New Tool Allows Haplotype-Aware Protein Sequence Analysis

Researchers at the University of Bergen have developed a new method to improve protein sequence analysis. The traditional approach of using the same reference proteins for all participants has been found to introduce bias, particularly for individuals who differ from the reference.

According to Marc Vaudel, senior author of the study published in Nature Methods, "We found that the small genetic changes that make us who we are create a bias: for those who differ from the reference, current informatic methods are blind to parts of their proteins."

To address this issue, the team created ProHap, a Python-based tool that constructs protein sequence databases from phased genotypes of reference panels. This innovation allows researchers to account for haplotype diversity in proteomic searches.

First author Jakub Vašíček, who designed the method, emphasizes the importance of this development: "Accounting for a greater diversity among cohort participants is key to refine medical research to individual profiles."

The new approach captures protein sequences that are most likely to be observed in the population, potentially leading to more accurate and personalized medical research. However, the researchers acknowledge that challenges remain. Many groups are underrepresented in genetic panels, and integrating diversity into current data models is complex. Vašíček notes, "The road is still long before we can treat all patients fairly, but we are making good progress.”