dropkick is a fully automated software tool for quality control and filtering of single-cell RNA sequencing (scRNA-seq) data, with a focus on excluding ambient barcodes and recovering real cells bordering the quality threshold. dropkick sets initial thresholds based on predictive global heuristics, then learns a gene-based representation of real cells and ambient barcodes, calculating a cell probability score for each barcode on a per-dataset basis. dropkick was developed primarily in Ken Lau’s lab.


Automated quality control and filtering of droplet-based single-cell data using dropkick, Heiser et al., Genome Res 2021