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With the publication of Uncertainty and the Management of Epidemics, we celebrate our 50th column! Since 2013, our Nature Methods Points of Significance has been offering crisp explanations and practical suggestions about best practices in statistical analysis and reporting. To all our readers and coauthors: thank you and see you in the next column!

Nature Methods: Points of View

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Points of View column in Nature Methods. (Points of View)
1 | Krzywinski M 2016 Intuitive design Nat Methods 13:895.
2 | Krzywinski M 2016 Binning high-resolution data Nat Methods 13:463.
3 | Hunnicutt BJ & Krzywinski M 2016 Neural circuit diagrams Nat Methods 13:189.
4 | Hunnicutt BJ & Krzywinski M 2016 Pathways Nat Methods 13:5.
5 | McInerny G & Krzywinski M 2015 Unentangling complex plots Nat Methods 12:591.
6 | Streit M & Gehlenborg N 2015 Temporal Data Nat Methods 12:97.
7 | Lex A & Gehlenborg N 2014 Sets and Intersections Nat Methods 11:778.
8 | Streit M & Gehlenborg N 2014 Bar charts and box plots Nat Methods 11:117.
9 | Krzywinski M & Cairo A 2013 Storytelling Nat Methods 10:687.
10 | Krzywinski M & Savig E 2013 Multidimensional Data Nat Methods 10:595.
11 | Krzywinski M & Wong B 2013 Plotting symbols Nat Methods 10:451.
12 | Krzywinski M 2013 Elements of visual style Nat Methods 10:371.
13 | Krzywinski M 2013 Labels and callouts Nat Methods 10:275.
14 | Krzywinski M 2013 Axes, ticks and grids Nat Methods 10:183.
15 | Wong B 2012 Visualizing biological data Nat Methods 9:1131.
16 | Wong B & Kjaegaard RS 2012 Pencil and paper Nat Methods 9:1037.
17 | Gehlenborg N & Wong B 2012 Power of the plane Nat Methods 9:935.
18 | Gehlenborg N & Wong B 2012 Into the third dimension Nat Methods 9:851.
19 | Gehlenborg N & Wong B 2012 Mapping quantitative data to color Nat Methods 9:769.
20 | Nielsen C & Wong B 2012 Representing genomic structural variation Nat Methods 9:631.
21 | Nielsen C & Wong B 2012 Managing deep data in genome browsers Nat Methods 9:521.
22 | Nielsen C & Wong B 2012 Representing the genome Nat Methods 9:423.
23 | Gehlenborg N & Wong B 2012 Integrating data Nat Methods 9:315.
24 | Gehlenborg N & Wong B 2012 Heat maps Nat Methods 9:213.
25 | Gehlenborg N & Wong B 2012 Networks Nat Methods 9:115.
26 | Shoresh N & Wong B 2012 Data exploration Nat Methods 9:5.
27 | Wong B 2011 The design process Nat Methods 8:987.
28 | Wong B 2011 Salience to relevance Nat Methods 8:889.
29 | Wong B 2011 Layout Nat Methods 8:783.
30 | Wong B 2011 Arrows Nat Methods 8:701.
31 | Wong B 2011 Simplify to clarify Nat Methods 8:611.
32 | Wong B 2011 Avoiding color Nat Methods 8:525.
33 | Wong B 2011 Color blindness Nat Methods 8:441.
34 | Wong B 2011 The overview figure Nat Methods 8:365.
35 | Wong B 2011 Typography Nat Methods 8:277.
36 | Wong B 2011 Points of review (part 2) Nat Methods 8:189.
37 | Wong B 2011 Points of review (part 1) Nat Methods 8:101.
38 | Wong B 2011 Negative space Nat Methods 8:5.
39 | Wong B 2010 Gestalt principles (part 2) Nat Methods 7:941.
40 | Wong B 2010 Gestalt principles (part 1) Nat Methods 7:863.
41 | Wong B 2010 Salience Nat Methods 7:773.
42 | Wong B 2010 Design of data figures Nat Methods 7:665.
43 | Wong B 2010 Color coding Nat Methods 7:573.
news + thoughts

Propensity score weighting

Mon 17-03-2025

The needs of the many outweigh the needs of the few. —Mr. Spock (Star Trek II)

This month, we explore a related and powerful technique to address bias: propensity score weighting (PSW), which applies weights to each subject instead of matching (or discarding) them.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Propensity score weighting. (read)

Kurz, C.F., Krzywinski, M. & Altman, N. (2025) Points of significance: Propensity score weighting. Nat. Methods 22:1–3.

Happy 2025 π Day—
TTCAGT: a sequence of digits

Thu 13-03-2025

Celebrate π Day (March 14th) and sequence digits like its 1999. Let's call some peaks.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2025 π DAY | TTCAGT: a sequence of digits. The digits of π are encoded into DNA sequence and visualized with Sanger sequencing. (details)

Crafting 10 Years of Statistics Explanations: Points of Significance

Sun 09-03-2025

I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player

Points of Significance is an ongoing series of short articles about statistics in Nature Methods that started in 2013. Its aim is to provide clear explanations of essential concepts in statistics for a nonspecialist audience. The articles favor heuristic explanations and make extensive use of simulated examples and graphical explanations, while maintaining mathematical rigor.

Topics range from basic, but often misunderstood, such as uncertainty and P-values, to relatively advanced, but often neglected, such as the error-in-variables problem and the curse of dimensionality. More recent articles have focused on timely topics such as modeling of epidemics, machine learning, and neural networks.

In this article, we discuss the evolution of topics and details behind some of the story arcs, our approach to crafting statistical explanations and narratives, and our use of figures and numerical simulations as props for building understanding.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Crafting 10 Years of Statistics Explanations: Points of Significance. (read)

Altman, N. & Krzywinski, M. (2025) Crafting 10 Years of Statistics Explanations: Points of Significance. Annual Review of Statistics and Its Application 12:69–87.

Propensity score matching

Mon 16-09-2024

I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player

In many experimental designs, we need to keep in mind the possibility of confounding variables, which may give rise to bias in the estimate of the treatment effect.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Propensity score matching. (read)

If the control and experimental groups aren't matched (or, roughly, similar enough), this bias can arise.

Sometimes this can be dealt with by randomizing, which on average can balance this effect out. When randomization is not possible, propensity score matching is an excellent strategy to match control and experimental groups.

Kurz, C.F., Krzywinski, M. & Altman, N. (2024) Points of significance: Propensity score matching. Nat. Methods 21:1770–1772.

Martin Krzywinski | contact | Canada's Michael Smith Genome Sciences CentreBC Cancer Research CenterBC CancerPHSA
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