UNCeqR is a method and associated software for discovering somatic mutations using the integration of DNA and RNA sequencing. UNCeqR is described in:
 Wilkerson MD, Cabanski CR, Sun W, Hoadley KA, Walter V, Mose LE, Troester MA, Hammerman PS, Parker JS, Perou CM, Hayes DN. (2014) Integrated RNA and DNA sequencing improves mutation detection in low purity tumors. Nucleic Acids Research. first published online June 26, 2014 doi:10.1093/nar/gku489
Precision cancer medicine depends on accurate somatic mutation detection to inform patient treatment, which is complicated by low tumor purity. In this setting, standard techniques of DNA whole exome sequencing yield low sensitivity. UNCeqR is a first-of-its-kind method that integrates patient-matched DNA sequencing and RNA sequencing to detect somatic mutations. Through application and validation in large cancer cohorts, we have demonstrated that adding RNA sequencing to DNA sequencing substantially boosts sensitivity for low purity tumors and rare mutations. UNCeqR substantially advances state-of-the-art mutation profiles with abundant novel driver and therapeutically-targeted mutation discoveries.
UNCeqR can accept a variety of sequencing inputs and configurations such as that depicted below.
- Somatic mutation discovery
Patient-matched DNA and RNA sequencing
RNA sequencing alone
DNA sequencing alone
- Interrogation of defined sites or mutations.
How to use UNCeqR
The minimum requirements to run UNCeqR is a tumor sequencing alignment. Additionally, there are a variety of data quality filtering options, described in  and in the documentation provided within the software distribution. For instance, mapping error alleles were calculated with the third party tool BlackOps tool. The population and artifact allele site used in  is available with the software distribution. Regenerating this allele list for different sequencing platforms is recommended. The output of UNCeqR is a table of somatically mutated sites and associated information. These somatic mutations can be annotated with predicted transcript and protein effects using third party tools, such as Annovar, as described in .
Examples of publications using UNCeqR
Frequently Asked Questions and Support
- Configuring for custom datasets
- Stay tuned