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.

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).

## Unit: milliseconds
##      expr      min       lq      mean    median        uq       max neval cld
##  p_within 933.3921 960.8329 1360.1196 1167.8408 1935.4512 2163.3598    10   b
##  b_within 852.4478 942.3608 1340.6979  947.0155 1221.6593 3875.1583    10   b
##  p_across 214.8735 231.0009  280.1609  255.0290  296.8121  487.2238    10  a 
##  b_across 238.9146 247.7053  263.8726  259.3734  278.3249  313.9127    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.

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.

Across chromosome

Visualizing two permutations of blocks across chromosome. Here we use larger blocks than previously.

Visualizing two bootstraps across chromosome:

Session information

## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
## 
## Matrix products: default
## BLAS:   /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-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_1.4.9        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):
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##   [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               
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##  [35] DBI_1.1.3                     Rcpp_1.0.9                   
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##  [89] lifecycle_1.0.3               BiocManager_1.30.19          
##  [91] jquerylib_0.1.4               data.table_1.14.4            
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