Abstract
Tumor progression is an evolutionary process during which cells acquire distinct genetic alterations. Several cancer evolutionary studies reconstruct this evolutionary process by applying bulk DNA sequencing to a tumor sample to infer the presence of genetic alterations using various tumor evolutionary algorithms. Through a comprehensive benchmarking effort of these algorithms, a recent study by Salcedo and colleagues found that algorithmic and experimental choices are the main drivers of the accuracy of tumor evolution reconstruction, shedding new light on interpreting previous studies and suggesting a useful path forward for the research community.
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