If the BAM files are each processed independently, and each processing task takes a while, then it is probably 'good enough' to use R-level parallel evaluation using BiocParallel (currently the recommendation for Bioconductor packages) or other evaluation framework. Also, presumably you will use Rhtslib, which provides C-level access to the hts library. This will requiring writing C / C++ code to interface between R and the hts library, and will of course be a significant underataking.
It might be worth outlining in a bit more detail what your task is and how (not too much detail!) you've tried to implement this in Rsamtools. Martin Morgan On 5/24/21, 10:01 AM, "Bioc-devel on behalf of Oleksii Nikolaienko" <bioc-devel-boun...@r-project.org on behalf of oleksii.nikolaie...@gmail.com> wrote: Dear Bioc team, I'd like to ask for your advice on the parallelization within a Bioc package. Please point me to a better place if this mailing list is not appropriate. After a bit of thinking I decided that I'd like to parallelize processing at the level of C++ code. Would you strongly recommend not to and use an R approach instead (e.g. "future")? If parallel C++ is ok, what would be the best solution for all major OSs? My initial choice was OpenMP, but then it seems that Apple has something against it (https://mac.r-project.org/openmp/). My own dev environment is mostly Big Sur/ARM64, but I wouldn't want to drop its support anyway. (On the actual task: loading and specific processing of very large BAM files, ideally significantly faster than by means of Rsamtools as a backend) Best, Oleksii Nikolaienko [[alternative HTML version deleted]] _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel _______________________________________________ Bioc-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/bioc-devel