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.. jupyter-execute::
:hide-code:
import set_working_directory
Counting gaps per sequence
==========================
We have several different ways of counting sequence gaps, and of visualising the results. By default, the ``count_gaps_per_seq()`` method returns a matrix of counts without the ability to visualise the results. When setting the argument ``unique=True``, the counts are for gaps uniquely induced by each sequence. This can be a useful indicator of highly divergent sequences.
.. jupyter-execute::
from cogent3 import load_aligned_seqs
aln = load_aligned_seqs("data/brca1.fasta", moltype="dna")
counts = aln.count_gaps_per_seq(unique=True)
counts[10: 20] # limiting the width of the displayed output
Plotting counts of unique gaps
------------------------------
Using the ``drawable`` argument causes the returned object to have a ``drawable`` attribute (type ``Drawable`` which has ``show()`` and ``write()`` methods), for the corresponding plot type. The three plot types supported are shown below. In all cases, placing the mouse pointer over a data point will show hover text with the number of unique gaps and the sequence name.
Displaying unique gaps as a bar chart
-------------------------------------
.. jupyter-execute::
counts = aln.count_gaps_per_seq(unique=True, drawable="bar")
counts.drawable.show(width=500)
.. jupyter-execute::
:hide-code:
outpath = set_working_directory.get_thumbnail_dir() / "plot_aln-gaps-per-seq.png"
counts.drawable.write(outpath)
Displaying unique gaps as a violin plot
---------------------------------------
.. jupyter-execute::
counts = aln.count_gaps_per_seq(unique=True, drawable="violin")
counts.drawable.show(width=300, height=500)
Displaying unique gaps as a box plot
------------------------------------
.. jupyter-execute::
counts = aln.count_gaps_per_seq(unique=True, drawable="box")
counts.drawable.show(width=300, height=500)
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