Rees, Jasmin;
Andrés, Aida;
(2022)
Inferring human evolutionary history.
Science
, 375
(6583)
pp. 817-818.
10.1126/science.abo0498.
Preview |
Text
Rees_Andres_manuscript.pdf - Accepted Version Download (301kB) | Preview |
Abstract
Genomes are invaluable tools for inferring the demographic and adaptive history of human populations, including migrations, population splits, admixture, and genetic adaptations. Growing datasets of modern and ancient genomes make this possible, but their massive size comes with important challenges, demanding techniques that analyze immense amounts of data in reasonable amounts of time while using as much information as possible. Combining genomes from different datasets poses perhaps an even greater challenge, especially when it comes to integrating ancient and modern genomes. On page 836 of this issue, Wohns et al. (1) report surmounting some of these challenges to construct the largest human genealogy to date, integrating modern and ancient genomes from multiple datasets to infer key events in human history together with their timings and geographical locations.
| Type: | Article |
|---|---|
| Title: | Inferring human evolutionary history |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1126/science.abo0498 |
| Publisher version: | https://doi.org/10.1126/science.abo0498 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159352 |
Archive Staff Only
 |
View Item |
