In our first episode, Alex and Lorena dive into the messy reality of processing single-cell RNA-seq data. What started as a simple QC project turned into a week-long journey across compute environments, mysterious pipeline errors, and zero-cell outputs. Along the way, we troubleshoot issues with Cell Ranger, uncover strange sequencing artifacts, and reflect on lessons in data handling, pipeline reproducibility, and client communication.

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In the introductory episode, Lorena and Alex introduce themselves and share how they got started in computational biology. They talk about their career paths, what drew them to bioinformatics, and some of the challenges and surprises they’ve encountered along the way. They also give a preview of the kinds of topics and practical issues they’ll be covering on the podcast, from workflow basics to troubleshooting analysis hiccups.

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In this episode of A Coffee with CompBio, Lorena and Alex share the twists and turns of realizing their methylation data wasn’t what it seemed. From puzzlingly low mapping rates to unexpected cloud costs caused by unoptimized compute jobs—thankfully caught just in time thanks to cost alarms—they highlight how essential clear communication and bioinformatics-aware experimental design are to any successful project.

In our new segments, Quick Sips and Brewing Up for Answers, we talk about PIXI for managing software environments and dig into the ever-present challenge of staying organized across complex projects.

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Alex and Lorena discuss a large bulk RNA-seq project that yielded lasting changes to their group’s everyday bioinformatics practices via the creation of parameterized R Markdown code templates. In the “Quick Sip” segment, they discuss reticulate for managing python environments in an R context, and in “Brewing Up Answers”, they reflect on the differences between industry and academia bioinformatics. 

Thanks to our 300+ listeners of past episodes!

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In this episode, we journey through the real-life challenges of building interactive single cell spatial data visualizations for large projects. Lorena shares her recent adventure turning mountains of data into a web app using tools like Python, R, and the (tricky-to-pronounce) single-cell viewer Vitessce. She discusses the hurdles of image cropping, memory limits, Python-R crossovers, and why “just putting it online” isn’t as easy as it sounds—especially when it comes to privacy, deployment, and avoiding surprise cloud bills.If you’ve ever had a collaborator say, “Can you just build me an app I can play with?”, this episode is for you.

In the “Quick Sips” segment, Alex and Lorena share tips on automating code linting with GitHub Actions. Finally, in our “Brewing Up Answers” segment, we chat about managing people in academia vs. industry, and why it’s a very different ballgame on each side of the fence.

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Also, we are looking for sponsors! Please get in touch if you or your business would like to help support this podcast .

Follow us on LinkedIn: https://www.linkedin.com/in/lpantano/ and https://www.linkedin.com/in/alexandra-bartlett-926b32109/

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