Use Cases¶
Is SimPrily right for your research?
Use case | Can SimPrily be used? | Notes | |
---|---|---|---|
Type of simulation | Coalescent simulation | yes | |
Forward simulation | no | ||
Model | Selection | no | |
Demographic model | yes | See MaCS/ms documentation | |
Recombination map | yes | Not necessary, but sims will be more accurate | |
Constant mutation rate | yes | ||
Constant model parameters | yes | ||
Uniform priors of parameters | yes | ||
Non-uniform priors | no | ||
Known SNP ascertainment | yes | ||
Unknown SNP ascertainment | yes | See Quinto-Cortes et al. (2018) | |
Size of simulation | Chromosome-size loci | yes | |
Whole genome | no | Must simulate each chromosome separately | |
1000’s of samples | no | Try msprime | |
Type of simulated data | Sequence (variant) data | yes | |
Exome data | yes | ||
SNP array data | yes | ||
Microsatellite/str data | no | ||
Returned data | AFS Summary statistics | yes | |
IBD Summary statistics | yes | Only with SNP array option | |
Raw simulated output | no | ||
PLINK ped/map output | yes | Only with SNP array option | |
Programing experience | None | yes | Use the Discovery Environment app |
Beginner command line | yes | Can use the Open Science Grid | |
Python | yes | Not necessary, but can add own functions and make pull requests |
If you still are not sure if SimPrily is right for your research check out other simulators at https://popmodels.cancercontrol.cancer.gov/gsr