Imputation tool for missing genotype data in model and non-model species
Please cite: O. Choudhury, A. Chakrabarty, S. Emrich. Highly Accurate and Efficient Data-Driven Methods For Genotype Imputation. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2017
ADDIT-NM Dependencies:
Python 2.7.5 or higher
Running ADDIT-NM:
usage: python Addit_NM.py [-h] -i INPUT -o OUTPUT [-w WINDOW] [-t SIMILARITY_THRESHOLD] [-sh SIMILARITY_HIGH] [-sl SIMILARITY_LOW] [-fh FREQUENCY_HIGH] [-fl FREQUENCY_LOW]
Example: python Addit_NM.py -i Test_Nonmodel_Missing.txt -o Test_Nonmodel_Imputed.txt
ADDIT-M Dependencies:
NumPy (v1.11.3) Scikit-Learn (v0.18.1)
Running ADDIT-M:
Test_Model_Training.zip has to be unzipped. It contains the txt file.
usage: python Addit_M.py [-h] -i INPUT -tr TRAIN -o OUTPUT [-w WINDOW]
Example: python Addit_M.py -i Test_Model_Missing.txt -tr Test_Model_Training.txt -o Test_Model_Imputed.txt
Contact: semrich@nd.edu