MOTIVATION: The assembly of contiguous sequence from metagenomic samples presents a particular challenge, due to the presence of multiple species, often closely related, at varying levels of abundance. Capturing diversity within species, for example, viral haplotypes, or bacterial strain-level diversity, is even more challenging. RESULTS: We present MetaCortex, a metagenome assembler that captures intra-species diversity by searching for signatures of local variation along assembled sequences in the underlying assembly graph and outputting these sequences in sequence graph format. We show that MetaCortex produces accurate assemblies with higher genome coverage and contiguity than other popular metagenomic assemblers on mock viral communities with high levels of strain-level diversity and on simulated communities containing simulated strains. AVAILABILITY AND IMPLEMENTATION: Source code is freely available to download from https://github.com/SR-Martin/metacortex, is implemented in C and supported on MacOS and Linux. The version used for the results presented in this article is available at doi.org/10.5281/zenodo.7273627. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

This special issue introduces current developments in bioinformatics, the use of computational techniques in the service of the life sciences, in the specific context of the analysis and interpretation of DNA molecules, where DNA is the primary informational molecule of all life. To fully appreciate the papers in this issue, some background knowledge in biology is required. The DNA in a cell is organized into a genome consisting of one or more chromosomes, each of which is a DNA molecule, which can be thought of as a long string over the alphabet of nucleotides, A, C, G, and T. Within a DNA string or sequence are substrings that are genes that normally encode the recipe for the functional proteins in the cell. The human genome is organized into 23 pairs of chromosomes, one maternal and one paternal chromosome set, containing a total of approximately six billion nucleotides. Amazingly, all ~1 trillion cells in one’s body, of diverse form and function, contain the same “molecular blueprint” with a near perfect copy of their genome.

MOTIVATION: For most research approaches, genome analyses are dependent on the existence of a high quality genome reference assembly. However, the local accuracy of an assembly remains difficult to assess and improve. The gEVAL browser allows the user to interrogate an assembly in any region of the genome by comparing it to different datasets and evaluating the concordance. These analyses include: a wide variety of sequence alignments, comparative analyses of multiple genome assemblies, and consistency with optical and other physical maps. gEVAL highlights allelic variations, regions of low complexity, abnormal coverage, and potential sequence and assembly errors, and offers strategies for improvement. Although gEVAL focuses primarily on sequence integrity, it can also display arbitrary annotation including from Ensembl or TrackHub sources. We provide gEVAL web sites for many human, mouse, zebrafish and chicken assemblies to support the Genome Reference Consortium, and gEVAL is also downloadable to enable its use for any organism and assembly. AVAILABILITY AND IMPLEMENTATION: Web Browser: http://geval.sanger.ac.uk, Plugin: http://wchow.github.io/wtsi-geval-plugin CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The Oxford Nanopore MinION sequencer, currently in pre-release testing through the MinION Access Programme (MAP), promises long reads in real-time from an inexpensive, compact, USB device. Tools have been released to extract FASTA/Q from the MinION base calling output and to provide basic yield statistics. However, no single tool yet exists to provide comprehensive alignment-based quality control and error profile analysis--something that is extremely important given the speed with which the platform is evolving. RESULTS: NanoOK generates detailed tabular and graphical output plus an in-depth multi-page PDF report including error profile, quality and yield data. NanoOK is multi-reference, enabling detailed analysis of metagenomic or multiplexed samples. Four popular Nanopore aligners are supported and it is easily extensible to include others. AVAILABILITY AND IMPLEMENTATION: NanoOK is an open-source software, implemented in Java with supporting R scripts. It has been tested on Linux and Mac OS X and can be downloaded from https://github.com/TGAC/NanoOK. A VirtualBox VM containing all dependencies and the DH10B read set used in this article is available from http://opendata.tgac.ac.uk/nanook/. A Docker image is also available from Docker Hub--see program documentation https://documentation.tgac.ac.uk/display/NANOOK. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: The increase in human populations around the world has put pressure on resources, and as a consequence food security has become an important challenge for the 21st century. Wheat (Triticum aestivum) is one of the most important crops in human and livestock diets, and the development of wheat varieties that produce higher yields, combined with increased resistance to pests and resilience to changes in climate, has meant that wheat breeding has become an important focus of scientific research. In an attempt to facilitate these improvements in wheat, plant breeders have employed molecular tools to help them identify genes for important agronomic traits that can be bred into new varieties. Modern molecular techniques have ensured that the rapid and inexpensive characterisation of SNP markers and their validation with modern genotyping methods has produced a valuable resource that can be used in marker assisted selection. CerealsDB was created as a means of quickly disseminating this information to breeders and researchers around the globe. DESCRIPTION: CerealsDB version 3.0 is an online resource that contains a wide range of genomic datasets for wheat that will assist plant breeders and scientists to select the most appropriate markers for use in marker assisted selection. CerealsDB includes a database which currently contains in excess of a million putative varietal SNPs, of which several hundreds of thousands have been experimentally validated. In addition, CerealsDB also contains new data on functional SNPs predicted to have a major effect on protein function and we have constructed a web service to encourage data integration and high-throughput programmatic access. CONCLUSION: CerealsDB is an open access website that hosts information on SNPs that are considered useful for both plant breeders and research scientists. The recent inclusion of web services designed to federate genomic data resources allows the information on CerealsDB to be more fully integrated with the WheatIS network and other biological databases.

