June 4, 2010

ParaSAM: a parallelized version of the significance analysis of microarrays algorithm

Filed under: Bioinformatics — Biointelligence: Education,Training & Consultancy Services @ 9:00 am
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Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements.

Summary: We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations.

Availability:A web version open to the public is available at For local installations, both the windows and web implementations of ParaSAM are available for free at

May 15, 2010

Supervised normalization of microarrays

Filed under: Bioinformatics — Biointelligence: Education,Training & Consultancy Services @ 9:30 am
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A major challenge in utilizing microarray technologies to measure nucleic acid abundances is ‘normalization’, the goal of which is to separate biologically meaningful signal from other confounding sources of signal, often due to unavoidable technical factors. It is intuitively clear that true biological signal and confounding factors need to be simultaneously considered when performing normalization. However, the most popular normalization approaches do not utilize what is known about the study, both in terms of the biological variables of interest and the known technical factors in the study, such as batch or array processing date.

Results: We show here that failing to include all study-specific biological and technical variables when performing normalization leads to biased downstream analyses. We propose a general normalization framework that fits a study-specific model employing every known variable that is relevant to the expression study. The proposed method is generally applicable to the full range of existing probe designs, as well as to both single-channel and dual-channel arrays. We show through real and simulated examples that the method has favorable operating characteristics in comparison to some of the most highly used normalization methods.

Availability: An R package called snm implementing the methodology will be made available from Bioconductor (

November 10, 2009

BASE – A software for Microarray Data Management and Analysis

Filed under: Bioinformatics,Microarray — Biointelligence: Education,Training & Consultancy Services @ 4:27 am
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Microarray techniques produce large amounts of data in many different formats and experiment sizes are growing with more samples analysed in each experiment. Samples are collected over long time and microarray analysis is performed asynchronously and re-analysed as more samples are hybridised. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. Particularly for microarray service facilities, where researchers deposit samples for experimentation, information tracking becomes vital for a subsequent data delivery back to the researchers. To meet the information tracking and data analysis challenges involved in microarray experiments BASE has been implemented.

BASE (Bioarray Software Environment) is a comprehensive free web-based database solution for the massive amounts of data generated by microarray analysis. It is a MIAME (Minimum Information About a Microarray Experiment guidelines) compliant application designed for microarray laboratories looking for a single point of storage for all information related to their microarray experimentation. BASE is a multi-user local data repository that features a web browser user interface, laboratory information management system (LIMS) for biomaterials and array production, annotations, hierarchical overview of analysis, and integrates tools like MultiExperiment Viewer (MEV) and GenePattern.

BASE is an annotable microarray data repository and analysis application providing researchers with efficient information management and analysis. BASE stores all microarray experiment related data, biomaterial information, and annotations regardless if analysis tools for specific techniques or data formats are readily available. As new techniques becomes available software applications should be expendable and modifiable to support changed needs. Moreover, it is an open source software and is freely available.

BASE website:

September 11, 2009

List of Companies working on Microarrays and related Data Analysis

Affymetrix —  Developing systems to acquire, analyze and manage genetic info.
Agilent Technologies —   Provider of a range of microarrays for different organisms, manufacture the 2100 bioanalyzer.
Asper Biotechnology —   Manufacture coated microarray glass slides.
Axon Instruments —  Design and manufacture of instrumentation for genomics and proteomics.
BioDiscovery —   Providing software solutions for gene expression research.
BioMicro Systems — Providing the MAUI Hybridization system for active mixing of ultra low volumes during microarray hybridization.
BioRobotics —  Design, manufacture, and supply of automated solutions for molecular biology research.
BioSieve —  Provides microarray data analysis package on Java platform.
Cartesian Technologies —   Providing tools for microscale liquid handling and associated automation.
Clondiag Chip Technologies —  Imaging and LIMS software and technologies.
Clontech — Development and production of innovative biological products.
GeneData —  Providing computational solutions for analyisis of large quantities of data.
GeneLogic — Providing a data management platform for large-scale data analysis.
Genemachines — Developing machinery for genomics automation.
Gene Network Sciences — Developing dynamic computer models of living cells and next generation data-mining tools.
Genomic Solutions — Providing a variety of genomic research tools.
Genetix — Providing microarray printers, scanners, reagents and consumables.
Genotypic — A genomics and bioinformatics company, providing microarray products & services.
Genome Explorations Inc. — Providing Gene Expression analysis using the Affymetrix Platform.
Iobion Informatics LLC —   Microarray data management and analysis software.
LION Bioscience — Providing expression data analysis systems.
Molecular Dynamics —  Developing and manufacturing microarray systems.
Motorola Life Sciences — Developing system solutions for high-performance gene espression profiling.
MWG Biotech — Microarray provider of multiple whole genome arrays, custom arrays and other array products
Ocimum Biosolutions — Providing biotechnology software solutions, including Genowiz for micorarray data analysis and management.
Packard BioScience — Producing tools used in genomics and proteomics.
Perkin Elmer — Providing a list of various microarray products.
Rosetta Inpharmatics — Providers of bioinformatics solutions and gene expression analysis systems.
Scanalytics — Providing image analysis software for extracting and visualizing DNA microarray data.
Silicon Genetics — Providing genomic expression data analysis, visualization, mining, and storage products.
SSI Robotics — Robotic automation systems and instrument integration for life science related processes.
Superarray Bioscience — Developing pathway/application specific gene expression tools

Add more to this list…… !!!