In a short period of time, I’ve encountered two situations where I needed to fix bugs in R functions, and I’ve also learned how to perform hot replacements…

If you live long enough, you’ll encounter plenty of awkward situations.

In bioinformatics, the more cutting-edge your research direction, the more problems you’ll face from the informatics side. Even when papers are published with excellent results, and the original authors share their code or even provide ready-to-use software tools, it doesn’t mean we can easily use these existing resources for reproduction or further research. Chaotic environment setup is just one aspect - more often than not, since software authors aren’t professional software engineers, we should be grateful if the tool just works. We can’t expect these software to be bug-free, nor can we expect them to have decent performance (unless performance was a development goal). Even tools from well-established labs aren’t free to these issues, such as… Azimuth.

I’ve developed a habit of listening to videos during my bike ride home after work. This week, I came across a video by XPIN about RISC-V. The video presents a viewpoint: RISC-V, as an instruction set architecture, suffers from severe fragmentation in its chip products, which poses significant challenges to the development of its application ecosystem. Therefore, it’s argued that fragmentation must be addressed through unified standards to achieve rapid development. This perspective reminded me of my years of experience using Linux, Android, and the R language, leading me to believe that the video’s argument might not be entirely accurate.

I’m still quite fond of my current Hexo theme. From using its predecessor material-x in 2021 to upgrading to Volantis 5.x in 2023, the theme’s functionality has completely met my personal needs, to the point where I haven’t upgraded to the author’s subsequent versions 6 and 7. However, after using AI to batch-translate my blog content into English earlier this year, there have been persistent issues with some interface elements remaining in Chinese. This year, instead of undertaking major renovations, I decided to fix these minor bugs myself under AI guidance.

Recently, I attempted to use pixi to compile and run podman on FydeOS. While I made some progress, it ultimately only achieved half success. In this blog post, I’ll share the entire process and the issues encountered.

When using pixi to manage bioinformatics analysis environments, we often encounter issues where some Bioconductor R packages show missing dependencies after installation. The exact cause of this problem is currently unclear. After using pixi for a year, this issue still hasn’t been fixed (as of October 2025). This article introduces how to use pixi’s tasks feature to resolve such problems.

In our current single-cell analysis pipeline based on scanpy, there’s a step that requires saving AnnData objects in loom format. However, unlike saving to h5ad format, when we write an AnnData object to a loom file without any special handling and then read it back, we find that the index information of obs and var (typically cell barcodes and gene names) is lost, and these indices become ordinary numeric identifiers.

Milo is a differential abundance analysis method for single-cell RNA sequencing data that can detect compositional changes in cell neighborhoods across different conditions.

DevPod is an open-source development environment management tool that allows you to create development environments similar to GitHub Codespaces on any Kubernetes cluster or Docker host. This article will introduce how to use the DevPod CLI to create workspaces and provide a detailed explanation of writing DevContainer configuration files.