_______ _______      _______ ______
 |__   __|  __ \ \    / /_   _|___  /
    | |  | |__) \ \  / /  | |    / / 
    | |  |  _  / \ \/ /   | |   / /  
    | |  | | \ \  \  /   _| |_ / /__ 
    |_|  |_|  \_\  \/   |_____/_____|

TRviz is a python library for analyzing tandem repeat sequences. TRviz includes modules for decomposing, encoding, aligning, and visualizing tandem repeat sequences.

Quick Start

Prerequisite

Note Before getting started, ensure you have MAFFT. The current version is tested with MAFFT v7.505.

Step 1: Install TRviz

# Install with pip
pip install trviz

or

# Install from source
git clone https://github.com/Jong-hun-Park/trviz.git
cd trviz/
pip install .

Step 2: Run Your First Analysis

Check out our Jupyter Notebook for code examples and start visualizing tandem repeat sequence right away!

Features Overview

Installation

Use pip for a quick installation, or install from source for more control.

pip install trviz

or

# Install from source
git clone https://github.com/Jong-hun-Park/trviz.git
cd trviz/
pip install .

Input and Output

Input

1. Tandem repeat sequences (alleles)
2. A set of motifs for decomposition

Output

1. A plot showing the motif composition of the input sequences (pdf by default)
2. A plot mapping color to motif (pdf by default)
3. Aligned and labeled motifs (text file)
4. Motif map, a set of motifs detected in the samples and their labels and frequencies (text file)

For more detailed descriptions, please see full documentation at readthedocs

Code examples

Generating a plot

from trviz.main import TandemRepeatVizWorker
from trviz.utils import get_sample_and_sequence_from_fasta

tr_visualizer = TandemRepeatVizWorker()
sample_ids, tr_sequences = get_sample_and_sequence_from_fasta(fasta_file_path)
tr_id = "CACNA1C"
motifs = ['GACCCTGACCTGACTAGTTTACAATCACAC']

tr_visualizer.generate_trplot(tr_id, sample_ids, tr_sequences, motifs)

Motif decomposition

from trviz.decomposer import Decomposer

tr_decomposer = Decomposer()
tr_sequence = "ACCTTGACCTTGACCTTGACCTTG"
motifs = ["ACCTTG"]
tr_decomposer.decompose(tr_sequence, motifs)
# >>> ["ACCTTG", "ACCTTG", "ACCTTG", "ACCTTG"]

Citation:

Jonghun Park, Eli Kaufman, Paul N Valdmanis, Vineet Bafna, TRviz: a Python library for decomposing and visualizing tandem repeat sequences, Bioinformatics Advances, Volume 3, Issue 1, 2023, vbad058

Contribute

Your feedback is valuable! If you encounter any issues during installation or usage, please submit them in the TRviz GitHub Issues.