Open AccessAll2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons
Author(s) -
Vivekananda Sarangi,
Yeongjun Jang,
Milovan Šuvakov,
Taejeong Bae,
Liana Fasching,
Shobana Sekar,
Livia Tomasini,
Jessica Mariani,
Flora M. Vaccarino,
Alexej Abyzov
Publication year - 2022
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1009487
Subject(s) - indel , computational biology , genome , mutation , biology , genetics , exome , false positive paradox , computer science , exome sequencing , gene , artificial intelligence , single nucleotide polymorphism , genotype
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, All 2 , 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 All 2 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.