Generating a visual representation is often the best way to understand large data sets, but standard tools such as gnuplot often fall short. This article shows how to use Perl/Tk, the standard GUI toolkit for Perl, to quickly build custom plotting and graphing tools |
Data Mining:
The need to integrate, visualize and mine different genomics data from growing sources is accelerating. The number of data mining tools, especially those for
microarray data is also rapidly increasing. A few examples of available tools are the free Genesis and J-Express for annotated microarray data or commercial tools such as SpotFire (http://www.spotfire.com/). Most data mining applications are costly, restricted to one or a few computer platforms, or they are specialized for handling data from one type of experiment. Also, using commercial software in development of new suites of software may lead to licensing and distribution issues. In order to accommodate the changing genomic data formats and database schemas without having to change the data mining and visualization tool, we developed TableView. Whether biologists are looking for patterns or genes of interest in SAGE,EST, microarray data or mining other genomics data, even in different databases, Table View can be used to do the work, easing the integration of different data types for visual exploration.
Microarray Data Analysis:
Functional genomics involves the analysis of large datasets of information derived from
various biological experiments. One such type of large-scale experiment involves monitoring
the expression levels of thousands of genes simultaneously under a particular condition,
called gene expression analysis. Microarray technology makes this possible and the quantity
of data generated from each experiment is enormous, dwarfi ng the amount of data generated
by genome sequencing project. Microarray technology has become one of the indispensable tools that many biologists use to monitor genome wide expression levels of genes in a given organism
Genomics refers to the comprehensive study of genes and their function. Recent advances in bioinformatics and high-throughput technologies such as microarray analysis are bringing about a revolution in our understanding of the molecular mechanisms underlying normal and dysfunctional biological processes. Microarray studies and other genomic techniques are also stimulating the discovery of new targets for the treatment of disease which is aiding drug development, immunotherapeutics and gene therapy. In this site, we have compiled an extensive list of resources to assist reseachers interested in establishing a microarray platform and performing expression profiling experiments.
Gene expression profiling or microarray analysis has enabled the measurement of thousands of genes in a single RNA sample. There are a variety of microarray platforms that have been developed to accomplish this and the basic idea for each is simple: a glass slide or membrane is spotted or "arrayed" with DNA fragments or oligonucleotides that represent specific gene coding regions. Purified RNA is then fluorescently- or radioactively labeled and hybridized to the slide/membrane. In some cases, hybridization is done simultaneously with reference RNA to facilitate comparison of data across multiple experiments. After thorough washing, the raw data is obtained by laser scanning or autoradiographic imaging . At this point, the data may then be entered into a database and analyzed by a number of statistical methods.
A number of issues must be addressed before establishing a microarray platform and beginning expression profiling studies, in particular, the overall cost. For a cDNA microarray platform, one must purchase a clone set, robot, printing pins and the reagents needed for DNA amplification and purification. The cost of these materials can vary significantly, but one can expect to need at least $100,000 to establish such a platform. However, once the process of printing and hybridizing microarrays has been optimized, the cost per experiment will fall dramatically. Thus, one must decide if the number of planned experiments is enough to warrant the time and cost of establishing a microarray platform. If not, it may be more prudent to seek the services of an academic microarray core facility or a commercial entity. |
