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The Outbreak Poems — artistic emissions in a pandemic


statistics + data

Nature Methods: Points of Significance

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Points of Significance column in Nature Methods. (Launch of Points of Significance)

Access all columns for free at Statistics for Biologists Nature Collection.

A Statistics Primer and Best Practices

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

The column is co-authored with Naomi Altman (Pennsylvania State University). Paul Blainey (Broad) is a contributing co-author.

Free Access

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

Also, in a recent post on the ofschemesandmemes blog, a new statistics collection for biologists was announced.

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

continuity and consistency

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.

VIEW ALL

news + thoughts

Virus Mutations Reveal How COVID-19 Really Spread

Mon 04-05-2020

Genetic sequences of the coronavirus tell story of when the virus arrived in each country and where it came from.

Our graphic in Scientific American's Graphic Science section in the June 2020 issue shows a phylogenetic tree based on a snapshot of the data model from Nextstrain as of 31 March 2020.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Virus Mutations Reveal How COVID-19 Really Spread. Text by Mark Fischetti (Senior Editor), art direction by Jen Christiansen (Senior Graphics Editor), source: Nextstrain (enabled by data from GISAID).

Cover of Nature Cancer April 2020

Mon 27-04-2020

Our design on the cover of Nature Cancer's April 2020 issue shows mutation spectra of patients from the POG570 cohort of 570 individuals with advanced metastatic cancer.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
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. (read more)

The cover design accompanies our report in the issue 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.

Modeling infectious epidemics

Wed 06-05-2020

Every day sadder and sadder news of its increase. In the City died this week 7496; and of them, 6102 of the plague. But it is feared that the true number of the dead this week is near 10,000 ....
—Samuel Pepys, 1665

This month, we begin a series of columns on epidemiological models. We start with the basic SIR model, which models the spread of an infection between three groups in a population: susceptible, infected and recovered.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Modeling infectious epidemics. (read)

We discuss conditions under which an outbreak occurs, estimates of spread characteristics and the effects that mitigation can play on disease trajectories. We show the trends that arise when "flattenting the curve" by decreasing `R_0`.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Modeling infectious epidemics. (read)

This column has an interactive supplemental component that allows you to explore how the model curves change with parameters such as infectious period, basic reproduction number and vaccination level.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Modeling infectious epidemics. (Interactive supplemental materials)

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

The Outbreak Poems

Sat 04-04-2020

I'm writing poetry daily to put my feelings into words more often during the COVID-19 outbreak.

That moment
when
you know a moment.
Branch to branch,
flit,
look everywhere,
chirp.
Memory,
scent
of thought fleeting.
Distant pasts
all
ways in plural
form.

Read the poems and learn what a piku is.

Deadly Genomes: Genome Structure and Size of Harmful Bacteria and Viruses

Tue 17-03-2020

A poster full of epidemiological worry and statistics. Now updated with the genome of SARS-CoV-2 and COVID-19 case statistics as of 3 March 2020.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Deadly Genomes: Genome Structure and Size of Harmful Bacteria and Viruses (zoom)

Bacterial and viral genomes of various diseases are drawn as paths with color encoding local GC content and curvature encoding local repeat content. Position of the genome encodes prevalence and mortality rate.

The deadly genomes collection has been updated with a posters of the genomes of SARS-CoV-2, the novel coronavirus that causes COVID-19.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Genomes of 56 SARS-CoV-2 coronaviruses that causes COVID-19.
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Ball of 56 SARS-CoV-2 coronaviruses that causes COVID-19.
Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
The first SARS-CoV-2 genome (MT019529) to be sequenced appears first on the poster.

Using Circos in Galaxy Australia Workshop

Wed 04-03-2020

A workshop in using the Circos Galaxy wrapper by Hiltemann and Rasche. Event organized by Australian Biocommons.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Using Circos in Galaxy Australia workshop. (zoom)

Download workshop slides.

Galaxy wrapper training materials, Saskia Hiltemann, Helena Rasche, 2020 Visualisation with Circos (Galaxy Training Materials).

Essence of Data Visualization in Bioinformatics Webinar

Thu 20-02-2020

My webinar on fundamental concepts in data visualization and visual communication of scientific data and concepts. Event organized by Australian Biocommons.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Essence of Data Visualization in Bioinformatics webinar. (zoom)

Download webinar slides.

Markov models — training and evaluation of hidden Markov models

Thu 20-02-2020

With one eye you are looking at the outside world, while with the other you are looking within yourself.
—Amedeo Modigliani

Following up with our Markov Chain column and Hidden Markov model column, this month we look at how Markov models are trained using the example of biased coin.

We introduce the concepts of forward and backward probabilities and explicitly show how they are calculated in the training process using the Baum-Welch algorithm. We also discuss the value of ensemble models and the use of pseudocounts for cases where rare observations are expected but not necessarily seen.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Markov models — training and evaluation of hidden Markov models. (read)

Grewal, J., Krzywinski, M. & Altman, N. (2019) Points of significance: Markov models — training and evaluation of hidden Markov models. Nature Methods 17:121–122.

Background reading

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

Altman, N. & Krzywinski, M. (2019) Points of significance: Markov Chains. Nature Methods 16:663–664.