My youngest daughter was recently watching a rerun of Home Improvement featuring Tim “The Tool Man” Taylor and his mock TV show Tool Time. She said “Dad, you and Tim both seem to get into a lot of trouble when playing with power tools.” My wife added that throwing a statistical degree into the mix appears to have increased the trouble coefficient. My vehement objections were met with a reminder of several recent incidents, including how we spent most of New Year’s Eve this year without water due to a slight mishap with copper joint I had sweated in a downstairs bathroom renovation project. OK, so I’m a DIY junkie and have a garage full of tools, but the operative word in this instance is slight.
Of course no home project would get very far without a power drill, and I have three: an 18V cordless with dual batteries, an old-school 3/8” Craftsman that works great whenever those accursed batteries weaken, and a red 1/2” Milwaukee complete with side handle and heavy duty chuck. The Milwaukee is great for man stuff like drilling holes in railroad ties and mixing big batches of thinset mortar. Tim would give it an “Urghh Urghh” (my feeble attempt to spell his signature simian/caveman/Scooby-Do/Chewbacca grunt)
Which brings us to the topic of this blog: Drill Down. Genomics data sets typically require conducting tens of thousands to millions (and in some cases even billions) of statistical tests, and we are immediately faced with how to most effectively present and explore the most significant ones. The idea behind Drill Down is to start with a summary graphic that highlights interesting points and enables you interactively zoom on them and obtain more statistical or graphical detail hierarchically.
A prototypical example of such a summary graph is a volcano plot, e.g. as generated by JMP Genomics’ One-Way ANOVA Analytical Process:
Each point represents a gene. The X-axis charts some measure of change (e.g. a difference between least-squares means) and the Y-axis is the corresponding –log10 p-value. The plot has a characteristic V-shape because of the statistical relationship between X and Y. The most significant points are towards the top and resemble lava rocks erupting from a volcano [insert Tim Taylor grunt here] and the least significant ones--a vast majority--are nicely overstruck at the bottom. The plots are dynamically linked to other displays like dendrograms and parallel plots, complete with brushing and zooming, capabilities not available in R. (Historical note: I believe Greg Gibson and I coined the term “volcano plot” in a 2001 Nature Genetics paper.)
After selecting desired points in the volcano, go to the window of “Action Buttons”, which offers a variety of Drill Down capabilities:
Drill Down with such Action Buttons is different from zoom a la Google Earth; you can launch sophisticated statistical analyses on the selected points, taking full advantage of either SAS or JMP functionality. For example, “Fit Model to Input Data for Selected Rows and Plot LS Means” launches JMP’s Fit Model platform on the selected genes (using the same model that you originally specified) and produces an informative integrated mix of statistical tables and graphics. Clicking “Plot OneWay Means by Chromosome and Position” fits one-way models in a SAS Data Step and then generates graphs like the following:
In this case the expression profiles of three treatment conditions are plotted along a very short section of the genome. The width of the confidence bands is interactively adjustable and the plot is embellished with gene track annotation that was automatically incorporated from a supplemental file specified in the initial JMPG dialog. You can drill down further and bring up various web pages corresponding to genes of interest.
So “Urghh Urghh” for Drill Down! It’s available in a few other places in JMP Genomics (e.g. Multidimensional Scaling and Predictive Modeling) and you can expect more in future releases.
By the way, that bathroom project is now finished and turned out beautifully. All three of the drills came in handy (if you want to borrow the Milwaukee please let me know). It took a mere four months to complete and cost only 3x more than our initial high-end estimate. More importantly, interlocutors are happily silent (at least until the next home improvement project begins) .
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