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Zero-preserving imputation of single-cell RNA-seq data.

Nature communications (2022-01-13)
George C Linderman, Jun Zhao, Manolis Roulis, Piotr Bielecki, Richard A Flavell, Boaz Nadler, Yuval Kluger
要旨

A key challenge in analyzing single cell RNA-sequencing data is the large number of false zeros, where genes actually expressed in a given cell are incorrectly measured as unexpressed. We present a method based on low-rank matrix approximation which imputes these values while preserving biologically non-expressed genes (true biological zeros) at zero expression levels. We provide theoretical justification for this denoising approach and demonstrate its advantages relative to other methods on simulated and biological datasets.

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ディスパーゼ®II, protease
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コラゲナーゼ Clostridium histolyticum由来, Type XI, 2-5 FALGPA units/mg solid, ≥800 CDU/mg solid
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デオキシリボヌクレアーゼ II from bovine spleen, Type V, essentially salt-free, lyophilized powder, ≥1,000 units/mg protein