Investigating bilateral symmetry¶

This notebook uses cect, the C. elegans Connectome Toolbox, to investigate how bilateral symmetry in C. elegans changes over development. Source of this file on GitHub

1) Install the cect package using pip¶

If the package has not already been installed, use pip to install it.

In [1]:

!python -m pip install -q cect # use this line to install the latest version of cect from PyPI if you haven't already

print(f"cect version: {__import__('cect').__version__} is installed")

!python -m pip install -q cect # use this line to install the latest version of cect from PyPI if you haven't already print(f"cect version: {__import__('cect').__version__} is installed")

cect version: 0.3.4 is installed

2) Import methods from cect¶

In [2]:

# Helper method to load data sets by name
from cect.Utils import get_connectome_dataset       
# Helper method to apply a specific "view" (e.g. only sensory or motor neurons) to a connectome dataset
from cect.ConnectomeView import get_view    
# Method to convert a connectivity matrix into a binary array indicating symmetric connections
from cect.Analysis import convert_to_symmetry_array  
# Method to get clearer name for each reader
from cect.Comparison import get_improved_reader_name         

# Helper method to load data sets by name from cect.Utils import get_connectome_dataset # Helper method to apply a specific "view" (e.g. only sensory or motor neurons) to a connectome dataset from cect.ConnectomeView import get_view # Method to convert a connectivity matrix into a binary array indicating symmetric connections from cect.Analysis import convert_to_symmetry_array # Method to get clearer name for each reader from cect.Comparison import get_improved_reader_name

3) Specify connectomes to use, views to examine, and extract symmetry info¶

In [3]:

datareaders = ["Witvliet1", "Witvliet2", "Witvliet3", "Witvliet4", "Witvliet5", "Witvliet6",\
               "Yim2024", "WhiteJSH", "Witvliet7", "Witvliet8", "Cook2019Herm"]
views = ["SensorySomaticH", "MotorSomaticH", "MotorHeadSubLat", "InterneuronsSomaticH", \
         "Neurons"] 
synclass = "Chemical"

symmetries = {} # to store the bilateral symmetry indices of symmetric connections

for name in datareaders:
    cds = get_connectome_dataset(name, from_cache=True)

    for view in views:
        v = get_view(view) # get the ConnectomeView object for the current view name

        if v.name not in symmetries: symmetries[v.name] = []
        cds_viewed_array = cds.get_connectome_view(v) # limit to the neurons in this view

        conns, percent, sym_info = convert_to_symmetry_array(cds_viewed_array, [synclass])
        symmetries[v.name].append(percent/100)

datareaders = ["Witvliet1", "Witvliet2", "Witvliet3", "Witvliet4", "Witvliet5", "Witvliet6",\ "Yim2024", "WhiteJSH", "Witvliet7", "Witvliet8", "Cook2019Herm"] views = ["SensorySomaticH", "MotorSomaticH", "MotorHeadSubLat", "InterneuronsSomaticH", \ "Neurons"] synclass = "Chemical" symmetries = {} # to store the bilateral symmetry indices of symmetric connections for name in datareaders: cds = get_connectome_dataset(name, from_cache=True) for view in views: v = get_view(view) # get the ConnectomeView object for the current view name if v.name not in symmetries: symmetries[v.name] = [] cds_viewed_array = cds.get_connectome_view(v) # limit to the neurons in this view conns, percent, sym_info = convert_to_symmetry_array(cds_viewed_array, [synclass]) symmetries[v.name].append(percent/100)

4) Plot bilateral symmetry across datasets¶

In [4]:

import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(10, 5))
ax.set_ylabel("Bilateral Symmetry Index", fontsize=12)

for view in symmetries:
    ax.plot([get_improved_reader_name(d) for d in datareaders], symmetries[view], \
            marker="o", linestyle="--" if "head" in view else "-", label=view, \
            linewidth=3 if view == "Neurons" else 1,)

plt.setp(ax.get_xticklabels(), rotation=45, ha="right")
ax.legend()
plt.show()

import matplotlib.pyplot as plt fig, ax = plt.subplots(figsize=(10, 5)) ax.set_ylabel("Bilateral Symmetry Index", fontsize=12) for view in symmetries: ax.plot([get_improved_reader_name(d) for d in datareaders], symmetries[view], \ marker="o", linestyle="--" if "head" in view else "-", label=view, \ linewidth=3 if view == "Neurons" else 1,) plt.setp(ax.get_xticklabels(), rotation=45, ha="right") ax.legend() plt.show()