Hi, not sure if this is the place to post suspected bugs, but I've found that readGAlignmentPairs() gets stuck when reading a bam file with the intervals specified. I'm running this on a bam that is the direct output of samtools, produced by downsampling a larger bam file to 10% of reads.

Script:

library(GenomicAlignments)

sessionInfo()

bamfile = "reads.bam"

df = readr::read_tsv("peaks.bed", col_names = c("chr", "start", "end", paste0("X", 4:10)))
intervals = makeGRangesFromDataFrame(df)

ps = Rsamtools::ScanBamParam(which=intervals)

readGAlignments(bamfile)
message("Single-end entire file read OK") # runs fine in ~60s

readGAlignmentPairs(bamfile)
message("Paired-end entire file read OK") # runs with a warning about unpaired alignments in ~60s

readGAlignments(bamfile, param=ps)
message("Single-end intervals read OK") # runs fine almost instantly

readGAlignmentPairs(bamfile, param=ps)
message("Paired-end intervals read OK") # never completes

sessionInfo():

R version 4.0.5 (2021-03-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.2 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
 [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets 
[8] methods   base     

other attached packages:
 [1] GenomicAlignments_1.26.0    Rsamtools_2.6.0            
 [3] Biostrings_2.58.0           XVector_0.30.0             
 [5] SummarizedExperiment_1.20.0 Biobase_2.50.0             
 [7] MatrixGenerics_1.2.1        matrixStats_0.58.0         
 [9] GenomicRanges_1.42.0        GenomeInfoDb_1.26.7        
[11] IRanges_2.24.1              S4Vectors_0.28.1           
[13] BiocGenerics_0.36.1        

loaded via a namespace (and not attached):
 [1] rstudioapi_0.13        zlibbioc_1.36.0        BiocParallel_1.24.1   
 [4] lattice_0.20-41        tools_4.0.5            grid_4.0.5            
 [7] crayon_1.4.1           Matrix_1.3-2           GenomeInfoDbData_1.2.4
[10] bitops_1.0-7           RCurl_1.98-1.3         DelayedArray_0.16.3   
[13] compiler_4.0.5

NB This was an entirely fresh install of both R and Bioconductor around 2 weeks ago

PS Both files are public data but the bam is still quite large (~300MB), I can provide these or test with a different example file if that would help.