SNIPar (single nucleotide imputation of parents) is a python library for imputing missing parental genotypes from observed sibling and parental genotypes, and for performing robust GWAS using the resulting imputed parental genotypes
Impute the expected sum of maternal and paternal genotypes given genotype data on the sibling offspring of the parents and IBD sharing between the sibling offspring
Imputes the expected genotype of the missing parent given a parent-offspring pair, or a parent and multiple full sibling offspring along with the shared IBD segments of those offspring.
Performs robust GWAS using observed and imputed parental genotypes along with observed proband genotypes (fGWAS.py script).
Computes PGS values for probands and parents from SNP weights using observed/imputed parental genotypes; analyse the direct and parental effects of the PGS on traits (fPGS.py).
The fGWAS.py and fPGS.py scripts use a random effects model to model phenotypic correlations between siblings.
Documentation for the modules and scripts is at: https://sibreg.readthedocs.io/en/master/
It is recommended to read the guide: https://sibreg.readthedocs.io/en/master/guide.html
And to work through the tutorial: https://sibreg.readthedocs.io/en/master/tutorial.html
SNIPar has the following dependencies:
python 3.7
Packages:
- numpy
- scipy
- pysnptools
- pandas
- networkx
- Cython
We highly recommend using a python distribution such as Anaconda 3 (https://store.continuum.io/cshop/anaconda/). This will come with both numpy and scipy installed and can include an MKL-compiled distribution for optimal speed.
To install from source, clone the git repository, and in the directory containing the SNIPar source code, at the shell type
'python setup.py install'
To check that the code is working properly and that the C modules have compiled, you should run tests. To run the tests, in the main SNIPar directory enter the command:
``python setup.py pytest``