treasureisland 1.0.3

Prediction of Genomic Islands

TreasureIsland

TreasureIsland python package is a machine learning-based Genomic Island prediction software, that uses an unsupervised representation of DNA for its prediction.

TreasureIsland was constructed from Benbow dataset.

Dependency :

Python >= 3.7

Installation:

Option1 - Use pip to install the package :

TreasureIsland can be installed by python package management system "pip" :

python -m pip install treasureisland

Option2 - Locally install package:

git clone https://github.com/priyamayur/GenomicIslandPrediction.git
python -m pip install -e GenomicIslandPrediction

Usage:

Option1 - Run TreasureIsland directly from commandline :

Run TreasureIsland from commandline on your DNA fasta file (example DNA files provided here), output is given in csv format:

python -m treasureisland <DNA file>     

Option2 - Run TreasureIsland from python :

The TreasureIsland package is used to find genomic island predictions which can be downloaded in csv, xlsx, txt file formats demonstrated in TreasureIsland package

Input file:

DNA sequence files in fasta format with a sequenceID.

example: >NC_002620.2 Chlamydia muridarum str. Nigg, complete sequence CACATAGCAAAACACTCAAAGTTTTTCAGCAAAAAAGCTTGTTGAAAAAATTGTTGACCGCCTGTTCACA....

Performance:

TreasureIsland takes 2-5 mins to run depending on the size of the input.

Output :

The results are shown in the following format for each genomic island:

example : NC_002620.2 1.0 130000.0 0.95597

The sample outputs can be found in the repository folder 'output' -output_NC_002620.2.csv

Testing:

Repository contains some sample DNA files that can be downloaded to test the TreasureIsland. Note : github downloads fasta file in txt format (filename.fasta.txt).

example :

python -m treasureisland ecoli.fasta   

Running TreasureIsland package from python:

import the Predictor class from treasureisland package:

from treasureisland.Predictor import Predictor

Instantiate the sequence with the DNA sequence file path as the argument. The DNA file used can be a fasta or genbank file.

seq = Predictor("<Path to DNA fasta file>/bsub.fasta") 

Get prediction data frame from sequence by running the predict method.

pred = seq.predict()

The predictions can be downloaded in text, csv, excel formats.

seq.predictions_to_csv(pred)
seq.predictions_to_excel(pred)
seq.predictions_to_text(pred)

Contact:

Feel free to contact at [e-mail]