Manuel Corpas

DECIPHER: Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources

Many patients suffering from developmental disorders harbor submicroscopic deletions or duplications that, by affecting the copy number of dosage-sensitive genes or disrupting normal gene expression, lead to disease. However, many aberrations are novel or extremely rare, making clinical interpretation problematic and genotype-phenotype correlations uncertain. Identification of patients sharing a genomic rearrangement and having phenotypic features in common leads to greater certainty in the pathogenic nature of the rearrangement and enables new syndromes to be defined. To facilitate the analysis of these rare events, we have developed an interactive web-based database called DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) which incorporates a suite of tools designed to aid the interpretation of submicroscopic chromosomal imbalance, inversions, and translocations. DECIPHER catalogs common copy-number changes in normal populations and thus, by exclusion, enables changes that are novel and potentially pathogenic to be identified. DECIPHER enhances genetic counseling by retrieving relevant information from a variety of bioinformatics resources. Known and predicted genes within an aberration are listed in the DECIPHER patient report, and genes of recognized clinical importance are highlighted and prioritized. DECIPHER enables clinical scientists worldwide to maintain records of phenotype and chromosome rearrangement for their patients and, with informed consent, share this information with the wider clinical research community through display in the genome browser Ensembl. By sharing cases worldwide, clusters of rare cases having phenotype and structural rearrangement in common can be identified, leading to the delineation of new syndromes and furthering understanding of gene function.

BioJS: an open source JavaScript framework for biological data visualization.

SUMMARYnBioJS is an open-source project whose main objective is the visualization of biological data in JavaScript. BioJS provides an easy-to-use consistent framework for bioinformatics application programmers. It follows a community-driven standard specification that includes a collection of components purposely designed to require a very simple configuration and installation. In addition to the programming framework, BioJS provides a centralized repository of components available for reutilization by the bioinformatics community.nnnAVAILABILITY AND IMPLEMENTATIONnhttp://code.google.com/p/biojs/.nnnSUPPLEMENTARY INFORMATIONnSupplementary data are available at Bioinformatics online.

GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training

In recent years, high-throughput technologies have brought big data to the life sciences. The march of progress has been rapid, leaving in its wake a demand for courses in data analysis, data stewardship, computing fundamentals, etc., a need that universities have not yet been able to satisfy—paradoxically, many are actually closing “niche” bioinformatics courses at a time of critical need. The impact of this is being felt across continents, as many students and early-stage researchers are being left without appropriate skills to manage, analyse, and interpret their data with confidence. This situation has galvanised a group of scientists to address the problems on an international scale. For the first time, bioinformatics educators and trainers across the globe have come together to address common needs, rising above institutional and international boundaries to cooperate in sharing bioinformatics training expertise, experience, and resources, aiming to put ad hoc training practices on a more professional footing for the benefit of all.

The GOBLET Training Portal: A Global Repository of Bioinformatics Training Materials, Courses and Trainers

Summary: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide. Availability and implementation: http://mygoblet.org/training-portal Contact: manuel.corpas@tgac.ac.uk

BioJS: an open source standard for biological visualisation - its status in 2014.

BioJS is a community-based standard and repository of functional components to represent biological information on the web. The development of BioJS has been prompted by the growing need for bioinformatics visualisation tools to be easily shared, reused and discovered. Its modular architecture makes it easy for users to find a specific functionality without needing to know how it has been built, while components can be extended or created for implementing new functionality. The BioJS community of developers currently provides a range of functionality that is open access and freely available. A registry has been set up that categorises and provides installation instructions and testing facilities at http://www.ebi.ac.uk/tools/biojs/. The source code for all components is available for ready use at https://github.com/biojs/biojs.

A Quick Guide for Building a Successful Bioinformatics Community

“Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop “The ‘How To Guide’ for Establishing a Successful Bioinformatics Network” at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB).

Anatomy of BioJS, an open source community for the life sciences

BioJS is an open source software project that develops visualization tools for different types of biological data. Here we report on the factors that influenced the growth of the BioJS user and developer community, and outline our strategy for building on this growth. The lessons we have learned on BioJS may also be relevant to other open source software projects. DOI: http://dx.doi.org/10.7554/eLife.07009.001

Lessons from Fraxinus, a crowd-sourced citizen science game in genomics

In 2013, in response to an epidemic of ash dieback disease in England the previous year, we launched a Facebook-based game called Fraxinus to enable non-scientists to contribute to genomics studies of the pathogen that causes the disease and the ash trees that are devastated by it. Over a period of 51 weeks players were able to match computational alignments of genetic sequences in 78% of cases, and to improve them in 15% of cases. We also found that most players were only transiently interested in the game, and that the majority of the work done was performed by a small group of dedicated players. Based on our experiences we have built a linear model for the length of time that contributors are likely to donate to a crowd-sourced citizen science project. This model could serve a guide for the design and implementation of future crowd-sourced citizen science initiatives. DOI: http://dx.doi.org/10.7554/eLife.07460.001

A Family Experience of Personal Genomics

This article presents a personal journey of a close-knit family from Málaga, Spain who engaged with direct-to-consumer (DTC) genomic testing. Whilst the testing was initiated by one member of the family who works as a genome bioinformatician, none of the remaining family had any prior experience with DTC genetic testing. A thoughtful account, written in the first person, is offered on the experience of genome testing across the various members of the family together with a reflection on how it felt to be a custodian of the ‘family genome’. The way the family processed their genome information is explored and the difficulties and challenges that resulted are discussed. Whilst there is a wealth of literature that describes how families communicate information surrounding single genes, there is very little which explores the experience of communication about whole, shared genomes. The experiences described in this paper provide an insight into this new territory.

Interpretation of genomic copy number variants using DECIPHER.

Many patients suffering from developmental disorders have submicroscopic deletions or duplications affecting the copy number of dosage‐sensitive genes or disrupting normal gene expression. Many of these changes are novel or extremely rare, making clinical interpretation problematic and genotype/phenotype correlations difficult. Identification of patients sharing a genomic rearrangement and having phenotypes in common increases certainty in the diagnosis and allows characterization of new syndromes. The DECIPHER database is an online repository of genotype and phenotype data whose chief objective is to facilitate the association of genomic variation with phenotype to enable the clinical interpretation of copy number variation (CNV). This unit shows how DECIPHER can be used to (1) search for consented patients sharing a defined chromosomal location, (2) navigate regions of interest using in‐house visualization tools and the Ensembl genome browser, (3) analyze affected genes and prioritize them according to their likelihood of haploinsufficiency, (4) upload patient aberrations and phenotypes, and (5) create printouts at different levels of detail. By following this protocol, clinicians and researchers alike will be able to learn how to characterize their patients chromosomal imbalances using DECIPHER. Curr. Protoc. Hum. Genet. 72:8.14.1‐8.14.17