Tag: visualizing biological data

By guest blogger, Helena Jambor, PhD, TU Dresden, @helenajambor

10 years after it all started, VIZBI came back to its original stomping grounds, the ATC at EMBL in Heidelberg. As its name suggests, VIZBI “Visualizing Biological Data”  is a blend of several worlds. Of biology, with its long history in visualizations that goes back to Ancient Greek text books, and of art and scientific illustration.

VIZBI is also inseparable from computer science and its tools to transform big data into human readable entities. And finally, VIZBI incorporates concepts of design and visual perception to make visualizations engaging and enlightening.

Highlighting spectacular biological images

At VIZBI 2010, microscopic images were omnipresent. Back then, I was embarking on my postdoc project, a large-scale microscopy screen of RNAs in cells. My memories tell me that this was the main focus of the conference. Indeed, a quick check of the 2010 program confirms that almost the entire community of light sheet microscopy and image processing were in attendance at the first ever event.

VIZBI 2019 continued to highlight spectacular biological images. A phenomenal augmented reality installation showed them in 3D, EM-tomography simulations by Peijun Zhang animated the 64-million atoms assembling into HIV particles, and Lucy Collinson shared the high numbers of high-resolution EM data collected at the Francis Crick Institute. This large amount of data is annotated with the help of amateurs, for example in their citizen science project at the Zooniverse “Etch a cell”.

Colourful confocal images or images of tissues also provided the inspiration to many works of illustrators on display that combined science and art, for example the double win of best poster and best art to a depiction of tubulin in a mitotic spindle by Beata Mierzwa @beatascienceart, a hugely talented artist and scientist (who also sells cool cytoskeleton-printed leggings and mini-brain organoid dresses).

Data visualization

At VIZBI 2019, visualizations of data – as opposed to images – gained a much more prominent spot. All keynote speakers were from the technology side. Hadley Wickham presented the history of ggplot2. Ggplot2 (and yes, there once was a ggplot1!) is the R universe for visualizing pretty much everything that comes in numbers and is now merged into the tidyverse. Being a visualization talk, all slides were themselves beautiful, I love the tidyverse playfully represented as stars of our universe! The second keynote was by Janet Iwasa who presented her animation work that heavily relies on 3D and computer graphics software used for animation films. Instead of earning her money in the film industry, she decided to put it to good use for biology. Janet first used her skills in her PhD project to visualize motor proteins “walking” along the cytoskeleton, and these days produces Oscar^®-worthy movies showing biology, such as the origin of life or the life cycle of HIV. And everyone take note: all her films start as a storyboard on paper, which is what I teach as good practice for all visualization designs.

Making the invisible visible

The third keynote was by Moritz Stefaner, a data designer who is enticed by biological data but appalled by the time-scales in biological projects (too long!). Luckily, he hasn’t given up on us just yet, and keeps producing phenomenal visualizations. For example, showing absence and loss is notoriously hard, but Moritz found a beautiful way to make the invisible visible in his designs for “Where the wild bees are” with Ferris Jabr for Scientific American.

Moritz left us hungry for more when also showing his data-cuisine project, that visualizes data about food and turns food into data: the number of berries picked in Finland become a layered dessert, and common causes of death are encoded as praline fillings – you never know which one you’ll get! (Luckily this was with Belgium pralines, so all deaths are sweet.)

Feedback wanted!

Visualizations of data were in the spotlight of many other projects too. This is of course owed to the many possibilities of large-scale methods that swamped biology with data in recent years: RNAseq, inexpensive genome sequencing, mass-spec at fantastic scales, robotics driven biochemistry and medicine, image processing that turns images into insights by quantifying signals and so on. RNA sequencing, for example, fuelled Susan Clark’s project tracing methylations in cancer, Phillippe Collas’ ambitious endeavour to understand 3D genome architecture, and is empowered by Charlotte Soneson’s “iSEE” software to interactively analyse data from high throughput experiments and the project of Kirsten Bos tracing human pathogens back thousands of years by sequencing tiny dental samples. And of course, of the biggest data projects in biology is the ENSEMBL genome browser, which was officially released as pre-alpha version VIZBI (check it out: 2020.ensembl.org), the very approachable Andy Yates and his team are looking for feedback!

