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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.
Quick Start
Prerequisites
- Python 3.10+ (3.10, 3.11, or 3.12 are tested)
- MAFFT (for multiple sequence alignment) — install from MAFFT website. Tested with v7.505.
Install
pip install trviz
Or from source:
git clone https://github.com/Jong-hun-Park/trviz.git
cd trviz/
pip install .
Run your first analysis
Check out our Jupyter notebook for code examples.
Features Overview
Input and output
Input
- Tandem repeat sequences (alleles)
- A set of motifs for decomposition
Output
- A plot showing the motif composition of the input sequences (PDF by default)
- A plot mapping color to motif (PDF by default)
- Aligned and labeled motifs (text file)
- Motif map: a set of motifs detected in the samples and their labels and frequencies (text file)
For more detailed descriptions, see the full documentation at readthedocs.
Code examples
Generate a plot (saves to disk)
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)
Customize the plot via matplotlib (v1.4.0+)
generate_trplot() and the underlying trplot() / plot_motif_color_map() now return (fig, ax),
so you can apply any matplotlib styling — fonts, ticks, titles, layout — before saving the figure
yourself.
fig, ax = tr_visualizer.generate_trplot(
tr_id, sample_ids, tr_sequences, motifs,
save=False, # skip the built-in savefig
)
# Apply any matplotlib styling you want:
ax.set_title("CACNA1C VNTR composition", fontsize=14)
ax.tick_params(axis="x", labelsize=12)
ax.set_xlabel("Repeat unit", fontsize=12)
fig.savefig("CACNA1C.pdf", dpi=300, bbox_inches="tight")
You can also draw the plot into your own ax (useful for embedding in a multi-panel figure):
import matplotlib.pyplot as plt
fig, axes = plt.subplots(1, 2, figsize=(16, 6))
tr_visualizer.visualizer.trplot(
aligned_labeled_repeats=aligned_trs,
sample_ids=sorted_sample_ids,
symbol_to_motif=symbol_to_motif,
ax=axes[0], # draw into your own axes
sort_by_clustering=False,
)
# ... draw something else into axes[1] ...
fig.savefig("multi_panel.pdf")
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.
1 maintainer
Metadata
1 maintainer
Release files for trviz 1.4.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| trviz-1.4.2.tar.gz | 796.0 kB | Details |
Built distributions (wheels)
Total release size: 4.2 MB
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