Skip to content

Latest commit

 

History

History
15 lines (10 loc) · 832 Bytes

README.md

File metadata and controls

15 lines (10 loc) · 832 Bytes
Raw

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)