Technical Challenges

Visualizations of high-dimensional datasets are not without problems. The technical challenges were addressed by David Sehnal who showed computational infrastructure to visualize protein structures (MolStar). The mathematical problems of dimensionality reductions were a topic of Wolfgang Huber’s talk, and a tool to visualize, and thereby find(!), batch effects, “proBatch”, was presented in the flash talk by Jelena Čuklina (they welcome beta-testing by users!). Teaching science visualizations, I often see a great need to discuss ethical and practical aspects. Critically assessing limitations and challenges of scientific visualizations might be a topic to be expanded in future, when VIZBI enters its second decade. This should be coupled with visual perception research, after all, we are no longer limited by computational power, but rather by what our eyes and brains can comprehend (see Miller 1956).

Flash talks

Speaking of flash talks: the conference organisers did such a great job in highlighting every single one (!) of the posters by one-minute talks. I tremendously enjoyed them, admittedly in part because I have a short attention span. Among the talks and art was also “Data dancing” by Alex Diaz. He showed that art and beauty can also be found in statistics and numbers blossoming like flowers across the page. On that note: see you next year in San Francisco!

 

P.S. Many more highlights I was unable to cover here. Check https://vizbi.org/2019/ for all posters and slides of the flash talks, check #VIZBI on twitter and my public collection of participants twitter handles (https://twitter.com/helenajambor/lists/vizbi2019).

 

 

Meeting report by EMBL event reporter Dagmara Kaczynska

In March I had the amazing opportunity to take part at the 10^th Visualizing Biological Data (VIZBI) workshop as an EMBL event reporter. This year VIZBI lasted for 3 days and included various sessions: DNA, RNA, Proteins, Cellular Systems, Tissues & Organisms as well as Populations & Ecosystems. As it was my first VIZBI conference I had wondered how it is possible that one workshop contains such a diversity of topics. Who is the audience? Who are the speakers? Even if you missed the VIZBI workshop this year, let’s relive it together.

What is VIZBI?

To start uncovering VIZBI let’s first visit the website. It shows that VIZBI focuses mostly on how data is represented, not only what it presents. What’s more, we learn that the audience consists of a variety of crafts such as scientists, medical illustrators, graphic designers, artists and computer scientists. This multidisciplinarity is also visible in the program of the conference. Although most of the speakers are researchers, we can also expect talks from statisticians, computer scientists, animators and data visualization experts. This collaborative approach of VIZBI makes it possible to find common patterns and guidelines to make a good visualization of biological data. Most importantly, participants of the VIZBI conference believe that good visualization is the key to scientific communication.

While thinking about a visualization, think about data first

To begin with, let’s slice and dice the ‘biological data visualization’ concept by asking – what is visualization? As the first keynote speaker, Hadley Wickham, pointed out most of us has a very different perception on what it actually means.

As the workshop touched upon topics varying from DNA to ecosystems there are also many ways to visualize them. Regardless of the field of study, Hadley Wickham recommended to ‘firstly, think about the data’. The main goal is to decide on a message and a story behind the findings. After answering these fundamental questions one can start looking for the best means to visualize them.

Biological data is complex

Following his recommendation, let’s take a look at data presented during the conference. It was not surprising to learn that biological data is, quite simply, complex – regardless of whether one studies genomes, proteins or tissues. Philippe Collas discussed the complexity of a genome, composed of various elements, that forms different structures.  He made a point by saying that ‘three dimensions (3D) matters’ and an image is just a representation of a real case scenario.

Life happens in 3D so images cause danger of misinterpretation

Almost all the speakers mentioned that life happens in 3D, which causes many struggles in the visualization and interpretation of data. When Lucy Collinson introduced electron microscopy data she emphasized that 2D views (such as images) of 3D scenes (such as proteins) can be misinterpreted.

