CPTAC and FDA publish findings of a community effort to identify and correct mislabeled samples in multi-omics studies
In biomedical research, sample mislabeling or incorrect annotation has been a long-standing issue contributing to irreproducible results and invalid conclusions. These issues are particularly prevalent in large scale multi-omics studies, in which multiple different omics experiments are carried out at different time periods and/or in different labs and human errors can arise during sample transferring, sample tracking, large-scale data generation, and data sharing/management.