Example notebook

The tour notebook loads a 24-sequence protein alignment and explores it with the widgets. It computes p-distances and a neighbour-joining tree in plain Python, then links all three views.

View on GitHub Open in nbviewer

To run it, clone the repository and open packages/python/examples/tour.ipynb. Its data files sit next to it in data/.

pip install react-bio-viz jupyterlab
jupyter lab packages/python/examples/tour.ipynb

The screenshots below are from the notebook running in JupyterLab.

1. Explore an alignment

read_fasta loads the records and MSA shows them, here with conservation and logo tracks. Pan, zoom, select and drag labels as in the live examples.

2. Read, drive and observe state

The notebook reads msa.selection after you select something. It prints each new selection into an Output widget as it happens, and then drives the view from Python:

msa.viewport = {**msa.viewport, "x0": 100, "x1": 160}
msa.options = {**msa.options, "colorStyle": "AA Zappo"}
msa.selection = {"rows": [], "columns": list(range(120, 130))}

3. Edit

Rename, row-removal and column-removal callbacks apply each edit to msa.msa. Double-click a label to rename it, hover a label for its ×, or select columns and press Delete.

4. Distances, linked to the alignment

p-distances computed in Python go into a DistanceMatrix. One traitlets.link on row_order keeps it in step with the alignment.

5. A tree that orders the rows

A short neighbour-joining implementation turns the distances into a tree. traitlets.dlink from its leaf_order makes the alignment rows (and so the matrix) follow the tree. Drag a node to rotate it, or past the top or bottom to reroot. Clicks report the node, its leaves and its descendants to a Python callback.

6. Newick, and genes

to_newick and parse_newick round-trip the tree, and a GeneModel shows the transcripts, exons and CDSs of a gene.