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1.  Assessing association between protein truncating variants and quantitative traits 
Bioinformatics  2013;29(19):2419-2426.
Motivation: In sequencing studies of common diseases and quantitative traits, power to test rare and low frequency variants individually is weak. To improve power, a common approach is to combine statistical evidence from several genetic variants in a region. Major challenges are how to do the combining and which statistical framework to use.
General approaches for testing association between rare variants and quantitative traits include aggregating genotypes and trait values, referred to as ‘collapsing’, or using a score-based variance component test. However, little attention has been paid to alternative models tailored for protein truncating variants. Recent studies have highlighted the important role that protein truncating variants, commonly referred to as ‘loss of function’ variants, may have on disease susceptibility and quantitative levels of biomarkers. We propose a Bayesian modelling framework for the analysis of protein truncating variants and quantitative traits.
Results: Our simulation results show that our models have an advantage over the commonly used methods. We apply our models to sequence and exome-array data and discover strong evidence of association between low plasma triglyceride levels and protein truncating variants at APOC3 (Apolipoprotein C3).
Availability: Software is available from http://www.well.ox.ac.uk/~rivas/mamba
Contact: donnelly@well.ox.ac.uk
doi:10.1093/bioinformatics/btt409
PMCID: PMC3777107  PMID: 23860716
2.  SAIL—a software system for sample and phenotype availability across biobanks and cohorts 
Bioinformatics  2010;27(4):589-591.
Summary: The Sample avAILability system—SAIL—is a web based application for searching, browsing and annotating biological sample collections or biobank entries. By providing individual-level information on the availability of specific data types (phenotypes, genetic or genomic data) and samples within a collection, rather than the actual measurement data, resource integration can be facilitated. A flexible data structure enables the collection owners to provide descriptive information on their samples using existing or custom vocabularies. Users can query for the available samples by various parameters combining them via logical expressions. The system can be scaled to hold data from millions of samples with thousands of variables.
Availability: SAIL is available under Aferro-GPL open source license: https://github.com/sail.
Contact: gostev@ebi.ac.uk, support@simbioms.org
Supplementary information: Supplementary data are available at Bioinformatics online and from http://www.simbioms.org.
doi:10.1093/bioinformatics/btq693
PMCID: PMC3035801  PMID: 21169373
3.  A System for Information Management in BioMedical Studies—SIMBioMS 
Bioinformatics  2009;25(20):2768-2769.
Summary: SIMBioMS is a web-based open source software system for managing data and information in biomedical studies. It provides a solution for the collection, storage, management and retrieval of information about research subjects and biomedical samples, as well as experimental data obtained using a range of high-throughput technologies, including gene expression, genotyping, proteomics and metabonomics. The system can easily be customized and has proven to be successful in several large-scale multi-site collaborative projects. It is compatible with emerging functional genomics data standards and provides data import and export in accepted standard formats. Protocols for transferring data to durable archives at the European Bioinformatics Institute have been implemented.
Availability: The source code, documentation and initialization scripts are available at http://simbioms.org.
Contact: support@simbioms.org; mariak@ebi.ac.uk
doi:10.1093/bioinformatics/btp420
PMCID: PMC2759553  PMID: 19633095

Results 1-3 (3)