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.

library(nullrangesData)
dhs <- DHSA549Hg38()
## see ?nullrangesData and browseVignettes('nullrangesData') for documentation
## loading from cache
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 1820.2076 2113.9483 2743.9982 2166.5210 4005.6536 4351.6155    10   b
##  b_within 1530.0095 1814.9135 2017.7530 1956.0643 2029.4123 3255.2062    10   b
##  p_across  391.5507  424.5649  537.8631  475.8006  551.6568  841.8597    10  a 
##  b_across  407.7798  435.0697  687.8482  467.5030  502.6434 2401.8366    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 4.1.1 (2021-08-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Mojave 10.14.6
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] C/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] grid      stats4    stats     graphics  grDevices utils     datasets 
## [8] methods   base     
## 
## other attached packages:
##  [1] microbenchmark_1.4.8        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                   
##  [37] xtable_1.8-4                  progress_1.2.2               
##  [39] gridGraphics_0.5-1            bit_4.0.4                    
##  [41] mclust_5.4.8                  httr_1.4.2                   
##  [43] RColorBrewer_1.1-2            speedglm_0.3-3               
##  [45] ellipsis_0.3.2                pkgconfig_2.0.3              
##  [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                  
##  [57] munsell_0.5.0                 BiocVersion_3.14.0           
##  [59] tools_4.1.1                   cachem_1.0.6                 
##  [61] generics_0.1.1                RSQLite_2.2.8                
##  [63] ggridges_0.5.3                evaluate_0.14                
##  [65] stringr_1.4.0                 fastmap_1.1.0                
##  [67] yaml_2.2.1                    knitr_1.36                   
##  [69] bit64_4.0.5                   purrr_0.3.4                  
##  [71] KEGGREST_1.34.0               mime_0.12                    
##  [73] pracma_2.3.3                  xml2_1.3.2                   
##  [75] biomaRt_2.50.0                compiler_4.1.1               
##  [77] filelock_1.0.2                curl_4.3.2                   
##  [79] png_0.1-7                     interactiveDisplayBase_1.32.0
##  [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                  
## [103] assertthat_0.2.1              rjson_0.2.20                 
## [105] withr_2.4.2                   GenomicAlignments_1.30.0     
## [107] Rsamtools_2.10.0              multcomp_1.4-17              
## [109] GenomeInfoDbData_1.2.7        parallel_4.1.1               
## [111] hms_1.1.1                     rmarkdown_2.11               
## [113] shiny_1.7.1                   restfulr_0.0.13