@article {872,
	title = {Rapid, Paralog-Sensitive CNV Analysis of 2457 Human Genomes Using QuicK-mer2.},
	journal = {Genes (Basel)},
	volume = {11},
	year = {2020},
	month = {2020 01 29},
	abstract = {<p>Gene duplication is a major mechanism for the evolution of gene novelty, and copy-number variation makes a major contribution to inter-individual genetic diversity. However, most approaches for studying copy-number variation rely upon uniquely mapping reads to a genome reference and are unable to distinguish among duplicated sequences. Specialized approaches to interrogate specific paralogs are comparatively slow and have a high degree of computational complexity, limiting their effective application to emerging population-scale data sets. We present QuicK-mer2, a self-contained, mapping-free approach that enables the rapid construction of paralog-specific copy-number maps from short-read sequence data. This approach is based on the tabulation of unique k-mer sequences from short-read data sets, and is able to analyze a 20X coverage human genome in approximately 20 min. We applied our approach to newly released sequence data from the 1000 Genomes Project, constructed paralog-specific copy-number maps from 2457 unrelated individuals, and uncovered copy-number variation of paralogous genes. We identify nine genes where none of the analyzed samples have a copy number of two, 92 genes where the majority of samples have a copy number other than two, and describe rare copy number variation effecting multiple genes at the APOBEC3 locus.</p>},
	keywords = {Algorithms, Computational Biology, DNA Copy Number Variations, Evolution, Molecular, Gene Duplication, Genome, Human, Humans, Sequence Analysis, DNA},
	issn = {2073-4425},
	doi = {10.3390/genes11020141},
	author = {Shen, Feichen and Kidd, Jeffrey M}
}
