James K. Bonfield

De novo genome assembly is challenging in highly repetitive regions; however, reference-guided assemblers often suffer from bias. We propose a framework for pangenome-guided sequence assembly, which can resolve short-read data in complex regions without bias towards a single reference genome. Our method frames assembly as a graph traversal optimisation problem, which can be implemented on quantum computers. The pipeline first annotates pangenome graphs with estimated copy numbers for each node, then finds a path on the graph that best explains those copy numbers. On simulated data, our approach significantly reduces the number of contigs compared to de novo assemblers. While it introduces a small increase in inaccuracies, such as false joins, our optimisation-based methods are competitive with current exhaustive search techniques. They are also designed to scale more efficiently as the problem size grows and will run effectively on future quantum computers.

CRAM has established itself as a high compression alternative to the BAM file format for DNA sequencing data. We describe updates to further improve this on modern sequencing instruments. With Illumina data CRAM 3.1 is 7–15% smaller than the equivalent CRAM 3.0 file, and 50–70% smaller than the corresponding BAM file. Long-read technology shows more modest compression due to the presence of high-entropy signals. The CRAM 3.0 specification is freely available from https://samtools.github.io/hts-specs/CRAMv3.pdf. The CRAM 3.1 improvements are available in a separate OpenSource HTScodecs library from https://github.com/samtools/htscodecs, and have been incorporated into HTSlib. Supplementary data are available at Bioinformatics online.

Motivation CRAM has established itself as a high compression alternative to the BAM file format for DNA sequencing data. We describe updates to further improve this on modern sequencing instruments. Results With Illumina data CRAM 3.1 is 7 to 15% smaller than the equivalent CRAM 3.0 file, and 50 to 70% smaller than the corresponding BAM file. Long-read technology shows more modest compression due to the presence of high-entropy signals. Availability The CRAM 3.0 specification is freely available from https://samtools.github.io/hts-specs/CRAMv3.pdf. The CRAM 3.1 improvements are available from https://github.com/samtools/hts-specs/pull/433, with OpenSource implementations in HTSlib and HTScodecs. Contact jkb{at}sanger.ac.uk Supplementary information Supplementary data are available online

Background: Since the original publication of the VCF and SAM formats, an explosion of software tools have been created to process these data files. To facilitate this a library was produced out of the original SAMtools implementation, with a focus on performance and robustness. The file formats themselves have become international standards under the jurisdiction of the Global Alliance for Genomics and Health. Findings: We present a software library for providing programmatic access to sequencing alignment and variant formats. It was born out of the widely used SAMtools and BCFtools applications. Considerable improvements have been made to the original code plus many new features including newer access protocols, the addition of the CRAM file format, better indexing and iterators, and better use of threading. Conclusion: Since the original Samtools release, performance has been considerably improved, with a BAM read-write loop running 5 times faster and BAM to SAM conversion 13 times faster (both using 16 threads, compared to Samtools 0.1.19). Widespread adoption has seen HTSlib downloaded >1 million times from GitHub and conda. The C library has been used directly by an estimated 900 GitHub projects and has been incorporated into Perl, Python, Rust, and R, significantly expanding the number of uses via other languages. HTSlib is open source and is freely available from htslib.org under MIT/BSD license.

Background: SAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling, and effect analysis amongst other methods. Findings: The first version appeared online 12 years ago and has been maintained and further developed ever since, with many new features and improvements added over the years. The SAMtools and BCFtools packages represent a unique collection of tools that have been used in numerous other software projects and countless genomic pipelines. Conclusion: Both SAMtools and BCFtools are freely available on GitHub under the permissive MIT licence, free for both non-commercial and commercial use. Both packages have been installed >1 million times via Bioconda. The source code and documentation are available from https://www.htslib.org.

Background Since the original publication of the VCF and SAM formats, an explosion of software tools have been created to process these data files. To facilitate this a library was produced out of the original SAMtools implementation, with a focus on performance and robustness. The file formats themselves have become international standards under the jurisdiction of the Global Alliance for Genomics and Health. Findings We present a software library for providing programmatic access to sequencing alignment and variant formats. It was born out of the widely used SAMtools and BCFtools applications. Considerable improvements have been made to the original code plus many new features including newer access protocols, the addition of the CRAM file format, better indexing and iterators, and better use of threading. Conclusion Since the original Samtools release, performance has been considerably improved, with a BAM read-write loop running 5 times faster and BAM to SAM conversion 13 times faster (both using 16 threads, compared to Samtools 0.1.19). Widespread adoption has seen HTSlib downloaded over a million times from GitHub and conda. The C library has been used directly by an estimated 900 GitHub projects and has been incorporated into Perl, Python, Rust and R, significantly expanding the number of uses via other languages. HTSlib is open source and is freely available from htslib.org under MIT / BSD license. Contact samtools{at}sanger.ac.uk

The bulk of space taken up by NGS sequencing CRAM files consists of per-base quality values. Most of these are unnecessary for variant calling, offering an opportunity for space saving. On the Syndip test set, a 17 fold reduction in the quality storage portion of a CRAM file can be achieved while maintaining variant calling accuracy. The size reduction of an entire CRAM file varied from 2.2 to 7.4 fold, depending on the non-quality content of the original file (see Supplementary Material S6 for details). Crumble is OpenSource and can be obtained from https://github.com/jkbonfield/crumble. Supplementary data are available at Bioinformatics online.

Motivation: The bulk of space taken up by NGS sequencing CRAM files consists of per-base quality values. Most of these are unnecessary for variant calling, offering an opportunity for space saving. Results: On the CHM1+CHM13 test set, a 17 fold reduction in quality storage can be achieved while maintaining variant calling accuracy. Availability: Crumble is OpenSource and can be obtained from https://github.com/jkbonfield/crumble . Contact: jkb@sanger.ac.uk Supplementary information: Supplementary data are available.

Long-read sequencing technologies such as Pacific Biosciences and Oxford Nanopore MinION are capable of producing long sequencing reads with average fragment lengths of over 10,000 base-pairs and maximum lengths reaching 100,000 base- pairs. Compared with short reads, the assemblies obtained from long-read sequencing platforms have much higher contig continuity and genome completeness as long fragments are able to extend paths into problematic or repetitive regions. Many successful assembly applications of the Pacific Biosciences technology have been reported ranging from small bacterial genomes to large plant and animal genomes. Recently, genome assemblies using Oxford Nanopore MinION data have attracted much attention due to the portability and low cost of this novel sequencing instrument. In this paper, we re-sequenced a well characterized genome, the Saccharomyces cerevisiae S288C strain using three different platforms: MinION, PacBio and MiSeq. We present a comprehensive metric comparison of assemblies generated by various pipelines and discuss how the platform associated data characteristics affect the assembly quality. With a given read depth of 31X, the assemblies from both Pacific Biosciences and Oxford Nanopore MinION show excellent continuity and completeness for the 16 nuclear chromosomes, but not for the mitochondrial genome, whose reconstruction still represents a significant challenge.