This is a method can be used for estimating the time of admixture in low coverage ancient genomes. Details of the method and algorithm can be found in Narasimhan et al. 2019. Download code from here.
Variation in molecular clock in primates
Multiple sequence alignments used in this study can be downloaded from here. Download code from here. For details of the methods and analysis, see Moorjani, Amorim et al. 2016 PNAS.
This is a method for estimating the date of Neanderthal gene flow using a single diploid genome. The main idea is to measure the extent of covariance in Neanderthal ancestry present in modern human genome to estimate the time of the Neanderthal gene flow. Details of the method and algorithm can be found in Moorjani et al. 2016 and Fu et al. 2014. Download code from here.
This simulator can be used for generating admixed genomes. As input the method takes phased data from two populations and generates admixed individuals for a given time of admixture and proportion of ancestry from each population. Method assumes instantaneous admixture but to generate data for multiple pulses or continuous admixture, one can run the same code in a loop. Details of the method can be found in Moorjani et al. 2011. For new implementation download code from here.
Rolloff: Method for dating admixture
For dating admixture in contemporary populations, one can use Rolloff which is available here. Details of the method and statistic can be found in Moorjani et al. 2013. This method was first introduced in Moorjani et al. 2011 and distributed as part of ADMIXTOOLS software package. The latest implementation is more reliable and robust to biases that can be introduced due to strong founder events that may postdate admixture.
South Asia genotype data
The genotype data used in Moorjani et al. (2013) Genetic Evidence for Recent Population Mixture in India is available upon request (due to the nature of the study consent, it is only available for population genetics studies). If interested in accessing this data, please email the corresponding authors with a signed letter (with your contact information) stating the following:
I affirm that
· The data will not be posted publicly.
· It will not be secondarily distributed to other people outside this collaboration.
· There will be no attempt to connect the data back to identifying information from any individuals in the study.