Dataset and Code for "Predicting CircRNA-disease Associations through Linear Neighborhood Label Propagation Method"

Dataset

Dataset1

• Dataset1/association.csv is the circRNA-disease association matrix of Dataset1, which contains 331 associations between 312 circRNAs and 40 diseases.
• Dataset1/all_circRNAs.csv contains all the circRNAs, corresponding to the rows of the association matrix.
• Dataset1/all_diseases.csv contains all the diseases, corresponding to the columns of the association matrix.

Dataset2

• Dataset2/association.csv is the circRNA-disease association matrix of Dataset2, which contains 650 associations between 603 circRNAs and 88 diseases.
• Dataset2/all_circRNAs.csv contains all the circRNAs, corresponding to the rows of the association matrix.
• Dataset2/all_diseases.csv contains all the diseases, corresponding to the columns of the association matrix.

Code

• case_study.py calculates score matrices of case studies on Dataset1 and Dataset2 respectively.

• LNLP_method.py contains our method function, that is linear_neighbor_predict.

• LNLP_evaluation.py implements LOOCV of CD-LNLP on Dataset1.

Result

• case_study_scores

  • Dataset1_scores.csv is the score matrix of case study on Dataset1.
  • Dataset2_scores.csv is the score matrix of case study on Dataset2.

• Dataset1_result/disease

  For every disease in Dataset1, the candidate circRNAs are in the text file named as the disease's name in Dataset1_result/disease folder in descending order of score.

• Dataset2_result/disease

  For every disease in Dataset2, the candidate circRNAs are in the text file named as the disease's name in Dataset2_result/disease folder in descending order of score.

• evaluation_result/loocv

  evaluation_result/loocv contains our method's evaluation result on LOOCV.

  • 0.1_0.9_1.0_loo.csv contains the values of 6 metrics.
  • 0.1_0.9_1.0_loo_pr_x.csv contains the values of recall on different thresholds.
  • 0.1_0.9_1.0_loo_pr_y.csv contains the values of precision on different thresholds.
  • 0.1_0.9_1.0_loo_roc_x.csv contains the values of False Positive Rate on different thresholds.
  • 0.1_0.9_1.0_loo_roc_y.csv contains the values of True Positive Rate on different thresholds.