Simgenotype: Understanding Haplotype Frequencies And Admixture

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Simgenotype: Understanding Haplotype Frequencies and Admixture

Hey guys! Today, we're diving deep into the simgenotype function within haptools. This nifty tool is super useful for simulating genotypes, especially when you're dealing with admixed populations. We're going to break down some common questions and confusions that might pop up when you're trying to get your simulations just right. Let's get started!

Understanding Frequencies in the .dat File

Let's kick things off by demystifying the .dat file. The big question: are the frequencies you input in this file for haplotypes or for the entire population? This is a crucial distinction, especially when you're trying to simulate admixed offspring.

Imagine this scenario: you've got a population of 7 individuals – two sets of grandparents, one set of parents, and one child. One set of grandparents is of CEU ancestry, and the other is of YRI ancestry. Naturally, the parents will have a mix of these ancestries, and the child will be admixed. So, how do you tell simgenotype about this?

Here's where things can get a bit confusing. The documentation mentions both haplotype frequencies and population frequencies. So, what's the deal? Well, the .dat file requires haplotype frequencies. This means you're specifying the frequency of each haplotype within the simulated population.

Now, consider this: if you're only looking at the first three generations (grandparents, parents, and the child), the frequency of admixed individuals might be zero, especially if the child hasn't reproduced yet. So, if you want to see any admixture, do you need to add a fourth generation? The answer is yes, you likely need to simulate additional generations to observe the effects of admixture fully. By adding more generations, you allow for recombination and the creation of new admixed haplotypes, making your simulation more realistic.

Let's look at those .dat file examples you provided:

14 Admixed CEU YRI
1 0 0.5 0.5
2 0 0.5 0.5
3 0.1428 0.4286 0.4286

And:

14 Admixed CEU YRI
1 0 0.5 0.5
2 1 0 0
3 0 0.5 0.5
4 0.072 0.464 0.464

The first example seems to be setting initial haplotype frequencies where 'Admixed' is a possible ancestry but has low initial representation. The second example includes an entry where an individual is purely CEU, which might be useful for establishing the baseline ancestries before admixture occurs.

In summary, when setting up your .dat file, focus on the haplotype frequencies and consider how many generations you need to simulate to accurately represent the admixture process. Don't forget that the more generations you simulate, the more realistic your admixed population will be.

Deciphering the simgenotype Command Output

Now, let's tackle the second part of your question, which revolves around the output you see when running the simgenotype command. You ran something like this:

haptools simgenotype --model model3.dat --mapdir $SCRATCH/haptools/ --ref_vcf Test.vcf.gz --sample_info 1000genomes_sampleinfo.tab --region 22:17000000-17005000 --verbosity DEBUG --out 100_Admixed.vcf

And you noticed this in the output:

[ DEBUG|10:47:56] Filtered sample info to limit populations within model file. Populations: ['Admixed', 'CEU', 'YRI']. (sim_genotype.py:96)

So, what does this mean? Does it mean you need to specify "Admixed" individuals in your sample file based on a random combination of CEU and YRI ancestry? Let's break it down.

The short answer is no, not exactly.

Here's what's happening: the simgenotype tool is filtering your sample info file (1000genomes_sampleinfo.tab) to only include the populations that are specified in your model file (model3.dat). In this case, those populations are 'Admixed', 'CEU', and 'YRI'. This filtering step ensures that the tool only considers individuals from these populations when it's building its model.

The key here is understanding that simgenotype will simulate "Admixed" ancestry based on the proportions you define in your model3.dat file. It uses the genotype data from the CEU and YRI samples in your sample info file to create the admixed individuals. It doesn't require you to pre-define admixed individuals in your sample file.

Think of it this way: You're providing simgenotype with the raw materials (CEU and YRI genotypes) and the recipe (the proportions in model3.dat). The tool then mixes these ingredients according to the recipe to create the admixed individuals.

However, there's a subtle but important point here. If you do want to create a larger simulated dataset with varying ancestry proportions, you might consider adding some pre-defined admixed individuals to your sample file. This can help the tool learn more complex patterns of admixture and generate more realistic simulations. But it's not strictly necessary.

So, to clarify:

  • You don't need to specify admixed individuals in your sample file for the basic simulation to work.
  • Simgenotype simulates admixed ancestry based on the proportions in your .dat file and the genotypes from your specified populations.
  • If you want more complex simulations, consider adding some pre-defined admixed individuals to your sample file.

Optimizing Your Simgenotype Simulations

To really nail your simgenotype simulations, consider these extra tips:

  1. Fine-tune your .dat file: Experiment with different haplotype frequencies to see how they affect the resulting admixed population. Pay special attention to the initial frequencies and how they evolve over generations.
  2. Play with sample sizes: The more samples you include in your sample info file, the more accurate your simulations will be. However, be mindful of computational resources, as larger sample sizes can increase processing time.
  3. Explore different regions: Simulate genotypes across different regions of the genome to see how admixture patterns vary. This can provide valuable insights into the genetic history of your simulated population.
  4. Use realistic recombination rates: Make sure you're using accurate recombination rates for your simulated region. This can significantly impact the patterns of admixture you observe.

By keeping these tips in mind, you'll be well on your way to creating realistic and informative simgenotype simulations. Happy simulating!

Conclusion

Alright, that's a wrap! We've covered a lot of ground today, from understanding haplotype frequencies in the .dat file to deciphering the simgenotype command output. Remember, the key to successful simulations is understanding the underlying principles and experimenting with different parameters. With a little practice, you'll be a simgenotype pro in no time!

Keep experimenting, keep learning, and most importantly, keep having fun with your research. You've got this! And as always, feel free to reach out if you have more questions. We're here to help you on your genomics journey. Peace out!