UNLABELLED: The design of genetic markers is of particular relevance in crop breeding programs. Despite many economically important crops being polyploid organisms, the current primer design tools are tailored for diploid species. Bread wheat, for instance, is a hexaploid comprising of three related genomes and the performance of genetic markers is diminished if the primers are not genome specific. PolyMarker is a pipeline that generates SNP markers by selecting candidate primers for a specified genome using local alignments and standard primer design tools to test the viability of the primers. A command line tool and a web interface are available to the community. AVAILABILITY AND IMPLEMENTATION: PolyMarker is available as a ruby BioGem: bio-polyploid-tools. Web interface: http://polymarker.tgac.ac.uk.

SUMMARY: Illumina's recently released Nextera Long Mate Pair (LMP) kit enables production of jumping libraries of up to 12 kb. The LMP libraries are an invaluable resource for carrying out complex assemblies and other downstream bioinformatics analyses such as the characterization of structural variants. However, LMP libraries are intrinsically noisy and to maximize their value, post-sequencing data analysis is required. Standardizing laboratory protocols and the selection of sequenced reads for downstream analysis are non-trivial tasks. NextClip is a tool for analyzing reads from LMP libraries, generating a comprehensive quality report and extracting good quality trimmed and deduplicated reads. AVAILABILITY AND IMPLEMENTATION: Source code, user guide and example data are available from https://github.com/richardmleggett/nextclip/.

SUMMARY: Scientists now use high-throughput sequencing technologies and short-read assembly methods to create draft genome assemblies in just days. Tools and pipelines like the assembler, and the workflow management environments make it easy for a non-specialist to implement complicated pipelines to produce genome assemblies and annotations very quickly. Such accessibility results in a proliferation of assemblies and associated files, often for many organisms. These assemblies get used as a working reference by lots of different workers, from a bioinformatician doing gene prediction or a bench scientist designing primers for PCR. Here we describe Gee Fu, a database tool for genomic assembly and feature data, including next-generation sequence alignments. Gee Fu is an instance of a Ruby-On-Rails web application on a feature database that provides web and console interfaces for input, visualization of feature data via AnnoJ, access to data through a web-service interface, an API for direct data access by Ruby scripts and access to feature data stored in BAM files. Gee Fu provides a platform for storing and sharing different versions of an assembly and associated features that can be accessed and updated by bench biologists and bioinformaticians in ways that are easy and useful for each. AVAILABILITY: http://tinyurl.com/geefu CONTACT: [email protected].