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Dive into the research topics where Andrew Blake is active.

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Featured researches published by Andrew Blake.


Genome Biology | 2013

A comparative phenotypic and genomic analysis of C57BL/6J and C57BL/6N mouse strains

Michelle Simon; Simon Greenaway; Jacqueline K. White; Helmut Fuchs; Valérie Gailus-Durner; Sara Wells; Tania Sorg; Kim Wong; Elodie Bedu; Elizabeth J. Cartwright; Romain Dacquin; Sophia Djebali; Jeanne Estabel; Jochen Graw; Neil Ingham; Ian J. Jackson; Andreas Lengeling; Silvia Mandillo; Jacqueline Marvel; Hamid Meziane; Frédéric Preitner; Oliver Puk; Michel J. Roux; David J. Adams; Sarah Atkins; Abdel Ayadi; Lore Becker; Andrew Blake; Debra Brooker; Heather Cater

BackgroundThe mouse inbred line C57BL/6J is widely used in mouse genetics and its genome has been incorporated into many genetic reference populations. More recently large initiatives such as the International Knockout Mouse Consortium (IKMC) are using the C57BL/6N mouse strain to generate null alleles for all mouse genes. Hence both strains are now widely used in mouse genetics studies. Here we perform a comprehensive genomic and phenotypic analysis of the two strains to identify differences that may influence their underlying genetic mechanisms.ResultsWe undertake genome sequence comparisons of C57BL/6J and C57BL/6N to identify SNPs, indels and structural variants, with a focus on identifying all coding variants. We annotate 34 SNPs and 2 indels that distinguish C57BL/6J and C57BL/6N coding sequences, as well as 15 structural variants that overlap a gene. In parallel we assess the comparative phenotypes of the two inbred lines utilizing the EMPReSSslim phenotyping pipeline, a broad based assessment encompassing diverse biological systems. We perform additional secondary phenotyping assessments to explore other phenotype domains and to elaborate phenotype differences identified in the primary assessment. We uncover significant phenotypic differences between the two lines, replicated across multiple centers, in a number of physiological, biochemical and behavioral systems.ConclusionsComparison of C57BL/6J and C57BL/6N demonstrates a range of phenotypic differences that have the potential to impact upon penetrance and expressivity of mutational effects in these strains. Moreover, the sequence variants we identify provide a set of candidate genes for the phenotypic differences observed between the two strains.


Database | 2011

BioMart Central Portal: an open database network for the biological community

Jonathan M. Guberman; J. Ai; Olivier Arnaiz; Joachim Baran; Andrew Blake; Richard Baldock; Claude Chelala; David Croft; Anthony Cros; Rosalind J. Cutts; A. Di Génova; Simon A. Forbes; T. Fujisawa; Emanuela Gadaleta; David Goodstein; Gunes Gundem; Bernard Haggarty; Syed Haider; Matthew Hall; Todd W. Harris; Robin Haw; Songnian Hu; Simon J. Hubbard; Jack Hsu; Vivek Iyer; Philip Jones; Toshiaki Katayama; Rhoda Kinsella; Lei Kong; Daniel Lawson

BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities. Database URL: http://central.biomart.org.


Nucleic Acids Research | 2014

The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data

Gautier Koscielny; Gagarine Yaikhom; Vivek Iyer; Terrence F. Meehan; Hugh Morgan; Julian Atienza-Herrero; Andrew Blake; Chao-Kung Chen; Richard Easty; Armida Di Fenza; Tanja Fiegel; Mark Grifiths; Alan Horne; Natasha A. Karp; Natalja Kurbatova; Jeremy Mason; Peter Matthews; Darren J. Oakley; Asfand Qazi; Jack Regnart; Ahmad Retha; Luis A. Santos; Duncan Sneddon; Jonathan Warren; Henrik Westerberg; Robert J. Wilson; David Melvin; Damian Smedley; Steve D. M. Brown; Paul Flicek

The International Mouse Phenotyping Consortium (IMPC) web portal (http://www.mousephenotype.org) provides the biomedical community with a unified point of access to mutant mice and rich collection of related emerging and existing mouse phenotype data. IMPC mouse clinics worldwide follow rigorous highly structured and standardized protocols for the experimentation, collection and dissemination of data. Dedicated ‘data wranglers’ work with each phenotyping center to collate data and perform quality control of data. An automated statistical analysis pipeline has been developed to identify knockout strains with a significant change in the phenotype parameters. Annotation with biomedical ontologies allows biologists and clinicians to easily find mouse strains with phenotypic traits relevant to their research. Data integration with other resources will provide insights into mammalian gene function and human disease. As phenotype data become available for every gene in the mouse, the IMPC web portal will become an invaluable tool for researchers studying the genetic contributions of genes to human diseases.


