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Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences
View ORCID ProfileVincenza Colonna, Qasim Ayub, Yuan Chen, Luca Pagani, Pierre Luisi, Marc Pybus, Erik Garrison, Yali Xue, Chris Tyler-Smith, The 1000 Genomes Project Consortium
doi: https://doi.org/10.1101/005462
Vincenza Colonna
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
2Institute of Genetics and Biophysics ‘A. Buzzati-Traverso’, National Research Council (CNR), Naples, Italy
Qasim Ayub
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
Yuan Chen
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
Luca Pagani
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
Pierre Luisi
3Institute of Evolutionary Biology (Universitat Pompeu Fabra-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
Marc Pybus
3Institute of Evolutionary Biology (Universitat Pompeu Fabra-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
Erik Garrison
4Department of Biology, Boston College, Chestnut Hill, Massachusetts, USA
Yali Xue
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
Chris Tyler-Smith
1The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambs. CB10 1SA, UK
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Posted May 23, 2014.
Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences
Vincenza Colonna, Qasim Ayub, Yuan Chen, Luca Pagani, Pierre Luisi, Marc Pybus, Erik Garrison, Yali Xue, Chris Tyler-Smith, The 1000 Genomes Project Consortium
bioRxiv 005462; doi: https://doi.org/10.1101/005462
Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences
Vincenza Colonna, Qasim Ayub, Yuan Chen, Luca Pagani, Pierre Luisi, Marc Pybus, Erik Garrison, Yali Xue, Chris Tyler-Smith, The 1000 Genomes Project Consortium
bioRxiv 005462; doi: https://doi.org/10.1101/005462
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