A computational method to predict and scan IL-5 inducing peptides.
IL5pred is developed to predict, scan, and design IL-5 inducing peptides. More information on IL5pred web server is available at https://webs.iiitd.edu.in/raghava/il5pred. Please read/cite the content about the IL5pred for complete information including the algorithm behind the approach.
The best Random Forest-based hybrid model (RF(DPC)+BLAST) is implemented in the webserver.
Standalone version of IL5pred is written in python3 and the following libraries are necessary for a successful run:
- scikit-learn
- Pandas
- Numpy
- blastp
To know about the available option for the standalone, type the following command:
python il5pred.py -h
To run the example, type the following command:
python3 il5pred.py -i example_input.fa
This will predict if the submitted sequences are IL-5 inducers or Non-inducers. It will use other parameters by default. It will save the output in "outfile.csv" in CSV (comma-separated variables).
Following is complete list of all options, you may get these options
usage: il5pred.py [-h]
[-i INPUT]
[-o OUTPUT]
[-j {1,2,3}]
[-t THRESHOLD]
[-w {9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25}]
[-d {1,2}]
Please provide the following arguments
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input: protein or peptide sequence(s) in FASTA format
or single sequence per line in a single letter code
-o OUTPUT, --output OUTPUT
Output: File for saving results by default outfile.csv
-j {1,2,3}, --job {1,2,3}
Job Type: 1:Predict, 2: Design, 3:Scan, by default 1
-t THRESHOLD, --threshold THRESHOLD
Threshold: Value between 0 to 1 by default 0.21
-w {9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25}, --winleng {9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25}
Window Length: 9 to 20 (scan mode only), by default 9
-d {1,2}, --display {1,2}
Display: 1:IL-5 inducing peptides only, 2: All peptides, by default 1
Input File: Allows user to provide input in FASTA format.
Output File: Program will save the results in CSV format, in case the user does not provide the output file name, it will be stored in "outfile.csv".
Threshold: User should provide a threshold between 0 and 1, by default it's 0.21.