Protocol for achieving enhanced snRNA-seq data quality using Quality Clustering

Single-nucleus RNA sequencing (snRNA-seq) data analysis presents a challenge in samples that have high levels of ambient RNA contamination. Quality Clustering (QClus) removes empty and highly contaminated droplets by utilizing multiple contamination metrics. Here, we present the steps for snRNA-seq data preprocessing using the QClus algorithm. First, we describe how to set up a computational environment. Next, we demonstrate how to use QClus to remove highly contaminated droplets, and finally, we show how to visualize and evaluate the results. For complete details on the use and execution of this protocol, please refer to Schmauch et al.(1).