Update README.md

README.md

@@ -7,9 +7,43 @@ Our method can be divided into two components: extracting signals of interest fr
 
 # Signal Extraction
 
-The raw fast5 files for all 77 tetramers are stored in [link]. We also store the final results after signal extraction step as `npy` files in [link].
+The ONT (Oxford   Nanopore Technologies) raw fast5 files for all 77 tetramers are stored in [link]. We also store the final results after signal extraction step as `npy` files in [link].
 
 The overall pipeline of this component is shown in the following figure. Please refer to **Figure S6** for more details.
 
 ![image info](./signal_extraction_pipeline.png)
 
+To use the code, you need to first download the fast5 files into some directory and set the following data path accordingly.
+```
+python signal_extraction.py --data_path="raw_fast5" --out_dir="processed_files/extracted_signals"
+
+python build_dataset.py --data_path="processed_files/extracted_signals" --pool_path="raw_fast5" 
+                        --out_path="processed_files/dataset" --std_thres_ub=10.0
+```
+
+# Classification
+
+With the built dataset, we are ready to perform classification with deep learning to achieve high classification accuracy.
+
+### Classification over 66 patterns
+```
+python main_allclass_convplus.py --data_path="processed_files/dataset/"
+                                 --lr=1e-3 --test_ratio=0.4 --batch_size=256 
+                                 --max_epoch=200 --early_stop=25
+                                 --chkpt="./chkpt/convplus/allclass_1e-3" 
+                                 --max_sample=3500 --num_trails=1
+```
+**Confusion Matrix**
+![image info](./all_class_cm.png)
+
+### Classification over permutation groups
+```
+python main_usecase_resnet1d.py --data_path="processed_files/dataset/"
+                                --lr=1e-3 --test_ratio=0.4 --batch_size=64 
+                                --max_epoch=400 --early_stop=50
+                                --chkpt="./chkpt/resnet1d/U2_1e-3" 
+                                --max_sample=5000 --num_trails=1
+                                --usecase_short="U2" --model_param="[64,4,1,2]"
+```
+**Confusion Matrix**
+![image info](./usecase_cm.png)