![]() “This massively reduces the overall costs for each microarray project relative to. Free software can analyze microarray data quickly and reliably and “transform data into biological insights in minutes, compared to weeks or sometimes even months with ,” says Anthony Schweitzer, head of bioinformatics in the expression business unit at Affymetrix. Another advantage: ease of data analysis. Microarrays also are faster to run than NGS experiments, and the equipment is broadly available. A targeted DNA microarray runs from $10 to $100 per sample, says Schena, whereas “the whole human genome is typically $100 $1,000 per sample.” (Targeting strategies are also available for NGS, to avoid the costs incurred by whole-genome sequencing, but they also add both cost and time.) Microarrays also can save funds by targeting variants rather than the entire genome, “which is 99.9% identical in all individuals, adds cost but not information, because it is invariant,” says Mark Schena, president of Arrayit. NGS, in contrast, costs hundreds to thousands of dollars per sample-and that’s assuming existing access to an NGS platform-meaning that for analyses requiring many samples, such as clinical studies, NGS costs can quickly become prohibitive. But rough estimates put microarrays at about $100 (or less) per sample for basic genomic studies, and up to $300 per sample for more complex studies, such as splice variant analysis, says Kim Caple, senior vice president and general manager of clinical business at Affymetrix. Many variables factor into cost estimates, including consumables, labor, time, sample type and (for NGS) the required read depth. Still, rumors of the death of microarrays have been, as they say, greatly exaggerated, and many researchers still use them. For instance, why look for phenotype-associated genetic markers when you can simply sequence the genome from end to end instead? In a sense, NGS changed the playing field by changing the types of questions researchers could ask. And then along came next-generation DNA sequencing (NGS), a method that seemingly can do everything microarrays can, and more. No longer did they need to probe one gene or transcript at a time with microarrays, they could extend their studies to the whole-genome or transcriptome level with little extra effort. Essentially grids of thousands or even millions of tiny spots of DNA printed onto glass slides, DNA microarrays enabled scientists to massively parallelize their research. Researchers have used DNA microarrays to drive genetic analyses for more than two decades. in neuroscience from Yale University, and completed postdoctoral work at the Vollum Institute.
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