Programming_I_Leukemia_analysis

Course project bioinformatics programming I

Files description

• read_data.py is for read in data;
• getcox.py is to calculate the cox-score of each gene when the dataset is given; also report the histogram of the cox-scores of genes;
• f.py will get the cox-regression result in the test dataset, while the PCA model is built on train dataset with the qualified genes; those genes have cox-score > or equal than the given threshold
• change_col_names created a dictionary using V columns names as key and probes names as values.
• sampling_the_data.py will get the balanced 5 train/test folds based on key feature: MRD day 29; Age; WBC at diagnosis.
• 1_gene_expression.md testing R Markdown
• project_notebook.ipynb jupyter notebook showing the the read in dataframe and the cox-score histogram based on the 207 patients.
• get_5_testfolds.ipynb jupyter notebook showing how to do stratified resampling to get balanced 5 train/test datasets.