RT Journal Article SR Electronic T1 Computational reconstruction of clonal hierarchies from bulk sequencing data of acute myeloid leukemia samples JF bioRxiv FD Cold Spring Harbor Laboratory SP 2021.01.23.427897 DO 10.1101/2021.01.23.427897 A1 Thomas Stiehl A1 Anna Marciniak-Czochra YR 2021 UL http://biorxiv.org/content/early/2021/01/25/2021.01.23.427897.abstract AB Acute myeloid leukemia is an aggressive cancer of the blood forming system. The malignant cell population is composed of multiple clones that evolve over time. Clonal data reflect the mechanisms governing treatment response and relapse. Single cell sequencing provides most direct insights into the clonal composition of the leukemic cells, however it is still not routinely available in clinical practice. In this work we develop a computational algorithm that allows identifying all clonal hierarchies that are compatible with bulk variant allele frequencies measured in a patient sample. The clonal hierarchies represent descendance relations between the different clones and reveal the order in which mutations have been acquired. The proposed computational approach is tested using single cell sequencing data that allow comparing the outcome of the algorithm with the true structure of the clonal hierarchy. We investigate which problems occur during reconstruction of clonal hierarchies from bulk sequencing data. Our results suggest that in many cases only a small number of possible hierarchies fits the bulk data. This implies that bulk sequencing data can be used to obtain insights in clonal evolution.Competing Interest StatementThe authors have declared no competing interest.