Rikke Schmidt KjÃ¦rgaard and Bang Wong. Cell 149: 1420â€“1421 (2012).
We’ve all done it—spent hours getting a figure just right for a paper, presentation, or grant application. We use tried and true compositions, standard depictions, and intuitive colors and then think to ourselves, this is how you do it. Or is it? ¶ A new guide by Felice C. Frankel and Angela H. DePace, Visual Strategies, eases the process of data presentation and enhances its effectiveness. If you seek inspiration and practical advice on how to craft more useful scientific graphics, this guide might be what you are looking for.
Samal, Lipika; Wright, Adam; Wong, Bang T.; Linder, Jeffrey A.; Bates, David W.
Informatics in Primary Care. 19 (2): 65-74 (2011).
The ageing population worldwide is increasingly acquiring multiple chronic diseases. The complex management of chronic diseases could be improved with electronic health records (EHRs) tailored to chronic disease care, but most EHRs in use today do not adequately support longitudinal data management. A key aspect of chronic disease management is that it takes place over long periods, but the way that most EHRs display longitudinal data makes it difficult to trend changes over time and slows providers as they review each patient’s unique course.
Cydney Nielsen & Bang Wong. Nature Methods 9, 521 (2012).
Techniques are at hand for taming the ever-growing number of data tracks.
Obtaining genome-scale data has never been easier. In addition to sequencing genomes, biologists now routinely profile epigenomes, transcriptomes and proteomes. There are exciting opportunities to better understand genome regulation by integrating diverse data types into unified views. Visualization facilitates data interpretation, but designing meaningful visual depictions of these data is a challenge.
Cydney Nielsen & Bang Wong. Nature Methods 9, 423 (2012).
The choice of visual representation of the linear genome is guided by the question being asked.
Many genomics techniques produce measurements that have both a value and a position on a reference genome. The genome coordinate provides a natural ordering to these data values and is the organizing principle driving how we commonly display and navigate genomic data today. A popular plotting approach is to arrange the linear genome coordinate along the x axis and express the data value range on the y axis (Fig. 1a). This conventional representation is limiting. By using other organizational frameworks we can better extract the information of interest and make sense of its patterns.
Nils Gehlenborg & Bang Wong. Nature Methods 9, 315 (2012).
Different analytical tasks require different visual representations.
Different data types have their own inherent structure that makes specific visualization techniques most fitting. For example, a matrix of gene expression values for given cell measurements can be highly informative when displayed as a heat map or parallel coordinate plot. The challenge is finding visualizations that will effectively combine data types. Many research studies depend on integrating data to comprehend underlying processes. Here we explore ways to merge data that are best represented as heat maps and node-link diagrams: two common but disparate graphing techniques.
Nils Gehlenborg & Bang Wong. Nature Methods 9, 213 (2012).
Heat maps are useful for visualizing multivariate data but must be applied properly.
Heat maps represent two-dimensional tables of numbers as shades of colors. This is a popular plotting technique in biology, used to depict gene expression and other multivariate data. The dense and intuitive display makes heat maps well-suited for presentation of high-throughput data. Hundreds of rows and columns can be displayed on a screen. Heat maps rely fundamentally on color encoding and on meaningful reordering of the rows and columns. When either of these components is compromised, the utility of the visualization suffers.
Nils Gehlenborg & Bang Wong. Nature Methods 9, 115 (2012).
We describe graphing techniques to support exploration of networks.
Most biological phenomena arise from the complex interactions between the cell’s many constituents such as proteins, DNA, RNA and small molecules. The graphical representations of networks can be useful in exploring this complex web of interactions. Choosing a suitable network visualization based on the patterns one hopes to highlight can yield meaningful insights into data.
Noam Shoresh and Bang Wong. Nature Methods 9, 5 (2012).
Enhancement of pattern discovery through graphical representation of data.
Data visualization can serve two distinct purposes: to communicate research findings and to guide the data-exploration process as the scientific story is unfolding. Each goal entails a different approach to data representation, but sound graphic design principles are important in both. This column is the first in a series that will focus on data-visualization techniques intended to support data exploration.
Bang Wong. Nature Methods 8, 987 (2011).
The primary tenets of design are utility and function. Just as objects are intuitive to use when they are well-designed, thoughtfully conceived scientific figures, slides and posters can be easy to interpret and understand. Whereas industrial design focuses on things people use, graphic design is concerned with designs people read. The design process helps us develop a visual literacy to construct presentations that are appealing and convincing.
Bang Wong. Nature Methods 8, 889 (2011).
In science communication, it is critical that visual information be interpreted efficiently and correctly. The discordance between components of an image that are most noticeable and those that are most relevant or important can compromise the effectiveness of a presentation. This discrepancy can cause viewers to mistakenly pay attention to regions of the image that are not relevant. Ultimately, the misdirected attention can negatively impact comprehension.