Nucleic Acids Research | 2010

EuroPhenome: a repository for high-throughput mouse phenotyping data

Hugh Morgan; Tim Beck; Andrew Blake; Hilary Gates; Niels C. Adams; Guillaume Debouzy; Sophie Leblanc; Christoph Lengger; Holger Maier; David Melvin; Hamid Meziane; Dave Richardson; Sara Wells; Jacqui White; Joe Wood; Martin Hrabé de Angelis; Steve D. M. Brown; John M. Hancock; Ann-Marie Mallon

The broad aim of biomedical science in the postgenomic era is to link genomic and phenotype information to allow deeper understanding of the processes leading from genomic changes to altered phenotype and disease. The EuroPhenome project (http://www.EuroPhenome.org) is a comprehensive resource for raw and annotated high-throughput phenotyping data arising from projects such as EUMODIC. EUMODIC is gathering data from the EMPReSSslim pipeline (http://www.empress.har.mrc.ac.uk/) which is performed on inbred mouse strains and knock-out lines arising from the EUCOMM project. The EuroPhenome interface allows the user to access the data via the phenotype or genotype. It also allows the user to access the data in a variety of ways, including graphical display, statistical analysis and access to the raw data via web services. The raw phenotyping data captured in EuroPhenome is annotated by an annotation pipeline which automatically identifies statistically different mutants from the appropriate baseline and assigns ontology terms for that specific test. Mutant phenotypes can be quickly identified using two EuroPhenome tools: PhenoMap, a graphical representation of statistically relevant phenotypes, and mining for a mutant using ontology terms. To assist with data definition and cross-database comparisons, phenotype data is annotated using combinations of terms from biological ontologies.


Nucleic Acids Research | 2007

EuroPhenome and EMPReSS: online mouse phenotyping resource

Ann-Marie Mallon; Andrew Blake; John M. Hancock

EuroPhenome (http://www.europhenome.org) and EMPReSS (http://empress.har.mrc.ac.uk/) form an integrated resource to provide access to data and procedures for mouse phenotyping. EMPReSS describes 96 Standard Operating Procedures for mouse phenotyping. EuroPhenome contains data resulting from carrying out EMPReSS protocols on four inbred laboratory mouse strains. As well as web interfaces, both resources support web services to enable integration with other mouse phenotyping and functional genetics resources, and are committed to initiatives to improve integration of mouse phenotype databases. EuroPhenome will be the repository for a recently initiated effort to carry out large-scale phenotyping on a large number of knockout mouse lines (EUMODIC).


Bioinformatics | 2005

EMPReSS: European Mouse Phenotyping Resource for Standardized Screens

E. C. J. Green; Georgios V. Gkoutos; Heena V. Lad; Andrew Blake; Joseph Weekes; John M. Hancock

UNLABELLED Standardized phenotyping protocols are essential for the characterization of phenotypes so that results are comparable between different laboratories and phenotypic data can be related to ontological descriptions in an automated manner. We describe a web-based resource for the visualization, searching and downloading of standard operating procedures and other documents, the European Mouse Phenotyping Resource for Standardized Screens-EMPReSS. AVAILABILITY Direct access: http://www.empress.har.mrc.ac.uk CONTACT [email protected].


BMC Bioinformatics | 2009

Practical application of ontologies to annotate and analyse large scale raw mouse phenotype data

Tim Beck; Hugh Morgan; Andrew Blake; Sara Wells; John M. Hancock; Ann-Marie Mallon

BackgroundLarge-scale international projects are underway to generate collections of knockout mouse mutants and subsequently to perform high throughput phenotype assessments, raising new challenges for computational researchers due to the complexity and scale of the phenotype data. Phenotypes can be described using ontologies in two differing methodologies. Traditionally an individual phenotypic character has either been defined using a single compound term, originating from a species-specific dedicated phenotype ontology, or alternatively by a combinatorial annotation, using concepts from a range of disparate ontologies, to define a phenotypic character as an entity with an associated quality (EQ). Both methods have their merits, which include the dedicated approach allowing use of community standard terminology, and the combinatorial approach facilitating cross-species phenotypic statement comparisons. Previously databases have favoured one approach over another. The EUMODIC project will generate large amounts of mouse phenotype data, generated as a result of the execution of a set of Standard Operating Procedures (SOPs) and will implement both ontological approaches to capture the phenotype data generated.ResultsFor all SOPs a four-tier annotation is made: a high-level description of the SOP, to broadly define the type of data generated by the SOP; individual parameter annotation using the EQ model; annotation of the qualitative data generated for each mouse; and the annotation of mutant lines after statistical analysis. The qualitative assessments of phenodeviance are made at the point of data entry, using child PATO qualities to the parameter quality. To facilitate data querying by scientists more familiar with single compound terms to describe phenotypes, the mappings between the Mammalian Phenotype (MP) ontology and the EQ PATO model are exploited to allow querying via MP terms.ConclusionWell-annotated and comparable phenotype databases can be achieved through the use of ontologically derived comparable phenotypic statements and have been implemented here by means of OBO compatible EQ annotations. The implementation we describe also sees scientists working seamlessly with ontologies through the assessment of qualitative phenotypes in terms of PATO qualities and the ability to query the database using community-accepted compound MP terms. This work represents the first time the combinatorial and single-dedicated approaches have both been implemented to annotate a phenotypic dataset.


