In our Getting to know us (a.k.a. Teamsembl) blog series, we talk to Ensembl colleagues and ask them a series of questions about their role in the project. In June, we talked to Jack Carpenter, who is a visiting PhD student within the Ensembl Non-Vertebrates team. Learn more about Jack’s placement at Ensembl and the experience he gained
Why did you choose to do a placement at Ensembl?
Coming from a biology background and a wet-lab research group, I was keen to work with and learn from highly skilled bioinformaticians in a non-academic setting. As a regular Ensembl Plants user, I decided to reach out to EMBL-EBI’s Non-vertebrate Genomics team. The group was very welcoming and committed to ensuring I would be a productive team member. The proposed projects were also well-tailored, enabling me to develop new collaborative and technical skills, particularly in Python, Git, SQL and Nextflow. The team seemed to be the perfect place to collaborate with experienced bioinformaticians whilst further developing my computational skills.
How long is your placement at Ensembl and what are you working on?
During my three-month placement, I have been working on developing a Nextflow pipeline that utilises Python scripts to detect an organism’s ploidy level from genome assembly metadata. Once completed, this code will be integrated with the genome loading pipeline to help with the automation of the Ensembl genome loading process. At the same time, I have been loading a few genomes to be released on the Ensembl Genomes website as well as the newer Ensembl Beta website.
What do you enjoy the most about your placement?
A placement that has both enabled me to make a meaningful contribution to Ensembl’s Non-vertebrates team whilst advancing my bioinformatics career has been incredibly fulfilling. Also the walks around the Wellcome Genome Campus are stunning and the snack desk in the office is pretty great too!
How did you get into bioinformatics?
Both my Master’s and PhD projects focus on stem cell development in the plant model organism Arabidopsis thaliana and I’m looking into how some transcription factor proteins regulate the genome on an epigenetic level to regulate cellular differentiation. During my work, I ended up generating a few multiomics datasets and needed to learn how to process and interpret the results. Luckily, my Master’s course had an intensive bioinformatics and biostatistics module, providing a holistic view of processing next-generation sequencing data in genome assembly, transcriptomics, metagenomics and phylogeny contexts. This introduced me to the field of bioinformatics and gave me a good basis for Bash and R scripting. During my research project, I applied what I had learnt by creating my own RNA-Seq pipeline, analysing the data and presenting my findings. I was very engaged with the computation and analysis aspects of the experimental processes and realised I wanted to develop my bioinformatics skills further.
What advice do you wish you had been given when you started in bioinformatics?
There are lots of free online resources out there that you can use to learn pretty much everything about bioinformatics, which is great, but for me the real consolidation came from applying what I had learnt. Some great websites to help with this are the ROSALIND Problems or sandbox.bio. Better still, I would recommend finding a research group with a computational-based project that you can get invested in. Also, when starting out, keeping a lab book for writing general notes and collecting thoughts is a good idea, I use a free note manager called Obsidian. Doing this from the beginning saved me a lot of effort; by keeping a stockpile of hints, I can often use them for resolving error messages I’ve already come across. It can also be helpful for remembering the basics, like how to exit Vim!
What is your favourite hobby or pastime?
I love to be in the ocean, I’ve even done a couple of Christmas day swims! Whether its surfing, paddle boarding, kayaking, coasteering or just a casual swim I’m always more than happy to have a dip in the closest river, lake or sea (unless it’s the Arctic sea of course, I’m not mad!).