IQI: Individualized Quantitative trait loci (QTL) Index

Xu, J.; Sun, C.; Tao, J.; Wei, S.; Dong, Y.; Guo, X.; Tian, H.; Chen, H.; Ma, Y.; Lyu, W.; Bi, S.; Zou, Y.; She, W.; Zhang, C.; Kang, J.; Kong, F.; Zhang, M.; Lyu, H.; Jiang, Y.

doi:10.1101/2025.02.06.636780

bioRxiv · 10.1101/2025.02.06.636780

IQI: Individualized Quantitative trait loci (QTL) Index

Xu, J.·Sun, C.·Tao, J.·Wei, S.·Dong, Y.·Guo, X.·Tian, H.·Chen, H.·Ma, Y.·Lyu, W.·Bi, S.·Zou, Y.·She, W.·Zhang, C.·Kang, J.·Kong, F.·Zhang, M.·Lyu, H.·Jiang, Y.

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Abstract

There is currently no standard efficient method to precisely detecting and characterizing the difference of quantitative trait loci (QTL) effect among groups and/or populations at individual level. The main reason is that the traditional global regression based QTL analyses can only derive an overall effect of genetic variants on the quantitative trait in a specific group. It is a big challenge to obtain the individual-level QTL effect, which is necessary for accurate testing and precise characterization. Here, we first proposed an individualized QTL index (IQI) that represents the degree of regulation between genetic variants and the trait for each individual. Based on IQI, Differential QTL (DQ) analysis framework was presented to accurately detect the case-control differences in more detail. In addition, IQI can be a new feature/biomarker applied to various accurate bioinformatics analysis, such as differential analysis, disease prediction, and survival analysis. Overall, IQI affords a new perspective on pathogenic mechanisms and will facilitate the study of genetic regulation more detailedly and precisely.

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Xu, J., Sun, C., Tao, J., Wei, S., Dong, Y., Guo, X., Tian, H., Chen, H., Ma, Y., Lyu, W., Bi, S., Zou, Y., She, W., Zhang, C., Kang, J., Kong, F., Zhang, M., Lyu, H., Jiang, Y.. 2025-02-08. IQI: Individualized Quantitative trait loci (QTL) Index. https://doi.org/10.1101/2025.02.06.636780

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