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MetaGLIMPSE: Meta-imputation of low-coverage sequencing data for modern and ancient genomes
Kiran H Kumar1, Simone Rubinacci2, Sebastian Zӧllner3
1Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA; Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA.
American Journal of Human Genetics
|March 8, 2026
Summary
MetaGLIMPSE offers accurate imputation for low-coverage sequencing, improving rare variant detection. This computationally efficient method enhances genetic analysis for both modern and ancient DNA samples.
Area of Science:
- Genomics
- Bioinformatics
Background:
- SNP array imputation has limitations for rare variants.
- Low-coverage sequencing requires accurate imputation methods.
- Privacy concerns limit direct use of multiple reference panels.
Purpose of the Study:
- To develop an efficient meta-imputation method for low-coverage sequencing.
- To improve imputation accuracy by combining multiple reference panels without privacy compromise.
- To evaluate MetaGLIMPSE performance on modern and ancient DNA.
Main Methods:
- Developed MetaGLIMPSE, a novel meta-imputation algorithm.
- Combined imputed genotypes from multiple reference panels using panel- and marker-specific weights.
- Tested performance across various coverages (0.1×-8×) and minor allele frequencies.
Main Results:
- MetaGLIMPSE consistently outperformed best single-panel imputation.
- Achieved accuracy comparable to combined panel imputation in some scenarios.
- Demonstrated computational efficiency, meta-imputing 500 genomes in 16% of GLIMPSE2 time.
Conclusions:
- MetaGLIMPSE provides an accurate and efficient solution for low-coverage sequencing imputation.
- The method enhances rare variant imputation across diverse DNA types and ancestries.
- MetaGLIMPSE overcomes privacy limitations of traditional multi-panel imputation.
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