Find graph motifs using simple, intuitive notation
Project description
d o t m o t i f
Find graph motifs using intuitive notation
DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like this:
# Look for all motifs of the form,
# Neuron A synapses on Neuron B:
A -> B
# ...and B inhibits C:
B -> C [type = "inhibitory"]
Examples
Notebook | Description |
---|---|
Looking for motifs in the IARPA MICrONS Pinky100 Dataset | |
Motif search in a custom graph | |
Subgraph search in the Janelia Hemibrain dataset |
Get Started
If you have DotMotif, a NetworkX graph, and a curious mind, you already have everything you need to start using DotMotif:
from dotmotif import Motif, GrandIsoExecutor
executor = GrandIsoExecutor(graph=my_networkx_graph)
triangle = Motif("""
A -> B
B -> C
C -> A
""")
results = executor.find(triangle)
Parameters
You can also pass optional parameters into the constructor for the dotmotif
object. Those arguments are:
Argument | Type, Default | Behavior |
---|---|---|
ignore_direction |
bool : False |
Whether to disregard direction when generating the database query |
limit |
int : None |
A limit (if any) to impose on the query results |
enforce_inequality |
bool : False |
Whether to enforce inequality; in other words, whether two nodes should be permitted to be aliases for the same node. For example, in A->B->C ; if A!=C , then set to True |
exclude_automorphisms |
bool : False |
Whether to return only a single example for each detected automorphism. See more in the documentation |
For more details on how to write a query, see Getting Started.
Citing
If this tool is helpful to your research, please consider citing it with:
# https://doi.org/10.1038/s41598-021-91025-5
@article{Matelsky_Motifs_2021,
title={{DotMotif: an open-source tool for connectome subgraph isomorphism search and graph queries}},
volume={11},
ISSN={2045-2322},
url={http://dx.doi.org/10.1038/s41598-021-91025-5},
DOI={10.1038/s41598-021-91025-5},
number={1},
journal={Scientific Reports},
publisher={Springer Science and Business Media LLC},
author={Matelsky, Jordan K. and Reilly, Elizabeth P. and Johnson, Erik C. and Stiso, Jennifer and Bassett, Danielle S. and Wester, Brock A. and Gray-Roncal, William},
year={2021},
month={Jun}
}
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