October 25, 2023

Charlotte Soneson: embracing the command line

Spotlight on FMIers showcases the lives, work and passions of the institute’s researchers and support staff. Charlotte Soneson, a member of the FMI Computational Biology Platform, told us about her career path in a field that is dominated by men and discussed efforts to build a diverse and collaborative community of software developers and data scientists.

Eighteen years ago, Charlotte Soneson got into computational biology almost by chance. Today, she’s an accomplished computational biologist who provides support to FMI researchers and is involved in an international project to develop open-source software for the analysis of biological data. Soneson is also the winner of this year’s Ruth Chiquet Prize, an internal FMI award for the most innovative new method or tool. Soneson was recognized together with Jan Seebacher, head of the FMI Proteomics Platform, for the development of “einprot” — an open-source software package for the statistical analysis of quantitative proteomics data.

How does it feel to be the winner of the Ruth Chiquet Prize?
It’s great!

How did your collaboration with Jan Seebacher in the Proteomics Platform start?
Two years ago, I was giving a workshop at the FMI about an interactive visualization tool, and Jan thought that the tool could be useful for proteomics data. Initially, it was a small project, but with time it expanded into what is now the einprot package. At the moment, the Proteomics Platform runs every proteomics experiment that is suitable for a quantitative analysis through this software package, and then the person who generated the data gets a report that allows them to go through everything that was done: they can see the results and explore them interactively, they can use the figures for their presentations, they can also run the tool themselves if further analyses are needed. We try to adapt the tool so that many different people can use it. Hopefully it’s something impactful for the FMI.

What inspired you to become a computational biologist?
I was always interested in mathematics and physics, but it was a bit of a coincidence that I got into computational biology. I did a master’s in engineering physics, and my thesis was in pure mathematics. After the master’s, I was looking into logistics and accounting, but then I got involved in a project together with a research group in the Biomedical Centre of Lund University in Sweden. That became my first PhD project. During my PhD, I mostly focused on visualization of high-dimensional data and new ways of exploring and visualizing them, especially to extract weak signals. After my PhD, which was in mathematics applied to genomics data and neuroscience data, I worked for three years as a computational biologist at the Swiss Institute of Bioinformatics in Lausanne. Then, I did a postdoc at the University of Zurich, working on method development for RNA-sequencing data. Five years ago, I joined the FMI’s Computational Biology Platform.

What are your main tasks as a senior computational biologist at the FMI?
In the Computational Biology Platform, we collaborate with research groups at the FMI in planning experiments and analyzing data. We also develop computational tools when we feel that there is a need for that. We teach and organize workshops, summer schools and courses at the FMI, at the University of Basel, at the Swiss Institute of Bioinformatics and elsewhere. We also keep in touch with the rest of the computational biology community to get input and share our experiences. For me, that's through Bioconductor, a project to develop, support, and disseminate free open-source software to analyze data from biological assays in a rigorous and reproducible manner.

How exactly are you involved in Bioconductor?
I co-chair the Teaching Committee, I'm involved in organizing the annual Bioconductor conferences, and I develop software packages — I submitted my first one 10 years ago and it's been a few more along the way. For the past four years, I've also been part of the Technical Advisory Board, which provides advice related to the technical underpinnings of the project, the core infrastructure, and the development and maintenance of software packages. It's nice to interact with people who are doing similar things as I do but are outside of my immediate work environment.

What do you like the most about your job at the FMI?
It's super varied. At the FMI, you get to work with a lot of very smart and dedicated people. There are so many technological developments and new things to learn all the time. You never get bored.

How is it to be a female researcher in a male-dominated field?
I have not felt that I have been hindered based on my gender. I've always had supportive mentors, and my parents never questioned why I wanted to do computational analysis or mathematics. At the same time, computational biology is still dominated by men, and you see that in conferences and organizations. But there is more awareness now, and there are groups, such as the R-ladies and the PyLadies, that work to create a more diverse computational community and increase the representation of women and other underrepresented minorities.

What is your advice for female scientists who want to work in computational biology?
For me, it was helpful to engage also with things that were not my own research project. Being involved in different activities helps build a network that can be useful both personally and professionally. It doesn't have to be very time-consuming: one can help organize a conference or do some teaching or contribute to an open-source software project. This month, for example, there is an event called Hacktoberfest, which is aimed at encouraging people to contribute to open-source software.

What's an interesting fact about you that isn’t on your CV?
I grew up close to the first IKEA store, so I used to work in their warehouse during summer, driving a forklift. When delivery trucks would come in, I would take the furniture out of the truck and put it in the storage.


Hailing from Osby, Sweden, Charlotte Soneson obtained a master’s degree in engineering physics and a PhD in mathematics from Lund University. After a stint as a postdoc at the University of Zurich, she joined the FMI Computational Biology Platform in 2018. In her free time, she enjoys running, watching old movies, and playing pop music at the piano. She recently took up knitting, too. Her favorite coding language is R.

Related stories