Distractions and amusements, with a sandwich and coffee.
With some very smart people, I work on problems in data visualization applied to cancer research and genome analysis. Previously I was involved in fingerprint mapping, system administration, computer security, fashion photography, medical imaging and LHC particle physics. My work is guided by a need to rationalize, make things pretty, combine science with art, mince words, find good questions, help make connections between ideas and explain complicated things. All while exercising snark.
The Sanctuary Project is a Lunar vault of science and art. It includes two fully sequenced human genomes, sequenced and assembled by us at Canada's Michael Smith Genome Sciences Centre.
The first disc includes a song composed by Flunk for the (eventual) trip to the Moon.
But how do you send sound to space? I describe the inspiration, process and art behind the work.
Celebrate `\pi` Day (March 14th) and finally see the digits through the forest.
This year is full of botanical whimsy. A Lindenmayer system forest – deterministic but always changing. Feel free to stop and pick the flowers from the ground.
And things can get crazy in the forest.
Check out art from previous years: 2013 `\pi` Day and 2014 `\pi` Day, 2015 `\pi` Day, 2016 `\pi` Day, 2017 `\pi` Day, 2018 `\pi` Day and 2019 `\pi` Day.
All that glitters is not gold. —W. Shakespeare
The sensitivity and specificity of a test do not necessarily correspond to its error rate. This becomes critically important when testing for a rare condition — a test with 99% sensitivity and specificity has an even chance of being wrong when the condition prevalence is 1%.
We discuss the positive predictive value (PPV) and how practices such as screen can increase it.
Altman, N. & Krzywinski, M. (2021) Points of significance: Testing for rare conditions. Nature Methods 18:224–225.
We demand rigidly defined areas of doubt and uncertainty! —D. Adams
A popular notion about experiments is that it's good to keep variability in subjects low to limit the influence of confounding factors. This is called standardization.
Unfortunately, although standardization increases power, it can induce unrealistically low variability and lead to results that do not generalize to the population of interest. And, in fact, may be irreproducible.
Not paying attention to these details and thinking (or hoping) that standardization is always good is the "standardization fallacy". In this column, we look at how standardization can be balanced with heterogenization to avoid this thorny issue.
Voelkl, B., Würbel, H., Krzywinski, M. & Altman, N. (2021) Points of significance: Standardization fallacy. Nature Methods 18:5–6.
Clear, concise, legible and compelling.
Making a scientific graphical abstract? Refer to my practical design guidelines and redesign examples to improve organization, design and clarity of your graphical abstracts.
An in-depth look at my process of reacting to a bad figure — how I design a poster and tell data stories.