Challenges of ultra large scale integration of biomedical computing systems

The NCRI Informatics Initiative is overseeing the implementation of an informatics framework for the UK cancer research community. The framework advocates an integrated multidisciplinary method of working between scientific and medical communities. Key to this process is community adoption of high quality acquisition, storage, sharing and integration of diverse data elements to improve knowledge of the causes, prevention and treatment of cancer. The integration of the complex data and meta-data used by these multiple communities is a significant challenge and there are technical, resource-based and sociological issues to be addressed. In this paper we review progress aimed at establishing the framework and outline key challenges in ultra large scale integration of biomedical computing systems

Mayday - integrative analytics for expression data

<p>Abstract</p> <p>Background</p> <p>DNA Microarrays have become the standard method for large scale analyses of gene expression and epigenomics. The increasing complexity and inherent noisiness of the generated data makes visual data exploration ever more important. Fast deployment of new methods as well as a combination of predefined, easy to apply methods with programmer's access to the data are important requirements for any analysis framework. Mayday is an open source platform with emphasis on visual data exploration and analysis. Many built-in methods for clustering, machine learning and classification are provided for dissecting complex datasets. Plugins can easily be written to extend Mayday's functionality in a large number of ways. As Java program, Mayday is platform-independent and can be used as Java WebStart application without any installation. Mayday can import data from several file formats, database connectivity is included for efficient data organization. Numerous interactive visualization tools, including box plots, profile plots, principal component plots and a heatmap are available, can be enhanced with metadata and exported as publication quality vector files.</p> <p>Results</p> <p>We have rewritten large parts of Mayday's core to make it more efficient and ready for future developments. Among the large number of new plugins are an automated processing framework, dynamic filtering, new and efficient clustering methods, a machine learning module and database connectivity. Extensive manual data analysis can be done using an inbuilt R terminal and an integrated SQL querying interface. Our visualization framework has become more powerful, new plot types have been added and existing plots improved.</p> <p>Conclusions</p> <p>We present a major extension of Mayday, a very versatile open-source framework for efficient micro array data analysis designed for biologists and bioinformaticians. Most everyday tasks are already covered. The large number of available plugins as well as the extension possibilities using compiled plugins and ad-hoc scripting allow for the rapid adaption of Mayday also to very specialized data exploration. Mayday is available at <url>http://microarray-analysis.org</url>.</p

vrmlgen: An R Package for 3D Data Visualization on the Web

The 3-dimensional representation and inspection of complex data is a frequently used strategy in many data analysis domains. Existing data mining software often lacks functionality that would enable users to explore 3D data interactively, especially if one wishes to make dynamic graphical representations directly viewable on the web. In this paper we present vrmlgen, a software package for the statistical programming language R to create 3D data visualizations in web formats like the Virtual Reality Markup Language (VRML) and LiveGraphics3D. vrmlgen can be used to generate 3D charts and bar plots, scatter plots with density estimation contour surfaces, and visualizations of height maps, 3D object models and parametric functions. For greater flexibility, the user can also access low-level plotting methods through a unified interface and freely group different function calls together to create new higher-level plotting methods. Additionally, we present a web tool allowing users to visualize 3D data online and test some of vrmlgen's features without the need to install any software on their computer.

eXframe: reusable framework for storage, analysis and visualization of genomics experiments

<p>Abstract</p> <p>Background</p> <p>Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types.</p> <p>Results</p> <p>We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients.</p> <p>Conclusion</p> <p>The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications.</p

Dys-regulated Gene Expression Networks by Meta-Analysis of Microarray Data on Oral Squamous Cell Carcinoma

Background: Oral squamous cell carcinoma (OSCC) is the sixth most common type of carcinoma worldwide. Development of OSCC is a multi-step process involving genes related to cell cycle, growth control, apoptosis, DNA damage response and other cellular regulators. The pathogenic pathways involved in this tumor are mostly unknown and therefore a better characterization of OSCC gene expression profile would represent a considerable advance. The availability of publicly available gene expression datasets has opened up new challenges especially for the integration of data generated by different research groups and different array platforms with the purpose of obtaining new insights on the biological process investigated.&#xd;&#xa;&#xd;&#xa;Results: In this work we performed a meta-analysis on four microarray and four datasets of gene expression data on OSCC in order to evaluate the degree of agreement of the biological results obtained by these different studies and to identify common regulatory pathways that could be responsible of tumor growth. Sixteen dys-regulated pathways implicated in OSCC were mined out from the four published datasets, and most importantly three pathways were first reported. Those regulatory pathways and biological processes which are significantly enriched have been investigated by means of literatures and meanwhile, four genes of the maximally altered pathways, ECM-receptor interaction, were validated and identified by qRT-PCR as a possible candidate of aggressiveness of OSCC.&#xd;&#xa;&#xd;&#xa;Conclusion: we have developed a robust method for analyzing pathways altered in OSCC using three expression array data sets. This study sets a stage for the further discovery of the basic mechanisms that may underlie a diseased state and would help in identifying critical nodes in the pathway that can be targeted for diagnosis and therapeutic intervention. In addition, those who are interested in our approach can obtain the software package (MATLAB platform) by email freely

SigTree: A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree.

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree, a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons

Two design patterns for visualising the parameter space of complex systems

A key feature of complex systems is that their behaviour can vary significantly depending on their location in parameter space. A major challenge for researchers is to understand how combinations of system parameters influence behaviour; that is, to understand the shape of parameter space. Tools for visualising the structure and dynamics of complex systems and the shape of their parameter spaces play an important role in addressing this challenge. Many of these tools are developed to address problems in specific domains. If complex systems share certain general properties that transcend their specific domain, it should be possible to share tools for understanding these systems between domains. One technique that has been proposed for achieving this is the use of design patterns