Quality control in the discovery, reporting, and recording of genomic variation.

Abstract

The usefulness of any database is dependent on the quality of its content. This is so for mutation databases and has been a continuing concern for those interested in such databases. This article discusses the critical points that determine the quality of the data, such as PCR errors, incomplete scanning, examination of the effect of the variation, and reporting and deposition of the mutations in a database. To illustrate the importance of quality control in mutation curation, nine articles reporting 34 novel phenylketonuria mutations were surveyed for the criteria believed to be important in describing mutations. Many articles were deficient in entries in several criteria, but there was still a high degree of certainty that the described mutations caused disease. Finally, strategies to eliminate errors and to enhance or indicate quality are discussed, including expression, the review process, checking deductions, and typing and encouraging compliance. Models for the future are also discussed.