Web-based Tools for the Analysis of DNA Microarrays

End of project reportDNA microarrays are widely used for gene expression profiling. Raw data resulting from microarray experiments, however, tends to be very noisy and there are many sources of technical variation and bias. This raw data needs to be quality assessed and interactively preprocessed to minimise variation before statistical analysis in order to achieve meaningful result. Therefore microarray analysis requires a combination of visualisation and statistical tools, which vary depending on what microarray platform or experimental design is used.Bioconductor is an existing open source software project that attempts to facilitate analysis of genomic data. It is a collection of packages for the statistical programming language R. Bioconductor is particularly useful in analyzing microarray experiments. The problem is that the R programming language’s command line interface is intimidating to many users who do not have a strong background in computing. This often leads to a situation where biologists will resort to using commercial software which often uses antiquated and much less effective statistical techniques, as well as being expensively priced. This project aims to bridge this gap by providing a user friendly web-based interface to the cutting edge statistical techniques of Bioconductor

Systematic meta-analyses and field synopsis of genetic and epigenetic studies in paediatric inflammatory bowel disease

We provide a comprehensive field synopsis of genetic and epigenetic associations for paediatric Inflammatory Bowel Disease (IBD). A systematic review was performed and included 84 genetic association studies reporting data for 183 polymorphisms in 71 genes. Meta-analyses were conducted for 20 SNPs in 10 genes of paediatric Crohn’s disease (CD) and for 8 SNPs in 5 genes of paediatric ulcerative colitis (UC). Five epigenetic studies were also included, but formal meta-analysis was not possible. Venice criteria and Bayesian false discovery probability test were applied to assess the credibility of associations. Nine SNPs in 4 genes were considered to have highly credible associations with paediatric CD, of which four variants (rs2066847, rs12521868, rs26313667, rs1800629) were not previously identified in paediatric GWAS. Differential DNA methylation in NOD2 and TNF-α, dysregulated expression in let-7 and miR-124 were associated with paediatric IBD, but not as yet replicated. Highly credible SNPs associated with paediatric IBD have also been implicated in adult IBD, with similar magnitudes of associations. Early onset and distinct phenotypic features of paediatric IBD might be due to distinct epigenetic changes, but these findings need to be replicated. Further progress identifying genetic and epigenetic susceptibility of paediatric IBD will require international collaboration, population diversity and harmonization of protocols

Statistical and integrative system-level analysis of DNA methylation data

Epigenetics plays a key role in cellular development and function. Alterations to the epigenome are thought to capture and mediate the effects of genetic and environmental risk factors on complex disease. Currently, DNA methylation is the only epigenetic mark that can be measured reliably and genome-wide in large numbers of samples. This Review discusses some of the key statistical challenges and algorithms associated with drawing inferences from DNA methylation data, including cell-type heterogeneity, feature selection, reverse causation and system-level analyses that require integration with other data types such as gene expression, genotype, transcription factor binding and other epigenetic information

Bioconductorbuntu: a linux distribution that implements a web-based dna microarray analysis server

BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets

Web-based Tools for the Analysis of DNA Microarrays

End of project reportDNA microarrays are widely used for gene expression profiling. Raw data resulting from microarray experiments, however, tends to be very noisy and there are many sources of technical variation and bias. This raw data needs to be quality assessed and interactively preprocessed to minimise variation before statistical analysis in order to achieve meaningful result. Therefore microarray analysis requires a combination of visualisation and statistical tools, which vary depending on what microarray platform or experimental design is used.Bioconductor is an existing open source software project that attempts to facilitate analysis of genomic data. It is a collection of packages for the statistical programming language R. Bioconductor is particularly useful in analyzing microarray experiments. The problem is that the R programming language’s command line interface is intimidating to many users who do not have a strong background in computing. This often leads to a situation where biologists will resort to using commercial software which often uses antiquated and much less effective statistical techniques, as well as being expensively priced. This project aims to bridge this gap by providing a user friendly web-based interface to the cutting edge statistical techniques of Bioconductor