Limiting the impact of protein leakage in single-cell proteomics.

Limiting artifacts during sample preparation can significantly increase data quality in single-cell proteomics experiments. Towards this goal, we characterize the impact of protein leakage by analyzing thousands of primary single cells that were prepared either fresh immediately after dissociation or cryopreserved and prepared at a later date. We directly identify permeabilized cells and use the data to define a signature for protein leakage. We use this signature to build a classifier for identifying damaged cells that performs accurately across cell types and species.
Competing Interests: Competing interests: N.S. is a founding director and CEO of Parallel Squared Technology Institute, which is a nonprofit research institute.