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 1581.3474 1716.7768 2504.3833 2047.7247 3861.4811 4129.0194    10   b
##  b_within 1427.5562 1505.6876 2051.7905 1858.5992 2077.9267 3420.9211    10   b
##  p_across  344.8032  373.0014  475.0357  413.3415  483.6439  757.1998    10  a 
##  b_across  348.5468  378.2331  485.4575  395.4837  502.5817  853.2259    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 Patched (2021-08-22 r80813)
## 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_1.4-7        excluderanges_0.99.6       
##  [3] EnsDb.Hsapiens.v86_2.99.0   ensembldb_2.17.4           
##  [5] AnnotationFilter_1.17.1     GenomicFeatures_1.45.2     
##  [7] AnnotationDbi_1.55.2        patchwork_1.1.1            
##  [9] plyranges_1.13.1            nullrangesData_0.99.2      
## [11] ExperimentHub_2.1.4         AnnotationHub_3.1.7        
## [13] BiocFileCache_2.1.1         dbplyr_2.1.1               
## [15] ggplot2_3.3.5               plotgardener_0.99.16       
## [17] nullranges_0.99.19          InteractionSet_1.21.1      
## [19] SummarizedExperiment_1.23.5 Biobase_2.53.0             
## [21] MatrixGenerics_1.5.4        matrixStats_0.61.0         
## [23] GenomicRanges_1.45.0        GenomeInfoDb_1.29.10       
## [25] IRanges_2.27.2              S4Vectors_0.31.5           
## [27] BiocGenerics_0.39.2        
## 
## 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_1.27.17          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_2.61.2            
##  [15] sandwich_3.0-1                prettyunits_1.1.1            
##  [17] colorspace_2.0-2              blob_1.2.2                   
##  [19] rappdirs_0.3.3                xfun_0.27                    
##  [21] dplyr_1.0.7                   crayon_1.4.1                 
##  [23] RCurl_1.98-1.5                jsonlite_1.7.2               
##  [25] survival_3.2-13               zoo_1.8-9                    
##  [27] glue_1.4.2                    gtable_0.3.0                 
##  [29] zlibbioc_1.39.0               XVector_0.33.0               
##  [31] strawr_0.0.9                  DelayedArray_0.19.4          
##  [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_5.4.7                  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_1.67.0                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_0.1.0                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_1.33.0               mime_0.12                    
##  [73] pracma_2.3.3                  xml2_1.3.2                   
##  [75] biomaRt_2.49.7                compiler_4.1.1               
##  [77] filelock_1.0.2                curl_4.3.2                   
##  [79] png_0.1-7                     interactiveDisplayBase_1.31.2
##  [81] tibble_3.1.5                  bslib_0.3.1                  
##  [83] stringi_1.7.5                 highr_0.9                    
##  [85] lattice_0.20-45               ProtGenerics_1.25.1          
##  [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_1.53.1           
##  [97] R6_2.5.1                      BiocIO_1.3.0                 
##  [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_1.29.0     
## [107] Rsamtools_2.9.1               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