Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - contact me Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca on Twitter Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Lumondo Photography Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Pi Art Martin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Hilbertonians - Creatures on the Hilbert CurveMartin Krzywinski / Canada's Michael Smith Genome Sciences Centre / mkweb.bcgsc.ca - Pi Day 2020 - Piku
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ellipses: layered


Scientific graphical abstracts — design guidelines


data visualization + art
The Personal OncoGenomics Program (POG) is a research initiative to study the impact of embedding genomic sequencing into real-time treatment planning for BC patients with metastatic cancers. Based out of the BC Cancer Research Centre and the GSC, POG is a large world-class clinical research collaboration of BC Cancer oncologists, pathologists and other clinical staff, researchers and technical personnel throughout BC healthcare facilities.
Interested in more art based on the POG570 cohort from the Personal OncoGenomics Program? Check out our 5-year POG anniversary posters and desktops.

Nature Cancer Cover — April 2020 issue

Pan-cancer genomic landscapes of advanced tumors after therapy

Pleasance, E., Titmuss, E., Williamson, L. et al. (2020) Pan-cancer analysis of advanced patient tumors reveals interactions between therapy and genomic landscapes. Nat Cancer 1:452–468.

Art is science in love.
— E.F. Weisslitz

4k desktops

Download all desktops.

The legend at the bottom of the desktop provides credits and reads

Mutation spectra of patients from the POG570 cohort of 570 individuals with advanced metastatic cancer.
Each ellipse system represents the mutation spectrum of an individual patient. Individual ellipses in the system correspond to the number of base changes in a given class and are layered by mutation count. Ellipse angle is controlled by the proportion of mutations in a class within the sample and its size is determined by a sigmoid mapping of mutation count scaled within the layer. The opacity of each system represents the duration since the diagnosis of advanced disease.

The desktop show all the 570 mutation spectra. Cases are sorted in chronological order of time of enrollment, with the oldest case first to the most recent, which is shown last. This is the reverse order to what is shown on the poster.

The last set of desktops is a remix of randomly placed ellipses. For those with visually insatiable appetites.

Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Design of the Nature Cancer April 2020 cover accompanying Pan-cancer genomic landscapes of advanced tumors after therapy. (4k resolution)

random remixes

Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Random remix of the design. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Random remix of the design. (4k resolution)
Martin Krzywinski / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Random remix of the design. (4k resolution)

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news + thoughts

Graphical Abstract Design Guidelines

Fri 13-11-2020

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.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Graphical Abstract Design Guidelines — Clear, concise, legible and compelling.

"This data might give you a migrane"

Tue 06-10-2020

An in-depth look at my process of reacting to a bad figure — how I design a poster and tell data stories.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A poster of high BMI and obesity prevalence for 185 countries.

He said, he said — a word analysis of the 2020 Presidential Debates

Thu 01-10-2020

Building on the method I used to analyze the 2008, 2012 and 2016 U.S. Presidential and Vice Presidential debates, I explore word usagein the 2020 Debates between Donald Trump and Joe Biden.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Analysis of word usage by parts of speech for Trump and Biden reveals insight into each candidate.

Points of Significance celebrates 50th column

Mon 24-08-2020

We are celebrating the publication of our 50th column!

To all our coauthors — thank you and see you in the next column!

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance: Celebrating 50 columns of clear explanations of statistics. (read)

Uncertainty and the management of epidemics

Mon 24-08-2020

When modelling epidemics, some uncertainties matter more than others.

Public health policy is always hampered by uncertainty. During a novel outbreak, nearly everything will be uncertain: the mode of transmission, the duration and population variability of latency, infection and protective immunity and, critically, whether the outbreak will fade out or turn into a major epidemic.

The uncertainty may be structural (which model?), parametric (what is `R_0`?), and/or operational (how well do masks work?).

This month, we continue our exploration of epidemiological models and look at how uncertainty affects forecasts of disease dynamics and optimization of intervention strategies.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Uncertainty and the management of epidemics. (read)

We show how the impact of the uncertainty on any choice in strategy can be expressed using the Expected Value of Perfect Information (EVPI), which is the potential improvement in outcomes that could be obtained if the uncertainty is resolved before making a decision on the intervention strategy. In other words, by how much could we potentially increase effectiveness of our choice (e.g. lowering total disease burden) if we knew which model best reflects reality?

This column has an interactive supplemental component (download code) that allows you to explore the impact of uncertainty in `R_0` and immunity duration on timing and size of epidemic waves and the total burden of the outbreak and calculate EVPI for various outbreak models and scenarios.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Uncertainty and the management of epidemics. (Interactive supplemental materials)

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Uncertainty and the management of epidemics. Nature Methods 17.

Background reading

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Modeling infectious epidemics. Nature Methods 17:455–456.

Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: The SEIRS model for infectious disease dynamics. Nature Methods 17:557–558.