An examination of the OMIM database for associating mutation to a consensus reference sequence

Area of Science:

• Biomedical Informatics
• Genetics
• Molecular Biology

Background:

• Gene mutations and associated phenotypes are crucial biomedical data.
• Databases like OMIM store this information, but data quality is often unexamined.
• Accurate mutation data is essential for genetic research and clinical applications.

Purpose of the Study:

• To assess the data quality of protein single-point mutations within the OMIM database.
• To identify and analyze the reasons for inconsistencies between mutation positions and reference sequences.
• To propose a method for resolving data discrepancies in OMIM.

Main Methods:

• Systematic examination of protein single-point mutation entries in the OMIM database.
• Alignment verification of reported mutation positions against corresponding reference sequences.
• Categorization and analysis of errors leading to mapping failures.

Main Results:

• Nearly 20% of OMIM mutation data could not be accurately mapped to a single reference sequence.
• Common causes for mapping failures include positional conflicts and site shifting (e.g., N-terminal methionine).
• Various other data errors contribute to the observed inconsistencies.

Conclusions:

• Significant data quality issues exist for protein mutation information in OMIM.
• These inconsistencies pose challenges for reliable data utilization in research.
• A preliminary model is proposed to address and resolve these OMIM data errors.