Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 176

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

The Great Migration and African-American Genomic Diversity

Open access
Baharian, Soheil, Barakatt, Maxime, Gignoux, Christopher R., Shringarpure, Suyash, Errington, Jacob, Blot, William J., Bustamante, Carlos D., Kenny, Eimear E., Williams, Scott M., Aldrich, Melinda C., Gravel, Simon·2016·PLOS Genetics

Published version of a preprint

Abstract

We present a comprehensive assessment of genomic diversity in the African-American population by studying three genotyped cohorts comprising 3,726 African-Americans from across the United States that provide a representative description of the population across all US states and socioeconomic status. An estimated 82.1% of ancestors to African-Americans lived in Africa prior to the advent of transatlantic travel, 16.7% in Europe, and 1.2% in the Americas, with increased African ancestry in the southern United States compared to the North and West. Combining demographic models of ancestry and those of relatedness suggests that admixture occurred predominantly in the South prior to the Civil War and that ancestry-biased migration is responsible for regional differences in ancestry. We find that recent migrations also caused a strong increase in genetic relatedness among geographically distant African-Americans. Long-range relatedness among African-Americans and between African-Americans and European-Americans thus track north- and west-bound migration routes followed during the Great Migration of the twentieth century. By contrast, short-range relatedness patterns suggest comparable mobility of ∼15-16km per generation for African-Americans and European-Americans, as estimated using a novel analytical model of isolation-by-distance.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pgen.1006059

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 8 references

Research works printed but not linked: 24

  1. CD Bustamante, 2011, Genomics for the world, Nature, 475, 163, 10.1038/475163a · DOI · Paper page
  2. EG Burchard, 2014, Missing patients, Nature, 513, 301, 10.1038/513301a · DOI
  3. JM Kidd, 2012, Population Genetic Inference from Personal Genome Data: Impact of Ancestry and Admixture on Human Genomic Variation, The American Journal of Human Genetics, 91, 660, 10.1016/j.ajhg.2012.08.025 · DOI · Paper page
  4. K Bryc, 2012, Genome-wide patterns of population structure and admixture in West Africans and African Americans, Proceedings of the National Academy of Sciences, 107, 786, 10.1073/pnas.0909559107 · DOI · Paper page
  5. BK Maples, 2013, RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference, The American Journal of Human Genetics, 93, 278, 10.1016/j.ajhg.2013.06.020 · DOI · Paper page
  6. A Auton, 2009, Global distribution of genomic diversity underscores rich complex history of continental human populations, Genome Research, 19, 795, 10.1101/gr.088898.108 · DOI · Paper page
  7. MW Smith, 2004, A High-Density Admixture Map for Disease Gene Discovery in African Americans, The American Journal of Human Genetics, 74, 1001, 10.1086/420856 · DOI · Paper page
  8. S Gravel, 2012, Population Genetics Models of Local Ancestry, Genetics, 191, 607, 10.1534/genetics.112.139808 · DOI · Paper page
  9. FT Juster, 1995, An Overview of the Health and Retirement Study, The Journal of Human Resources, 30, S7, 10.2307/146277 · DOI · Paper page
  10. LB Signorello, 2005, Southern community cohort study: establishing a cohort to investigate health disparities, Journal of the National Medical Association, 97, 972
  11. A Gullickson, 2006, Black/White Interracial Marriage Trends, 1850–2000, Journal of Family History, 31, 289, 10.1177/0363199006288393 · doi:10.1177/0363199006288393
  12. L Fejerman, 2014, Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25, Nature Communications, 5, 5260, 10.1038/ncomms6260 · DOI
  13. S Ramachandran, 2005, Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa, Proceedings of the National Academy of Sciences, 102, 15942, 10.1073/pnas.0507611102 · DOI · Paper page
  14. 2014, Whole-genome sequence variation, population structure and demographic history of the Dutch population, Nature Genetics, 46, 818, 10.1038/ng.3021 · DOI · Paper page
  15. PF Palamara, 2012, Length Distributions of Identity by Descent Reveal Fine-Scale Demographic History, The American Journal of Human Genetics, 91, 809, 10.1016/j.ajhg.2012.08.030 · DOI · Paper page
  16. WD Koenig, 1988, Internal Migration in the Contemporary United States: Comparison of Measures and Partitioning of Stages, Human Biology, 60, 927
  17. SR Browning, 2012, Detecting Rare Variant Associations by Identity-by-Descent Mapping in Case-Control Studies, Genetics, 190, 1521, 10.1534/genetics.111.136937 · DOI
  18. S Turner, 2011, Quality Control Procedures for Genome-Wide Association Studies, Current Protocols in Human Genetics, 68, 1.19.1, 10.1002/0471142905.hg0119s68 · DOI · Paper page
  19. O Delaneau, 2012, Improved whole-chromosome phasing for disease and population genetic studies, Nature Methods, 10, 5, 10.1038/nmeth.2307 · DOI · Paper page
  20. A Gusev, 2009, Whole population, genome-wide mapping of hidden relatedness, Genome Research, 19, 318, 10.1101/gr.081398.108 · DOI · Paper page
  21. EY Durand, 2014, Reducing Pervasive False-Positive Identical-by-Descent Segments Detected by Large-Scale Pedigree Analysis, Molecular Biology and Evolution, 31, 2212, 10.1093/molbev/msu151 · DOI
  22. DF Conrad, 2006, A worldwide survey of haplotype variation and linkage disequilibrium in the human genome, Nature Genetics, 38, 1251, 10.1038/ng1911 · DOI · Paper page
  23. DH Alexander, 2009, Fast model-based estimation of ancestry in unrelated individuals, Genome Research, 19, 1655, 10.1101/gr.094052.109 · DOI · Paper page
  24. X Zheng, 2012, A high-performance computing toolset for relatedness and principal component analysis of SNP data, Bioinformatics, 28, 3326, 10.1093/bioinformatics/bts606 · DOI · Paper page

Cited by

See all 176

Metadata

Authors
Baharian, S., Barakatt, M., Gignoux, C. R., Shringarpure, S., Errington, J., Blot, W. J., Bustamante, C. D., Kenny, E. E., Williams, S. M., Aldrich, M. C., & Gravel, S.
Venue
PLOS Genetics
Published
2016-05-27
Volume
12
Issue
5
Pages
e1006059
ISSN
  • 1553-7390 (ISSN-L)
  • 1553-7404
OpenAlex
W2408170490
Cited by
176
References
8
FWCI
16.63
Type
journal article
Language
en
Open access
gold
Funders
  • Canadian Institutes of Health Research (MOP-136855)
  • National Science Foundation (1201234)
  • National Institutes of Health (K07 CA172294)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The Great Migration and African-American Genomic Diversity. https://app.cochat.ai/papers/10.1371/journal.pgen.1006059
The paper
Baharian, S., Barakatt, M., Gignoux, C. R., Shringarpure, S., Errington, J., Blot, W. J., Bustamante, C. D., Kenny, E. E., Williams, S. M., Aldrich, M. C., & Gravel, S. (2016). The Great Migration and African-American Genomic Diversity. PLOS Genetics. https://doi.org/10.1371/journal.pgen.1006059

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.