MitoIMP: A Computational Framework for Imputation of Missing Data in Low-Coverage Human Mitochondrial Genome.

The incompleteness of partial human mitochondrial genome sequences makes it difficult to perform relevant comparisons among multiple resources. To deal with this issue, we propose a computational framework for deducing missing nucleotides in the human mitochondrial genome. We applied it to worldwide mitochondrial haplogroup lineages and assessed its performance. Our approach can deduce the missing nucleotides with a precision of 0.99 or higher in most human mitochondrial DNA lineages. Furthermore, although low-coverage mitochondrial genome sequences often lead to a blurred relationship in the multidimensional scaling analysis, our approach can correct this positional arrangement according to the corresponding mitochondrial DNA lineages. Therefore, our framework will provide a practical solution to compensate for the lack of genome coverage in partial and fragmented human mitochondrial genome sequences. In this study, we developed an open-source computer program, MitoIMP, implementing our imputation procedure. MitoIMP is freely available from https://github.com/omics-tools/mitoimp.