that describes the new created software tool.The changes have been highlighted

BACKGROUND: In the ten years since the initial publication of the RenSeq protocol, the method has proved to be a powerful tool for studying disease resistance in plants and providing target genes for breeding programmes. Since the initial publication of the methodology, it has continued to be developed as new technologies have become available and the increased availability of computing power has made new bioinformatic approaches possible. Most recently, this has included the development of a k-mer based association genetics approach, the use of PacBio HiFi data, and graphical genotyping with diagnostic RenSeq. However, there is not yet a unified workflow available and researchers must instead configure approaches from various sources themselves. This makes reproducibility and version control a challenge and limits the ability to perform these analyses to those with bioinformatics expertise. RESULTS: Here we present HISS, consisting of three workflows which take a user from raw RenSeq reads to the identification of candidates for disease resistance genes. These workflows conduct the assembly of enriched HiFi reads from an accession with the resistance phenotype of interest. A panel of accessions both possessing and lacking the resistance are then used in an association genetics approach (AgRenSeq) to identify contigs positively associated with the resistance phenotype. Candidate genes are then identified on these contigs and assessed for their presence or absence in the panel with a graphical genotyping approach that uses dRenSeq. These workflows are implemented via Snakemake, a python-based workflow manager. Software dependencies are either shipped with the release or handled with conda. All code is freely available and is distributed under the GNU GPL-3.0 license. CONCLUSIONS: HISS provides a user-friendly, portable, and easily customised approach for identifying novel disease resistance genes in plants. It is easily installed with all dependencies handled internally or shipped with the release and represents a significant improvement in the ease of use of these bioinformatics analyses.

BACKGROUND: Single Nucleotide Polymorphisms (SNPs) are widely used molecular markers, and their use has increased massively since the inception of Next Generation Sequencing (NGS) technologies, which allow detection of large numbers of SNPs at low cost. However, both NGS data and their analysis are error-prone, which can lead to the generation of false positive (FP) SNPs. We explored the relationship between FP SNPs and seven factors involved in mapping-based variant calling - quality of the reference sequence, read length, choice of mapper and variant caller, mapping stringency and filtering of SNPs by read mapping quality and read depth. This resulted in 576 possible factor level combinations. We used error- and variant-free simulated reads to ensure that every SNP found was indeed a false positive. RESULTS: The variation in the number of FP SNPs generated ranged from 0 to 36,621 for the 120 million base pairs (Mbp) genome. All of the experimental factors tested had statistically significant effects on the number of FP SNPs generated and there was a considerable amount of interaction between the different factors. Using a fragmented reference sequence led to a dramatic increase in the number of FP SNPs generated, as did relaxed read mapping and a lack of SNP filtering. The choice of reference assembler, mapper and variant caller also significantly affected the outcome. The effect of read length was more complex and suggests a possible interaction between mapping specificity and the potential for contributing more false positives as read length increases. CONCLUSIONS: The choice of tools and parameters involved in variant calling can have a dramatic effect on the number of FP SNPs produced, with particularly poor combinations of software and/or parameter settings yielding tens of thousands in this experiment. Between-factor interactions make simple recommendations difficult for a SNP discovery pipeline but the quality of the reference sequence is clearly of paramount importance. Our findings are also a stark reminder that it can be unwise to use the relaxed mismatch settings provided as defaults by some read mappers when reads are being mapped to a relatively unfinished reference sequence from e.g. a non-model organism in its early stages of genomic exploration.

The advent of second-generation sequencing (2GS) has provided a range of significant new challenges for the visualization of sequence assemblies. These include the large volume of data being generated, short-read lengths and different data types and data formats associated with the diversity of new sequencing technologies. This article illustrates how Tablet-a high-performance graphical viewer for visualization of 2GS assemblies and read mappings-plays an important role in the analysis of these data. We present Tablet, and through a selection of use cases, demonstrate its value in quality assurance and scientific discovery, through features such as whole-reference coverage overviews, variant highlighting, paired-end read mark-up, GFF3-based feature tracks and protein translations. We discuss the computing and visualization techniques utilized to provide a rich and responsive graphical environment that enables users to view a range of file formats with ease. Tablet installers can be freely downloaded from http://bioinf.hutton.ac.uk/tablet in 32 or 64-bit versions for Windows, OS X, Linux or Solaris. For further details on the Tablet, contact [email protected].

