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The Nature Methods Points of View column column offers practical advice in design and data presentation for the busy scientist.

50+ columns of good explanations ·

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 Significance

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca

▲ Points of Significance column in Nature Methods. (Launch of Points of Significance)

menu authors figures bibliography

57 | Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20.

56 | Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modelling of time-to-event data with censoring. Nature Methods 19:1513–1515.

55 | Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Survival analysis — time-to-event data and censoring. Nature Methods 19:906–908.

54 | Megahed, F.M, Chen, Y-J., Megahed, A., Ong, Y., Altman, N. & Krzywinski, M. (2021) Points of significance: The class imbalance problem. Nature Methods 18:1270–1272.

53 | Altman, N. & Krzywinski, M (2021) Points of significance: Graphical assessments of tests and classifiers. Nature Methods 18:840–842

52 | Altman, N. & Krzywinski, M (2021) Points of significance: Testing for rare conditions. Nature Methods 18:224–225.

51 | Voelkl, B., Würbel, H., Krzywinski, M. & Altman, N. (2021) Points of significance: The standardization fallacy. Nature Methods 18:5–7.

50 | Bjørnstad, O.N., Shea, K., Krzywinski, M. & Altman, N. (2020) Points of significance: Uncertainty and the management of epidemics. Nature Methods 17:867–868.

49 | 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.

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

47 | Grewal, J., Krzywinski, M. & Altman, N. (2020) Points of significance: Markov models — training and evaluation of hidden Markov models. Nature Methods 17:121–122.

46 | Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Hidden Markov models. Nature Methods 16:795–796.

45 | Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov chains. Nature Methods 16:663–664.

44 | Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. Nature Methods 16:451–452.

43 | Greco, L., Luta, G., Krzywinski, M. & Altman, N. (2019) Points of significance: Analyzing outliers: Robust methods to the rescue. Nature Methods 16:275–276.

42 | Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments Nature Methods 16:211–212.

41 | Altman, N. & Krzywinski, M. (2018) Points of significance: Predicting with confidence and tolerance Nature Methods 15:843–844.

40 | Smucker, B., Krzywinski, M. & Altman, N. (2018) Points of significance: Optimal experimental design Nature Methods 15:559–560.

39 | Altman, N. & Krzywinski, M. (2018) Points of significance: Curse(s) of dimensionality Nature Methods 15:299–400.

38 | Bzdok, D., Krzywinski, M. & Altman, N. (2018) Points of significance: Statistics vs machine learning. Nature Methods 15:233–234.

37 | Bzdok, D., Krzywinski, M. & Altman, N. (2018) Points of significance: Machine learning: supervised methods. Nature Methods 15:5–6.

36 | Bzdok, D., Krzywinski, M. & Altman, N. (2017) Points of significance: Machine learning: a primer. Nature Methods 14:1119–1120.

35 | Altman, N. & Krzywinski, M. (2017) Points of significance: Ensemble methods: Bagging and random forests. Nature Methods 14:933–934.

34 | Krzywinski, M. & Altman, N. (2017) Points of significance: Classification and regression trees. Nature Methods 14:757–758.

33 | Lever, J., Krzywinski, M. & Altman, N. (2017) Points of significance: Principal component analysis. Nature Methods 14:641–642.

32 | Altman, N. & Krzywinski, M. (2017) Points of significance: Clustering. Nature Methods 14:545–546.

31 | Altman, N. & Krzywinski, M. (2017) Points of significance: Tabular data. Nature Methods 14:329–330.

30 | Altman, N. & Krzywinski, M. (2017) Points of significance: Interpreting P values. Nature Methods 14:213–214.

29 | Altman, N. & Krzywinski, M. (2017) Points of significance: P values and the search for significance. Nature Methods 14:3–4.

28 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Regularization. Nature Methods 13:803–804.

27 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Model selection and overfitting. Nature Methods 13:703–704.

26 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Classifier evaluation. Nature Methods 13:603–604.

25 | Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.

