|sw summary=er CNVer is a method for CNV detection that supplements the depth-of-coverage with paired-end mapping information, where matepairs mapping discordantly to the reference serve to indicate the presence of variation. CNVer combines this information within a unified computational framework called the donor graph, allowing it to better mitigate the sequencing biases that cause uneven local coverage. CNVer can also reconstruct the absolute copy counts of segments of the donor genome, and work with low coverage datasets. |bio domain=Structural variantsstructural variation detection and copy number variation detection|maintained=Yes