UNLABELLED: Data visualization can play a key role in comparative genomics, for example, underpinning the investigation of conserved synteny patterns. Strudel is a desktop application that allows users to easily compare both genetic and physical maps interactively and efficiently. It can handle large datasets from several genomes simultaneously, and allows all-by-all comparisons between these. AVAILABILITY AND IMPLEMENTATION: Installers for Strudel are available for Windows, Linux, Solaris and Mac OS X at http://bioinf.scri.ac.uk/strudel/.

SUMMARY: Tablet is a lightweight, high-performance graphical viewer for next-generation sequence assemblies and alignments. Supporting a range of input assembly formats, Tablet provides high-quality visualizations showing data in packed or stacked views, allowing instant access and navigation to any region of interest, and whole contig overviews and data summaries. Tablet is both multi-core aware and memory efficient, allowing it to handle assemblies containing millions of reads, even on a 32-bit desktop machine. AVAILABILITY: Tablet is freely available for Microsoft Windows, Apple Mac OS X, Linux and Solaris. Fully bundled installers can be downloaded from http://bioinf.scri.ac.uk/tablet in 32- and 64-bit versions.

SUMMARY: New software tools for graphical genotyping are required that can routinely handle the large data volumes generated by the high-throughput single-nucleotide polymorphism (SNP) platforms, genotyping-by-sequencing and other comparable genotyping technologies. Flapjack has been developed to facilitate analysis of these data, providing real time rendering with rapid navigation and comparisons between lines, markers and chromosomes, with visualization, sorting and querying based on associated data, such as phenotypes, quantitative trait loci or other mappable features. AVAILABILITY: Flapjack is freely available for Microsoft Windows, Mac OS X, Linux and Solaris, and can be downloaded from http://bioinf.scri.ac.uk/flapjack .

UNLABELLED: TOPALi v2 simplifies and automates the use of several methods for the evolutionary analysis of multiple sequence alignments. Jobs are submitted from a Java graphical user interface as TOPALi web services to either run remotely on high-performance computing clusters or locally (with multiple cores supported). Methods available include model selection and phylogenetic tree estimation using the Bayesian inference and maximum likelihood (ML) approaches, in addition to recombination detection methods. The optimal substitution model can be selected for protein or nucleic acid (standard, or protein-coding using a codon position model) data using accurate statistical criteria derived from ML co-estimation of the tree and the substitution model. Phylogenetic software available includes PhyML, RAxML and MrBayes. AVAILABILITY: Freely downloadable from http://www.topali.org for Windows, Mac OS X, Linux and Solaris.

The BRIDGES project was funded by the UK Department of Trade and Industry (DTI) to address the needs of cardiovascular research scientists investigating the genetic causes of hypertension as part of the Wellcome Trust funded (#4.34M) cardiovascular functional genomics (CFG) project. Security was at the heart of the BRIDGES project and an advanced data and compute grid infrastructure incorporating latest grid authorisation technologies was developed and delivered to the scientists. We outline these grid infrastructures and describe the perceived security requirements at the project start including data classifications and how these evolved throughout the lifetime of the project. The uptake and adoption of the project results are also presented along with the challenges that must be overcome to support the secure exchange of life science data sets. We also present how we will use the BRIDGES experiences in future projects at the National e-Science Centre.

The main purpose of this research is to develop methods for automatic identification of biological specimens in digital photographs and drawings held in a database. Incorporation of taxonomic drawings into a visual indexing system has not been attempted to date. Diatoms are a single cell microscopic algae that provide a particularly suitable case study. Identification of diatoms is a challenging task due to the huge number of the species, blurred boundaries between species, and life cycle related shape changes. A novel model based on principal curves representing the life cycle related shape variation of a number of diatom species has been developed. Our model is suitable for reconstruction purposes, allowing us to produce drawings of a variety of diatom shapes, thus providing a link between the photographs and drawings. We present the classification results of photographed and drawn specimens based on the model and compare our results to another recent system for diatom identification. Finally, given a diatom specimen, we are able not only to identify the species it belongs to but also to pinpoint the stage in the life cycle it represents.

We present a new method for automatic landmark extraction from the contours of biological specimens. Our ultimate goal is to enable automatic identification of biological specimens in photographs and drawings held in a database. We propose to use active appearance models for visual indexing of both photographs and drawings. Automatic landmark extraction will assist us in building the models. We describe the results of using our method on drawings and photographs of examples of diatoms, and present an active shape model built using automatically extracted data.

A method for shape analysis of diatoms (single-cell algae with silica shells) based on extraction of features on the contour of the cells by multi-scale mathematical morphology is presented. After building a morphological contour curvature scale space, we present a method for extracting the most prominent features by unsupervised cluster analysis. The number of extracted features matches well with those found visually in 92% of the 350 diatom images examined.