Function

On this page, we introduce all the functions and parameters in detail.

1. Check Blast Database

database_name    # input the target fasta database, and make sure it located in the current folder.

2. Make Database

database_name    # input the target fasta database, and make sure it has been checked in Check Blast Database function (1).
-o               # input the out database name, and it will be saved in rpct/blastDB.

3. Read

file_name    # input your Fasta datasets name, and you should make sure your file in the current folder.
-o           # input the out folder name, and it will be saved by default in /Reads.

4. Blast

folder_name    # input the Fasta folder name which has been created in Read function (3).
-db            # choose the blast database, or you can make your database through Make Database function (2).
-n             # input the iteration number.
-ev            # input the expected value.
-o             # input the out folder name, and it will be saved by default in PSSMs folder.

5. Extract

folder_name     # input the two PSSM folders name which has been created in Blast function (4).
-raa            # raac book saved in raacDB folder in rpct, and you can not use this parameter and -r together.
-o              # if you choose the parameter -raa, you should input a folder name, and if you choose the parameter -r, you should input a file name.
-l              # input the window size for the RAAC-PSSM extraction method.
-r              # self_raa_code format should contain all amino acid types, and be separated by '-', for example: LVIMC-AGST-PHC-FYW-EDNQ-KR .

-d    # input the target feature file and output a single result of it, and you can not use this parameter and -f together.
-f    # input the target feature folder and output the Hyperparameters file which contains all results of the feature folder, and you can not use this parameter and -d together.

7. Train

-d     # input the target feature file, and you can not use this parameter with -f and -cg together.
-f     # input the feature folder, and you can not use this parameter with -d, -c and -g together.
-c     # the penalty coefficient of SVM, and you can not use this parameter with -f and -cg together.
-g     # the gamma of RBF-SVM, and you can not use this parameter with -f and -cg together.
-o     # if you choose the parameter -f, you should input a folder name, and if you choose the parameter -d, you should input a file name.
-cg    # the Hyperparameters file which has been created in Search function (6) or defined in Set Hyperparameters File function (16), and you can not use this parameter with -d, -c and -g together.

8. Evaluate

-d     # input the target feature file, and you can not use this parameter with -f and -cg together.
-f     # input the feature folder, and you can not use this parameter with -d, -c and -g together.
-c     # the penalty coefficient of SVM, and you can not use this parameter with -f and -cg together.
-g     # the gamma of RBF-SVM, and you can not use this parameter with -f and -cg together.
-o     # if you choose the parameter -f, you should input a folder name, and if you choose the parameter -d, you should input a file name.
-cg    # the Hyperparameters file which has been created in Search function (6) or defined in Set Hyperparameters File function (16), and you can not use this parameter with -d, -c and -g together.
-cv    # the cross validation fold of SVM, you can choose 5, 10 or -1 or define it by your experience.

9. ROC

document_name    # input the target feature file.
-c               # the penalty coefficient of SVM, you can get it through Search function (6) or define it by your experience, and you can not use this parameter with -f and -cg together.
-g               # the gamma of RBF-SVM, you can get it through Search function (6) or define it by your experience, and you can not use this parameter with -f and -cg together.
-o               # input the out file name, and the ROC-Cruve will be saved by defualt in current folder.

10. Filter

document_name    # input the target feature file name.
-c               # the penalty coefficient of SVM, you can get it through Search function (6) or define it by your experience.
-g               # the gamma of RBF-SVM, you can get it through Search function (6) or define it by your experience.
-cv              # the cross validation fold of SVM, you can choose 5, 10 or -1 or define it by your experience.
-o               # input the out folder name.
-r               # the random sampling number of Relief method.
-raac            # input the raac book name.
-t               # input the raac type and size.

11. Predict

document_name    # input the target feature file, and make sure it has the same reduce type with the target model.
-m               # input the target model file, and make sure it has the same reduce type with the target feature file.
-o               # input the out file name, and the predict result will be saved by defualt in current folder.

12. Filter-feature-file set

document_name    # input the target feature file which has been chosen in Filter function (10).
-f               # input the Feature_Sort_File which has been created in Filter function (10).
-n               # the stop feature number of target feature file, and you can find it in the ACC_Chart which has been created in Filter function (10).
-o               # input the out file name.

13. Self Reduce Amino Acids Code

aaindex_id    # the ID of physical and chemical characteristics in AAindex Database, and you can check it in /rpct/aaindexDB or view it online.

14. Integrated Learning

-tf    # input the train feature folder name.
-pf    # input the predict feature folder name which has been created by an independent datasets.
-ef    # input the eval result file name which has been created by Evaluate funtion (8) and saved in eval_result folder.
-cg    # the Hyperparameters file which has been created in Search function (6) or defined in Set Hyperparameters File function (16).
-m     # the number of integrated-learning members.

15. Principal Component Analysis

document_name    # input the feature file name.
-c               # the penalty coefficient of SVM, you can get it through Search function (6) or define it by your experience, and you can not use this parameter with -f and -cg together.
-g               # the gamma of RBF-SVM, you can get it through Search function (6) or define it by your experience, and you can not use this parameter with -f and -cg together.
-o               # input the out folder name.
-cv              # the cross validation fold of SVM, you can choose 5, 10 or -1 or define it by your experience.

16. Set Hyperparameters File

folder_name    # input the train feature folder name.
-c             # the penalty coefficient of SVM.
-g             # the gamma of RBF-SVM.
-o             # input the out file name, and the Hyperparameters file will be saved by defualt in current folder.

17. Ray Blast

folder_name    # input the target fasta folder which has been created in Read function (3).
-o             # input the out folder name, and the folder saved by default in /PSSMs.

18. Ray Supplement

folder_name    # input the target fasta folder which has been created in Read function (3).
-o             # input the out folder name, and the folder saved by default in /PSSMs.

19. View

raac_book_name    # input the target RAAC book name.
-t                # input the target type which you want to view.

pssm_file_name    # input the target pssm file path.
-raa              # input the target RAAC book name.
-r                # input the target reduce type
-o                # input the out file name, and the file saved by default in current folder.