The Points of Significance column was launched in September 2013 as an educational resource to authors and to provide practical suggestions about best practices in statistical analysis and reporting.
This month we launch a new column "Points of Significance" devoted to statistics, a topic of profound importance for biological research, but one that often doesn’t receive the attention it deserves.
The "aura of exactitude" that often surrounds statistics is one of the main notions that the Points of Significance column will attempt to dispel, while providing useful pointers on using and evaluating statistical measures.
—Dan Evanko, Let's Give Statistics the Attention it Deserves in Biological Research
In February 2015, Nature Methods announced that the entire Points of Significance collection will be free.
When Nature Methods launched the Points of Significance column over a year ago we were hopeful that those biologists with a limited background in statistics, or who just needed a refresher, would find it accessible and useful for helping them improve the statistical rigor of their research. We have since received comments from researchers and educators in fields ranging from biology to meteorology who say they read the column regularly and use it in their courses. Hearing that the column has had a wider impact than we anticipated has been very encouraging and we hope the column continues for quite some time.
—Dan Evanko, Points of Significance now free access
The pieces range from comments, to advice on very specific experimental approaches, to the entire collection of the Points of Significance columns that address basic concepts in statistics in an experimental biology context. These columns, originally published in Nature Methods thanks to Martin Krzywinski and guest editor Naomi Altman, have already proven very popular with readers and teachers. Finally, the collection presents a web tool to create box plots among other resources.
—Veronique Kiermer, Statistics for biologists—A free Nature Collection
Each column is written with continuity and consistency in mind. Our goal is to never rely on concepts that we have not previously discussed. We do not assume previous statistical knowledge—only basic math. Concepts are illustrated using practical examples that embody the ideas without extraneous complicated details. All of the figures are designed with the same approach—as simple and self-contained as possible.
We focus on the important distinction between confidence intervals, typically used to express uncertainty of a sampling statistic such as the mean and, prediction and tolerance intervals, used to make statements about the next value to be drawn from the population.
Confidence intervals provide coverage of a single point—the population mean—with the assurance that the probability of non-coverage is some acceptable value (e.g. 0.05). On the other hand, prediction and tolerance intervals both give information about typical values from the population and the percentage of the population expected to be in the interval. For example, a tolerance interval can be configured to tell us what fraction of sampled values (e.g. 95%) will fall into an interval some fraction of the time (e.g. 95%).
Altman, N. & Krzywinski, M. (2018) Points of significance: Predicting with confidence and tolerance Nature Methods 15:843–844.
Krzywinski, M. & Altman, N. (2013) Points of significance: Importance of being uncertain. Nature Methods 10:809–810.
A 4-day introductory course on genome data parsing and visualization using Circos. Prepared for the Bioinformatics and Genome Analysis course in Institut Pasteur Tunis, Tunis, Tunisia.
Data visualization should be informative and, where possible, tasty.
Stefan Reuscher from Bioscience and Biotechnology Center at Nagoya University celebrates a publication with a Circos cake.
The cake shows an overview of a de-novo assembled genome of a wild rice species Oryza longistaminata.
The presence of constraints in experiments, such as sample size restrictions, awkward blocking or disallowed treatment combinations may make using classical designs very difficult or impossible.
Optimal design is a powerful, general purpose alternative for high quality, statistically grounded designs under nonstandard conditions.
We discuss two types of optimal designs (D-optimal and I-optimal) and show how it can be applied to a scenario with sample size and blocking constraints.
Smucker, B., Krzywinski, M. & Altman, N. (2018) Points of significance: Optimal experimental design Nature Methods 15:599–600.
Krzywinski, M., Altman, N. (2014) Points of significance: Two factor designs. Nature Methods 11:1187–1188.
Krzywinski, M. & Altman, N. (2014) Points of significance: Analysis of variance (ANOVA) and blocking. Nature Methods 11:699–700.
Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments. Nature Methods 11:597–598.
An illustration of the Tree of Life, showing some of the key branches.
The tree is drawn as a DNA double helix, with bases colored to encode ribosomal RNA genes from various organisms on the tree.
All living things on earth descended from a single organism called LUCA (last universal common ancestor) and inherited LUCA’s genetic code for basic biological functions, such as translating DNA and creating proteins. Constant genetic mutations shuffled and altered this inheritance and added new genetic material—a process that created the diversity of life we see today. The “tree of life” organizes all organisms based on the extent of shuffling and alteration between them. The full tree has millions of branches and every living organism has its own place at one of the leaves in the tree. The simplified tree shown here depicts all three kingdoms of life: bacteria, archaebacteria and eukaryota. For some organisms a grey bar shows when they first appeared in the tree in millions of years (Ma). The double helix winding around the tree encodes highly conserved ribosomal RNA genes from various organisms.
Johnson, H.L. (2018) The Whole Earth Cataloguer, Sactown, Jun/Jul, p. 89
An article about keyboard layouts and the history and persistence of QWERTY.
McDonald, T. (2018) Why we can't give up this odd way of typing, BBC, 25 May 2018.
I've previously taken a more fine-art approach to cover design, such for those of Nature, Genome Research and Trends in Genetics. I've used microscopy images to create a cover for PNAS—the one that made biology look like astrophysics—and thought that this is kind of material I'd start with for the MCS cover.