One challenging subfield of proteomics that has recently emerged is single-cell proteomics. The ability to study protein expression levels from individual cells rather than describing expression levels on a population level provides a more detailed understanding of cellular processes within tissues in both healthy and pathological conditions. Major challenges in single-cell proteomics are the extremely low sample amounts, complicating protein extraction, detection and quantification. In recent years, many specialized sample preparation and data acquisition methods have been developed to address these issues. Some efforts have also been made to improve data analysis approaches for single-cell proteomics, such as the use of advanced retention time alignment strategies. Nevertheless, there is still an effort to be made to further enhance the downstream data analysis of single-cell proteomics data.