828  909.6544    10   b
##  b_within 711.1458 736.5462 774.7927 755.7430 804.9269  889.9765    10   b
##  p_across 183.4025 202.5134 248.0761 252.1929 264.0984  347.4833    10  a 
##  b_across 240.9222 241.0585 360.3647 262.7695 291.4427 1128.8665    10  a

Visualize 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)
    })
  }
}
plotGRanges(gr)

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

sessionInfo()
## R version 4.2.1 Patched (2022-07-09 r82577)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_GB/en_US.UTF-8
## 
## 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             
## [107] multcomp_1.4-20               GenomeInfoDbData_1.2.9       
## [109] parallel_4.2.1                hms_1.1.2                    
## [111] rmarkdown_2.17                shiny_1.7.3                  
## [113] restfulr_0.0.15