However, this problem concerns all biological fields. For example, Philippe Collas and Andy Yates discussed the complexity of a genome. Susan Clark presented how the 3D organization of epigenome is disrupted in cancer.

Moreover, Marc Baaden tackled the difficulties of recapitulating dynamics in a static image. In contrast, Loïc Royer showed 4D videos of morphogenesis and challenges with microscopes such as focus or stabilization of images as well as the importance of digital image processing.

Data and visualizations need to be cleaned and structured

In order to form the main message of a discovery, one needs to understand the complexity of data. Many speakers advised to clean and structure data as a first step of analysis. Here, Moritz Stefaner showed the image from Ursus Wehrli ‘The Art of Clean Up’ to represent the art of tidying up.

What’s more, structuring your visualization will help an audience understand the concept better. Hadley Wickham believes that orthogonal components make it easier to compare and remember (in this case using purr library in R).

Data analysis needs to be well documented (preferably in a form of code)

It is obvious that the analysis of biological data is not trivial.  What’s more, one set of data may lead to many different observations. Most of the speakers drew attention to the importance of documenting data and pipelines of analysis. Many advised to use codes. ‘A code is readable, reproducible text’ as Hadley Wickham presented. Most scientists, especially those from RNA and DNA fields such Charlotte Soneson, Irmtraud Meyer and Wolfgang Huber, shared the same opinion.

Data needs story for visualization

Now, when data is cleaned and tackled it is time to decide on the message and a story. Then, one can investigate possible ways of visualizing the findings. How can one find the best way to visualize data? Probably the most common advice was by trial and error, learning what others do, using design concepts, consulting with others. However, if you really have a clear purpose it will be much easier. Moritz Stefaner also believes that scientists have too much trust in the defaults. For example, he showed that rainbow gradient is not necessarily the best one!

Data analysis and visualization need iterations

According to Moritz Stefaner, Loïc Royer and Hadley Wickham, iterations are the key for a good data analysis and visualization. Prototyping and modifying should be a habit of all scientists. Only by iterating can we create something of great value and importance. One needs to ‘create a bunch of bad visualizations that need to be iterated as long as you find the best solution’ Hadley Wickham summarized.

Illustrations and animations capture the complexity of data

As mentioned above, the VIZBI society cares and makes an effort to prepare good visualizations. They believe that visualization is the key to every communication – illustrations and animations make a concept easier to understand. A recipient is able to grasp a research idea much faster. Janet Iwasa also showed that animation enables showing the complexity of biological data as they are in 3D. It can make a hypothesis more accurate and discoveries much clearer. She compared a model figure with a snapshot of her animation to illustrate the difference in perception.  What’s more, to make an animation one needs to fully understand a concept to illustrate it, which makes a finding more precise.

Conclusions

To conclude, although at first sight it seems that all VIZBI session are very diverse, in fact they have a lot in common. All present ways to visualize biological findings based on data. Having said that, the data and visualization techniques are very versatile, but there is a common pipeline. To make data clear to everyone the clue is to find the best way to visualize it by iterating and modifying different solutions. In order to find the best means we need to focus on a main message and story. To create a story we need to fully understand the data by cleaning, structuring and analyzing. Keeping a good documentation in the form of codes, storyboards and notes make findings transparent and reproducible to others. Communication is key in the progress of science, and scientists can improve their visualization methods and skills. VIZBI participants believe that it is worth putting in a lot of effort to make data more understandable and memorable.

Remember to have fun and use your creativity! I definitely had a lot of fun as an event reporter at the 2019 VIZBI workshop, and will incorporate all these lessons in my daily research.

If you have any questions or would like to discuss biological data visualization, please write me a message.

All the images were taken during the conference using private phone. All the images are set to presenter’s names. There are no images of slides that presenters asked not to tweet about.