Luminex is a bead-based multi-analyte profiling technology that lets you measure up to 100 proteins in a single sample (in this case, cell supernatants).

So in order to avoid doing endless ELISAs to detect proteins one-by-one, I sent a set of samples to our friendly local core facility for custom Luminex analysis. Here’s the setup: in my lab, we’re interested in innate immune cells and the proteins they secrete.

Finding biological meaning from significant parameter lists.

Graphing plots from high-dimensional data in R.

Going digital: Moving your biological data to R.

Obviously, you’re going to need to go beyond Excel and Prism to get the most out of this type of data, but where to start? In this article, I’ll be describing several real-life analysis solutions involving large datasets, written for non-computational biologists. We’re not talking about impact factor here (sadly)-the rise of multiplexed modalities and new technologies has made it possible to collect dozens to thousands of different parameters on a single sample, where back in the day an entire PhD would have been dedicated to achieving the same result.

If you’re a scientist working in biomedical research today, chances are the datasets you’re working with are getting bigger and bigger.

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