Introduction Cancer genomes exhibit surprisingly weak signatures of negative selection[1][1],[2][2]. This may be because tumors evolve either under very weak selective pressures (‘weak selection') or under conditions that prevent the elimination of …
The functional impact of most genomic alterations found in cancer, alone or in combination, remains largely unknown. Here we integrate tumor barcoding, CRISPR/Cas9-mediated genome editing and ultra-deep barcode sequencing to interrogate pairwise …
Large-scale genomic analyses of human cancers have cataloged somatic point mutations thought to initiate tumor development and sustain cancer growth. However, determining the functional significance of specific alterations remains a major bottleneck …
Genomic instability and high mutation rates cause cancer to acquire numerous mutations and chromosomal alterations during its somatic evolution; most are termed passengers because they do not confer cancer phenotypes. Evolutionary simulations and …
The ziggurat algorithm is a very fast rejection sampling method for generating pseudorandom numbers (PRNs) from statistical distributions. In the algorithm, rectangular sampling domains are layered on top of each other (resembling a ziggurat) to …
Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. …
DNA instability is an important contributor to cancer development. Previously, defects in the chromosome segregation and excessive DNA double strand breaks due to the replication or oxidative stresses were implicated in DNA instability in cancer. …
Cancer progression is driven by the accumulation of a small number of genetic alterations. However, these few driver alterations reside in a cancer genome alongside tens of thousands of additional mutations termed passengers. Passengers are widely …