Multidimensional multi-omics datasets from The Cancer Genome Atlas (TCGA), the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and similar initiatives are becoming a powerful approach to understanding the molecular basis of disease and accelerating the translation of new discoveries to patient care. While there is value in multi-omics technologies and datasets to help reach a deeper understanding of a disease and ultimately help a physician and patient determine the most appropriate treatment option, sample mislabeling presents as a roadblock that can occur in data production and analysis pipelines involving data-rich, large-scale omics studies.
In the latest publication of the journal Nature Medicine, FDA and CPTAC are launching the precisionFDA NCI-CPTAC Multi-omics Mislabeling Challenge, the first computational challenge using multi-omics data to detect and correct specimen mislabeling. The challenge objective is to encourage development and evaluation of computational algorithms that can accurately detect and correct mislabeled samples using rich multi-omics data. This challenge has the potential to accelerate the translation of multidimensional omics technologies and datasets into the clinic.
Please visit the precisionFDA NCI-CPTAC Mislabeling Challenge webpage to sign up for more information.
Launch and data release for subchallenge 1: September 24, 2018
Subchallenge 1 submission deadline: October 31, 2018
Data release for subchallenge 2: November 1, 2018
Subchallenge 2 submission deadline: December 18, 2018
Results posted on precisionFDA: January 22, 2019