PSnoD codes for predicting snoRNA-disease association using matrix completion technique
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before running the program, be sure your system installed python version 3.6 plus
and packages:
pip install cvxpy
pip install matrix_completion
and sklearn, numpy, pandas, matplotlib, scipy
if you are only interested in BNNR, you could ignore matrix_completion and cvxpy installations.
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all codes lie in PSnoD_WorkFlow directory , you could import it
the program relies input_data, output_csv, output_images, the three directories.
check file main.py to find the usage
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if you are only interested in the BNNR completion method, and want to complete a matrix, please directly use:
from PSnoD_WorkFlow.BNNR import bnnr
completed_matrix, iterations = bnnr(matrix.to_numpy(), mask.to_numpy(), alpha=param_a, beta=param_b)
- where matrix is the a pandas dataframe object, and composed of disease matrix at left upper corner,
sonRNA matrix at right lower corner and relation matrix at right upper corner. - the mask matrix is as the same size with the matrix you need to be completed, but the element within it
is only 0 or 1, which 0 represent the relation is unknown, and 1 represent known - alpha and beta are hyperparameters