Smith-Waterman Algorithm for CB&B 752: Biomedical Data Science: Mining and Modeling
Python3 is required.
The script can be directly downloaded from Github using the following commands:
git clone https://github.com/dingyaozhang/SWAlgorithm.git cd SWAlgorithm
You could directly use hw1.py in the folder.
If you want to install the package in the python:
pip install git+https://github.com/dingyaozhang/SW_Algorithm.git
If you directly download the script folder, you could use it directly
python hw1.py -i <input file> -s blosum62.txt # if you have your own substitution matrix file, you could change blosum62.txt. # you could use > to output data to a file.
You could try the sample data:
python hw1.py -i tests/input.txt -s blosum62.txt > output.txt python hw1.py -i tests/sample-input1.txt -s blosum62.txt > output1.txt diff -E -b output1.txt tests/sample-output1.txt #compare with standard results python hw1.py -i tests/sample-input2.txt -s blosum62.txt > output2.txt diff -E -b output2.txt tests/sample-output2.txt #compare with standard results
If you install the package in the python, then in the command line:
python -c "from SWAlgorithm.hw1 import runSW;runSW('<input file>','blosum62.txt',-2,-1)" > output.txt
You could try the sample data:
python -c "from SWAlgorithm.hw1 import runSW;runSW('tests/input.txt','blosum62.txt',-2,-1)" > output.txt python -c "from SWAlgorithm.hw1 import runSW;runSW('tests/sample-input1.txt','blosum62.txt',-2,-1)" > output1.txt diff -E -b output1.txt tests/sample-output1.txt #compare with standard results python -c "from SWAlgorithm.hw1 import runSW;runSW('tests/sample-input2.txt','blosum62.txt',-2,-1)" > output2.txt diff -E -b output2.txt tests/sample-output2.txt #compare with standard results
You could also use it in python like:
import sys sys.stdout = open('file.txt', 'w') from SWAlgorithm.hw1 import runSW runSW('tests/input.txt','blosum62.txt',-2,-1) sys.stdout.close()
Usage: python hw1.py -i <input file> -s <score file> [OPTION...] input file (-i --input): The name of input file. score file (-s --score): The name of score file. Options (need to include values after the option switches): --opengap: The number of open gap penalty used. Default is -2. --extgap: The number of extension gap penalty used. Default is -1.
For installation by pip:
Usage: runSW('<input file>','<score file>',opengap,extgap) python hw1.py -i -s blosum62.txt [OPTION...] input file: The name of input file. score file: The name of score file. opengap: The number of open gap penalty used. We suggest to use -2. extgap: The number of extension gap penalty used. We suggest to use -1.
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Note: Smith-Waterman Algorithm for CB&B 752: Biomedical Data Science: Mining and Modeling
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