24 | Altman, N. & Krzywinski, M. (2016) Points of significance: Regression diagnostics. Nature Methods 13:385–386.

23 | Altman, N. & Krzywinski, M. (2016) Points of significance: Analyzing outliers: Influential or nuisance. Nature Methods 13:281–282.

22 | Krzywinski, M. & Altman, N. (2015) Points of significance: Multiple linear regression. Nature Methods 12:1103–1104.

21 | Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. Nature Methods 12:999–1000.

20 | Altman, N. & Krzywinski, M. (2015) Points of significance: Association, correlation and causation. Nature Methods 12:899–900.

19 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayesian networks. Nature Methods 12:799–800.

18 | Kulesa, A., Krzywinski, M., Blainey, P. & Altman, N. (2015) Points of significance: Sampling distributions and the bootstrap. Nature Methods 12:477–478.

17 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayesian statistics. Nature Methods 12:277–278.

16 | Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of significance: Bayes' theorem. Nature Methods 12:277–278.

15 | Altman, N. & Krzywinski, M. (2015) Points of significance: Split plot design. Nature Methods 12:165–166.

14 | Altman, N. & Krzywinski, M. (2015) Points of significance: Sources of variation. Nature Methods 12:5–6.

13 | Krzywinski, M., Altman, N. (2014) Points of significance: Two factor designs. Nature Methods 11:1187–1188.

12 | Krzywinski, M., Altman, N. & Blainey, P. (2014) Points of significance: Nested designs. Nature Methods 11:977–978.

11 | Blainey, P., Krzywinski, M. & Altman, N. (2014) Points of significance: Replication. Nature Methods 11:879–880.

10 | Krzywinski, M. & Altman, N. (2014) Points of significance: Analysis of variance (ANOVA) and blocking. Nature Methods 11:699–700.

9 | Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments. Nature Methods 11:597–598.

8 | Krzywinski, M. & Altman, N. (2014) Points of significance: Non-parametric tests. Nature Methods 11:467–468.

7 | Krzywinski, M. & Altman, N. (2014) Points of significance: Comparing samples — Part II — Multiple testing. Nature Methods 11:355–356.

6 | Krzywinski, M. & Altman, N. (2014) Points of significance: Comparing samples — Part I — t–tests. Nature Methods 11:215–216.

5 | Krzywinski, M. & Altman, N. (2014) Points of significance: Visualizing samples with box plots. Nature Methods 11:119–120.

4 | Krzywinski, M. & Altman, N. (2013) Points of significance: Power and sample size. Nature Methods 10:1139–1140.

3 | Krzywinski, M. & Altman, N. (2013) Points of significance: Significance, P values and t–tests. Nature Methods 10:1041–1042.

2 | Krzywinski, M. & Altman, N. (2013) Points of significance: Error bars. Nature Methods 10:921–922.

1 | Krzywinski, M. & Altman, N. (2013) Points of significance: Importance of being uncertain. Nature Methods 10:809–810.

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news + thoughts

Neural network primer

Mon 06-02-2023

Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon

In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.

▲ Nature Methods Points of Significance column: Neural network primer. (read)

Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.

We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.

Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20.

Background reading

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.

Cell Genomics cover

Mon 16-01-2023

Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.

Designed in collaboration with with Carlos Urzua.

▲ Our Cell Genomics cover depicts parent-of-origin assignment as a circuit (volume 3, issue 1, 11 January 2023). (more)

Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).

Browse my gallery of cover designs.

▲ A catalogue of my journal and magazine cover designs. (more)

Science Advances cover

Thu 05-01-2023

My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.

More details about the design.

▲ My Science Advances cover that encodes sequence onto hypercubes (volume 9, issue 1, 6 January 2023). (more)

Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.

Browse my gallery of cover designs.

▲ A catalogue of my journal and magazine cover designs. (more)

Regression modeling of time-to-event data with censoring

Mon 21-11-2022

If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber

In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.

We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).

▲ Nature Methods Points of Significance column: Regression modeling of time-to-event data with censoring. (read)

Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19.