A systematic statistical genetics approach discovers CES drivers as hotspots of human de novo mutation and shows that clonal expansions in germline may both modulate the prevalence of disorders and lead to false-positive disease associations.

A combination of whole-genome NanoSeq with deep whole-exome and targeted NanoSeq is used to accurately characterize mutation rates and genes under positive selection in sperm cells.

A new version of nanorate DNA sequencing, with an error rate lower than five errors per billion base pairs and compatible with whole-exome and targeted capture, enables epidemiological-scale studies of somatic mutation and selection and the generation of high-resolution selection maps across coding and non-coding sites for many genes.

A new computational approach to in silico mutagenesis screening allow comprehensive mapping of cancer driver mutations.

Sex bias and association with smoking history identified in the landscape of driver mutations and clonal expansions in normal human bladder tissue may explain the higher bladder cancer risk in men and smokers.

Abstract. Identifying the genes capable of driving tumorigenesis in different tissues is one of the central goals of cancer genomics. Computational methods