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Displaying posts with the tag: dataviz [Clear Filter]

Data Visualization with Flying Colors

Posted by on August 29th, 2019

The importance of barrier-free use of colors in images and graphs has been highlighted in letters to editors (Miall, 2007), papers (Geissbuehler and Lasser, 2013, Levine, 2009), editorials (anonymous, 2007), columns (Wong, 2011) and on numerous web pages. One of the recommendations is to use a color blindness simulator. Having a color vision deficiency myself,[…]

Data manipulation? It’s normal(ization)!

Posted by on June 25th, 2019

In a previous blog, I have highlighted several ways to visualize the cell-to-cell heterogeneity from time-lapse imaging data. However, I have ignored that data is often rescaled in a way that reduces variability. For time-lapse imaging data, it is common to set the initial fluorescence intensity to 1 (or 100%). As a consequence, any changes[…]

Non-zero baselines: the good, the bad, and the ugly

Posted by on June 20th, 2019

Of all the charts being ridiculed at WTFviz, many get shamed for their lack of a zero-baseline. When teaching DataViz, zero-baselines are invariably a topic of debate. The rules about zero baselines are necessary are often unclear. Therefore, let’s quickly recap. Bar charts: always show zero When we ecnode amounts by length, as done in[…]

Visualizing the heterogeneity of single cell data from time-lapse imaging

Posted by on December 12th, 2018

When we examined the kinetics of Rho GTPase activity in endothelial cells in response to receptor stimulation (Reinhard, 2017), we noticed considerable cell-to-cell heterogeneity. In the original work we published graphs with the average response, reflecting the response of the whole cell population. However, these graphs fail to show the cellular heterogeneity. What is the[…]

Make a difference: the alternative for p-values

Posted by on October 8th, 2018

Calculation and reporting of p-values is common in scientific publications and presentations (Cristea and Ioannidis, 2018). Usually, the p-value is calculated to decide whether two conditions, e.g. control and treatment, are different. Although a p-value can flag differences, it cannot quantify the difference itself (footnote 1). Therefore, p-values fail to answer a very relevant question:[…]

Visualizing data with R/ggplot2 – One more time

Posted by on June 26th, 2018

Experiments are rarely performed in isolation. Usually, several conditions are compared in parallel or sequential experiments. This experimental strategy also applies to time-dependent data, e.g. from timelapse imaging. So, naturally, after I published a ‘walk-through for plotting temporal data using R and ggplot2, I was immediately asked how to plot two (or more) sets of[…]

Visualizing data with R/ggplot2 – It’s about time

Posted by on May 31st, 2018

The visualization of temporal data by line graphs has been documented and popularized by William Playfair in the 18th century (Aigner et al, 2011; Beniger and Robyn, 1978). Today, time-dependent changes are still depicted by line graphs and ideally accompanied by a measure of uncertainty (Marx, 2013). Below, I provide a ‘walk-through’ for generating such a[…]

How to win a conference prize

Posted by on December 11th, 2017

Or, at least, produce nice posters while trying. Students on average author 1-3 papers and produce at least three times that many conference posters***. At large meetings, such as the ASCB, thousands of posters are presented each year. While presenting posters is popular, posters sessions evoke mixed feelings: they are often late in the evening,[…]

Color-blind people are your audience too!

Posted by on April 27th, 2017

Or, please stop mixing green/red Color is a key aspect of graphic design, but for many years was not relevant for scientific figures that were largely black and white. Falling prices for color print and electronic publishing changed this dramatically and scientists now frequently produce multi-colored figures. Using color functionally is not always straightforward but[…]

Leaving the bar in five steps

Posted by on March 24th, 2017

Introduction Graphs (or charts or plots) are often used for the display and summary of data. They are essential tools for the communication of results in presentations or manuscripts. One particular type of graph, the bar graph, is often used to quantitatively compare (multiple) conditions. The earliest known example of a bar graph, dates from[…]