Data supporting the high-accuracy haplotype imputation using unphased genotype data as the references.

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Haplotype imputation is crucial for genetic studies.
• Unphased genotype data can serve as a reference for imputation.
• Evaluating different imputation pipelines and software is essential for optimizing accuracy.

Purpose of the Study:

• To compare the performance of different implementation pipelines for haplotype imputation.
• To evaluate the accuracy of HiFi against three major imputation software tools.
• To provide data-driven strategies for selecting optimal phasing pipelines and software.

Main Methods:

• Development and comparison of three implementation pipelines (A, B, and C) for haplotype imputation.
• Performance evaluation based on accuracy metrics.
• Comparative analysis between the HiFi imputation tool and three established imputation software packages.

Main Results:

• The three implementation pipelines demonstrated similar accuracy, with implementation-B showing a slight, consistent advantage.
• HiFi achieved superior performance in haplotype imputation accuracy.
• The other three imputation software tools exhibited slightly better performance in genotype imputation accuracy.

Conclusions:

• Implementation-B offers a marginally improved accuracy over implementations A and C.
• HiFi is a strong choice for studies prioritizing haplotype imputation accuracy.
• The choice between HiFi and other software depends on whether haplotype or genotype imputation accuracy is the primary goal.