Mammalian Genome | 2007

Mouse Phenotype Database Integration Consortium: integration [corrected] of mouse phenome data resources.

John M. Hancock; Niels C. Adams; Vassilis Aidinis; Andrew Blake; Molly Bogue; Steve D.M. Brown; Elissa J. Chesler; Duncan Davidson; Christopher Duran; Janan T. Eppig; Valérie Gailus-Durner; Hilary Gates; Georgios V. Gkoutos; Simon Greenaway; Martin Hrabé de Angelis; George Kollias; Sophie Leblanc; Kirsty Lee; Christoph Lengger; Holger Maier; Ann-Marie Mallon; Hiroshi Masuya; David Melvin; Werner Müller; Helen Parkinson; Glenn Proctor; Eli Reuveni; Paul N. Schofield; Aadya Shukla; Cynthia L. Smith

Understanding the functions encoded in the mouse genome will be central to an understanding of the genetic basis of human disease. To achieve this it will be essential to be able to characterize the phenotypic consequences of variation and alterations in individual genes. Data on the phenotypes of mouse strains are currently held in a number of different forms (detailed descriptions of mouse lines, first-line phenotyping data on novel mutations, data on the normal features of inbred lines) at many sites worldwide. For the most efficient use of these data sets, we have initiated a process to develop standards for the description of phenotypes (using ontologies) and file formats for the description of phenotyping protocols and phenotype data sets. This process is ongoing and needs to be supported by the wider mouse genetics and phenotyping communities to succeed. We invite interested parties to contact us as we develop this process further.


Comparative and Functional Genomics | 2004

Ontologies for the description of mouse phenotypes

G. V. Gkoutos; E. C. J. Green; Ann-Marie Mallon; Andrew Blake; Simon Greenaway; John M. Hancock; Duncan Davidson

Ontologies are becoming increasingly important for the efficient storage, retrieval and mining of biological data. The description of phenotypes using ontologies is a particularly complex problem. We outline a schema that can be used to describe phenotypes by combining orthologous axiomatic ontologies. We also describe tools for storing, browsing and searching such complex ontologies. Central to this approach is that assays (protocols for measuring phenotypic characters) describe what has been measured as well as how this was done, allowing assays to link individual organisms to ontologies describing phenotypes. We have evaluated this approach by automatically annotating data on 600 000 mutant mice phenotypes using the SHIRPA protocol. We believe this approach will enable the flexible, extensible and detailed description of phenotypes from any organism.


PLOS Biology | 2015

Applying the ARRIVE Guidelines to an In Vivo Database

Natasha A. Karp; Terry Meehan; Hugh Morgan; Jeremy Mason; Andrew Blake; Natalja Kurbatova; Damian Smedley; Julius Jacobsen; Richard F. Mott; Vivek Iyer; Peter Matthews; David Melvin; Sara Wells; Ann M. Flenniken; Hiroshi Masuya; Shigeharu Wakana; Jacqueline K. White; K. C. Kent Lloyd; Corey Reynolds; Richard Paylor; David B. West; Karen L. Svenson; Elissa J. Chesler; Martin Hrabě de Angelis; Glauco P. Tocchini-Valentini; Tania Sorg; Yann Herault; Helen Parkinson; Ann-Marie Mallon; Steve D. M. Brown

The Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines were developed to address the lack of reproducibility in biomedical animal studies and improve the communication of research findings. While intended to guide the preparation of peer-reviewed manuscripts, the principles of transparent reporting are also fundamental for in vivo databases. Here, we describe the benefits and challenges of applying the guidelines for the International Mouse Phenotyping Consortium (IMPC), whose goal is to produce and phenotype 20,000 knockout mouse strains in a reproducible manner across ten research centres. In addition to ensuring the transparency and reproducibility of the IMPC, the solutions to the challenges of applying the ARRIVE guidelines in the context of IMPC will provide a resource to help guide similar initiatives in the future.

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Ann-Marie Mallon

Wellcome Trust Sanger Institute

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David Melvin

Wellcome Trust Sanger Institute

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E. C. J. Green

Medical Research Council

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Helen Parkinson

European Bioinformatics Institute

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Niels C. Adams

Wellcome Trust Sanger Institute

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