trviz 0.1.2

A python library for decomposing and visualizing tandem repeat sequences

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

Full documentation is available at readthedocs

Overview of TRviz

Getting Started

Prerequisite

TRviz requires MAFFT.

Install the library with pip or from source.

with pip

pip install trviz

from source

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

Motivation

There have been many approaches to visualize the variations in tandem repeats. However, there is no tool available for that. TRViz automatically decompose tandem repeat sequence into motifs, and align the decomposed motifs, and finally generate a plot to show the aligned motifs.

Input

1. Tandem repeat sequences in FASTA format
2. A set of motifs for decomposition

Output

1. Motif map, a set of motifs detected in the samples and their labels and frequencies
2. Aligned and labeled motifs
3. Plot showing the motif composition of the input sequences
4. Plot mapping color to the motif sequences

Code samples and examples

TRviz has four modules:

1. Decomposition
2. Encoding
3. Alignment
4. Visualization

See full documentation at readthedocs

Generating a TR 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"]

Contact Us

Please submit an issue on the TRviz github