IceR improves proteome coverage and data completeness in global and single-cell proteomics

Abstract

Label-free quantitative proteomics by data dependent acquisition offers high protein identification rates but is often limited by missing values. Here, the authors develop a quantification workflow that substantially reduces missing values while maintaining high identification rates and quantification accuracy.