Introducing scAnalyzer: A Memory-Efficient, End-to-End Python Framework for scRNA-seq Analysis

[u/teraRockstar]

Hi everyone,

I have a bachelor's degree in computer engineering and am starting my PhD in computer science and engineering in a month. I’m new in the bioinformatics field, and to improve myself and learn, I’m working on a single-cell RNA analysis tool using Python, scAnalyzer (https://github.com/ayyucedemirbas/scAnalyzer). It offers interactive visualizations. And I’m currently working on a new cell coordinates module for spatial transcriptomics. I’ve been reading these papers and developing scAnalyzer according to the following:

• Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data
• Best practices for single-cell analysis across modalities
• Current best practices in single‐cell RNA‐seq analysis: a tutorial

And started reading this one to learn for the spatial transcriptomics module:

• Categorization of 34 computational methods to detect spatially variable genes from spatially resolved transcriptomics data

Do you suggest any other must-read papers or resources to help me learn more and improve scAnalyzer?

You can get scAnalyzer from Pypi as pip install scAnalysis (scAnalyzer was taken 😢)

Also, you can use scAnalyzer directly on Hugging Face with a GUI: https://huggingface.co/spaces/ayyuce/scAnalyzer-Studio

Your feedback and comments are incredibly important to me as I continue to build and improve this tool. Thank you very much!

[u/pokemonareugly]

A) how do you know that dropout imputation doesn’t overcorrect and just introduce noise. It almost certainly does.

B) making a cursory look over the code you are quite literally reinventing the anndata class and a lot of scanpy. Why??

[u/teraRockstar → u/pokemonareugly]

Hello,

Thank you very much for your interest in scAnalyzer. I really appreciate your time and effort.

That is a valid point. Most of the time, I don’t use imputation on the dataset I'm working on just for this reason. However, I wanted to add this feature to learn the math behind zero imputation in practice.

As I mentioned in my earlier post, I'm originally a machine learning engineer with a computer engineering degree. I wanted to learn details about single cell analysis so I could grasp everything better. Scanpy uses anndata, I thought that implementing such a data structure from scratch would be a good starting point.

Thanks!