Protocol for fast scRNA-seq raw data processing using scKB and non-arbitrary quality control with COPILOT.

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Single-cell RNA sequencing (scRNA-seq) is a powerful tool for analyzing cellular heterogeneity.
• Quality control of raw scRNA-seq data is crucial for accurate downstream analysis.
• Existing methods can be time-consuming or lack objective criteria.

Purpose of the Study:

• To present a streamlined protocol for fast and non-arbitrary quality control of scRNA-seq raw data.
• To introduce scKB and COPILOT as tools to improve scRNA-seq data processing.
• To provide an accessible entry point for new users of scRNA-seq technology.

Main Methods:

• scKB, a wrapper for kallisto and bustools, was developed for accelerated alignment and transcript count matrix generation.
• COPILOT was employed for non-arbitrary background noise removal by comparing cell quality distributions.
• The protocol integrates these tools into a cohesive workflow.

Main Results:

• scKB demonstrated significantly faster processing speeds compared to Cell Ranger.
• COPILOT effectively removed background noise based on objective quality metrics.
• The combined protocol streamlines the scRNA-seq data processing workflow.

Conclusions:

• The scKB and COPILOT protocol offers a fast and reliable method for scRNA-seq quality control.
• This approach simplifies data processing and enhances accessibility for researchers new to scRNA-seq.
• The protocol facilitates more efficient and accurate analysis of single-cell gene expression data.