All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons |
| |
Authors: | Vivekananda Sarangi Yeongjun Jang Milovan Suvakov Taejeong Bae Liana Fasching Shobana Sekar Livia Tomasini Jessica Mariani Flora M Vaccarino Alexej Abyzov |
| |
Institution: | 1. Department of Quantitative Health Sciences, Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, United States of America;2. Child Study Center, Yale University, New Haven, Connecticut, United States of America;3. Department of Neuroscience, Yale University, New Haven, Connecticut, United States of America; Queen’s University, CANADA |
| |
Abstract: | Accurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing a cell’s genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell without the need for data from bulk(s). It is based on pair-wise comparisons of all cells to each other where every call for base pair substitution and indel is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing. |
| |
Keywords: | |
|
|