Genotype imputation using Bidirectional Recurrent Neural Network

Authors: Deepak Muralidharan and Manikandan Srinivasan

Course project for CM229 (Instructor: Prof Sriram Sankararaman)

The folder contains the code for the following methods:

Bidirectional Recurrent Neural Network for Diploid/Haploid genotype data. (bi_haploid_training, bi_diploid_training, bi_haploid_testing, bi_diploid_testing)
Unidirectional Recurrent Neural Network for Diploid/haploid genotype data. (uni_haploid_training, uni_haploid_testing)
Robust PCA based imputation method for Diploid/haploid genotype data. (robust_pca_main.m)

For any queries, contact: Deepak Muralidharan (deepakmuralidharan2308@gmail.com) or Manikandan Srinivasan (manikandandav@gmail.com)

Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
Mendel_Impute_benchmark		Mendel_Impute_benchmark
data		data
icons		icons
old_files		old_files
old_weights		old_weights
results		results
weights		weights
.gitignore		.gitignore
README.md		README.md
bi_diploid_testing.py		bi_diploid_testing.py
bi_diploid_testing_rough.py		bi_diploid_testing_rough.py
bi_diploid_testing_sampling.py		bi_diploid_testing_sampling.py
bi_diploid_testing_sampling_multipos.py		bi_diploid_testing_sampling_multipos.py
bi_diploid_testing_sampling_multipos_2.py		bi_diploid_testing_sampling_multipos_2.py
bi_diploid_training.py		bi_diploid_training.py
bi_haploid_testing.py		bi_haploid_testing.py
bi_haploid_training.py		bi_haploid_training.py
cm229-final-presentation.pdf		cm229-final-presentation.pdf
cm229-final-report.pdf		cm229-final-report.pdf
ground.p		ground.p
plotting.py		plotting.py
predicted.p		predicted.p
uni_diploid_testing.py		uni_diploid_testing.py
uni_diploid_testing_rough.py		uni_diploid_testing_rough.py
uni_diploid_training.py		uni_diploid_training.py
uni_haploid_testing.py		uni_haploid_testing.py
uni_haploid_training.py		uni_haploid_training.py