kgap.md

Feature Extraction Package for Biological Sequences Based on Mathematical Descriptors

Home • Key Features • List of files • Dependencies • Installing • How To Use • Citation

Preprocessing

Before executing any method in this package, it is necessary to run a pre-processing script, to eliminate any noise from the sequences (e.g., other letters as: N, K ...,). To use this script, follow the example below:

Important: This package only accepts sequence files in Fasta format as input to the methods.

To run the tool (Example): $ python3.7 preprocessing/preprocessing.py -i input -o output


Where:

-h = help

-i = Input - Fasta format file, e.g., test.fasta

-o = output - Fasta format file, e.g., output.fasta

Running:

$ python3.7 preprocessing/preprocessing.py -i dataset.fasta -o preprocessing.fasta 

Xmer k-Spaced Ymer Composition Frequency (kGap).

To use this model, follow the example below:

To run the code (Example): $ python3.7 methods/Kgap.py -i input -o output -l label -k kgap -bef before -aft after -seq type


Where:

-i = Input - Fasta format file, E.g., test.fasta

-o = Output - CSV format file, E.g., test.csv.

-l = label - lncRNA, circRNA...

-k = gap - e.g., Frequency of kgap, E.g. 1 = A_A, 2 = A__A, 3 = A___A...

-bef = before - e.g., 1 = A_A, 2 = AA_A, 3 = AAA_A...

-aft = after - e.g., 1 = A_A, 2 = A_AA, 3 = A_AAA...

-seq = type of sequence, e.g., 1 = DNA, 2 = RNA and 3 = Protein

Running:

$ python3.7 methods/Kgap.py -i sequences.fasta -o sequences.csv -l test -k 1 -bef 1 -aft 2 -seq 1

Note Input sequences for feature extraction must be in fasta format.

Note This example will generate a csv file with the extracted features.