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Deconstructing structure

By Elie Dolgin Deconstructing structure Courtesy of Jonathan Pritchard The paper: D. Falush et al., “Inference of population structure using multilocus genotype data: dominant markers and null alleles,” Mol Ecol Notes, 7:574–78, 2007. (Cited in 91 papers) The finding: University College Cork’s Daniel Falush and the University of Chicago’s Jonathan Pritchard updated a widely used comp

Elie Dolgin

Deconstructing structure

Courtesy of Jonathan Pritchard

The paper:

D. Falush et al., “Inference of population structure using multilocus genotype data: dominant markers and null alleles,” Mol Ecol Notes, 7:574–78, 2007. (Cited in 91 papers)

The finding:

University College Cork’s Daniel Falush and the University of Chicago’s Jonathan Pritchard updated a widely used computer program called STRUCTURE that clusters organisms into populations based on multilocus genotype data to tease apart cryptic species or ancestral history. The researchers “added a little whistle on the program,” says Pritchard, by including dominant genetic markers, which make differentiating between homozygous and heterozygous genotypes.

The impact:

The software’s improvement was especially important to researchers who rely on dominant markers and who study organisms without sequenced genomes, says Noah Rosenberg, a population geneticist at the University of Michigan, Ann Arbor.

The application:

Using STRUCTURE and dominant markers called amplified fragment length polymorphisms, University of Colorado at...

The future:

“I do hope to fully replace STRUCTURE for dense data” such as single nucleotide polymorphisms and multiple genome comparisons, says Falush, who is working on an alternative algorithm to extract more demographic detail from large datasets. “With a little imagination, you should be able to get a lot more information,” he says.

Versions of STRUCTURE:
1.0: Genetics 155:945-59, 2000
2.0: Genetics 164:1567-87, 2003
2.2: Mol Ecol Notes 7:574-78, 2007
2.3: Mol Ecol Res 9:1322-32, 2009

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