by Caitlin Smith
The use of microarrays—tiny arrangements of known samples, such as probes, which can be hybridized to unknown samples—has revolutionized how scientists study gene expression. Thousands of these samples are spotted onto a solid support, such as microscope glass slides, silicon chips, or nylon membranes. New applications are emerging (see below), but common uses of microarrays include the discovery of new genes, and the study of their expression patterns; with a single DNA chip, you can evaluate the expression of thousands of genes simultaneously. Microarrays are also frequently used to diagnose diseases, especially for specifying types of cancer.
But making sense of the reams of data that come from microarrays can be overwhelming. And yet the process needn’t be, because microarray analysis at its heart is simpler than many expect it to be—especially with the right software. The latest developments in microarray analysis software should help you steam through that analysis in no time.
Flexibility and ease of use
With the release of their Nexus CGH imminent, BioDiscovery aims to make lab life easier for researchers: “The challenge has been to create a product that can be used by scientists. Our approach has been to create application-specific products rather than tool boxes.” BioDiscovery tries to make the software very easy to use, even for non-statisticians. “We focused to create a platform-independent software solution for doing advanced copy number analysis from scratch,” says BioDiscovery’s President, Soheil Shams.
Another market leader geared toward ease of use is Molecular Devices, which offers their GenePix® Pro 6.1 and Acuity® software packages. “GenePix® Pro software is unique in that it was the first software package that integrated hardware control with data analysis, allowing users to immediately transition from image acquisition to spot-finding, normalization, and visualization without the requirement of running separate programs,” says Varshal Davé, director of marketing, microarray, and microdissection. Other companies have emulated GenePix® Pro software in some ways, says Davé, such as “the simplicity and visual appeal of the user interface, [and] the utilization of the industry-standard file formats that we invented years ago—GenePix® Array Lists (GAL files), and GenePix® Results (GPR files).” GenePix® Pro and Acuity® were designed with the idea of empowering biologists to analyze their own microarray data from a biologically relevant standpoint, rather than previous “black box” software methods that only required the user to plug in the data. They are designed so that the scientist has access to the data at all times during analysis, and so that manipulations to the data are apparent at all times.
The challenge of new applications
The rapid expansion of microarray technology is challenging software developers to come up with ways to integrate a myriad of new applications.
“There are a number of diverging directions in which the maturing microarray industry is going, brought on primarily by the acceptance in the market of the broad applicability of microarray technology,” says Davé. Now that microarrays have become an accepted form of experimentation, scientists are using them in many areas of research. “The increasing numbers of applications are taking us out of the traditional realm of gene expression analysis and into new fields, such as array-based comparative genomic hybridization, DNA methylation, chromatin immunoprecipitation, SNP analysis, splice variance, and resequencing, to name a few.” In addition to DNA microarrays, the use of protein and tissue microarrays is on the rise. Microarrays themselves are also becoming more complex, with higher density and smaller feature size, and multiple parallel arrays per slide, or even microtiter plate wells. “Our software, therefore, has to be able to handle these increased demands, and adapt to the variety of formats and densities,” says Davé.
Microarray technology is also moving into clinical diagnostics. “Going forward, we see this trend increasing as regulatory agencies are coming to a better understanding of the diagnostic implications of microarray data,” says Davé. “The guidelines for regulatory approval are still somewhat in flux, but it becomes much more important for microarray data analysis software developers to work closely with array application developers, as well as with the regulatory agencies, to create solutions which adhere to these regulatory requirements.”
Emphasizing biological relevance of results
Agilent is planning to release a new version of its GeneSpring GX at the end of the year. It is designed, in partnership with Strand Life Sciences, to “provide our users guidance through the complex gene expression analysis workflows, while also providing users access to the biological relevance of their results,” says Product Manager Thon Deboer.
Deboer says that GeneSpring “allows the non-expert user access to the powerful statistical analyses needed due to the complex nature of gene expression data, without the need to be a statistical expert, so the user can focus on the biological relevance of the results. There will also be a tight integration with the pathway analysis tool Pathway Architect, which allows for access to the vast knowledge base on gene, protein and small molecule interaction from the literature.”
A major challenge in microarray-based gene expression is the large amount of information you suddenly have to interpret. “Having access to the expression values of thousands of genes from many different experimental conditions, like tissues, disease state, treatment type, etc., does not result directly in the biological insight that is required to understand the underlying causes of the diseases or insight into the fundamental workings of the organism under study,” explains Deboer. “Complete understanding can only be achieved by combining many different approaches and technologies. Combining information on the expression level of genes, with other measurement technologies such as copy number variations of genes, genomic methylation patterns, and protein modification state of the millions of proteins as measured by mass spectrometry technologies is going to be required [for] full insight.”
At Ariadne Genomics, biological relevance also takes priority with their Pathway Studio software package, which contains “enrichment algorithms that can be used to mine the set of a hundred thousand networks for the ones that provide the best fit to the microarray data and thus offer a mechanistic explanation of the changes observed,” says Product Manager David Denny.
Ariadne Genomics’ ResNet Database consists of experimentally derived, biologically relevant facts about protein and small molecule interactions and regulation. “Because our ResNet is more comprehensive than other knowledge based products, and can be easily extended with domain specific knowledge by the end-user, the tool is more flexible to answer compelling and emerging research questions,” says Denny.
Denny agrees with Deboer that a multidisciplinary approach is more likely to be fruitful. “We see a big trend in combining various kinds of data, such as gene expression data, proteomics data, and phosphorylation data. Many systems provide an analysis of these data independently but do not offer a view that leverages the benefit of integrating these data together. As more disparate types of data become prolific, tools that integrate and interpret that data will become more essential.”
