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.. jupyter-execute::
:hide-code:
import set_working_directory
Information analysis of an alignment
====================================
Information here is in the formal sense -- maximum entropy minus the entropy at a position. This is fast to compute and is an indicator of the variability at a position.
Illustrated with a simple example
---------------------------------
.. jupyter-execute::
from cogent3 import load_aligned_seqs, make_aligned_seqs, make_seq
s1 = make_seq("TGATGTAAGGTAGTT", name="s1", moltype="dna")
s2 = make_seq("--CTGGAAGGGT---", name="s2", moltype="dna")
seqs = make_aligned_seqs(data=[s1, s2], array_align=False, moltype="dna")
draw = seqs.information_plot(window=2, include_gap=True)
draw.show(width=500, height=400)
On a sample data set
--------------------
Clicking on any of the legend items causes that to disappear from the plot.
.. jupyter-execute::
aln = load_aligned_seqs("data/brca1.fasta", moltype="protein")
fig = aln.information_plot(stat="median")
fig.show(width=500, height=400)
.. jupyter-execute::
:hide-code:
outpath = set_working_directory.get_thumbnail_dir() / "plot_aln-info-plot.png"
fig.write(outpath)
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