https://github.com/dhimmel/opcendo
Candidate OPC–endothelial cell interactors
https://github.com/dhimmel/opcendo
gene-ontology oligodendrocyte-precursor-cells protein-interaction string
Last synced: about 2 months ago
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Candidate OPC–endothelial cell interactors
- Host: GitHub
- URL: https://github.com/dhimmel/opcendo
- Owner: dhimmel
- Created: 2016-02-26T19:14:26.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2016-05-03T19:57:42.000Z (about 9 years ago)
- Last Synced: 2025-01-28T23:50:07.514Z (4 months ago)
- Topics: gene-ontology, oligodendrocyte-precursor-cells, protein-interaction, string
- Language: Jupyter Notebook
- Homepage:
- Size: 10.1 MB
- Stars: 0
- Watchers: 3
- Forks: 1
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# Identifying candidate OPC–endothelial cell interactors
By Daniel Himmelstein & Dan Zollinger
Oligodendrocyte precursor cells (OPCs) were [recently found](https://doi.org/10.1126/science.aad3839 "Oligodendrocyte precursors migrate along vasculature in the developing nervous system") to migrate along the vascular endothelium. Here we identify gene pairs that are candidate OPC–endothelial cell interactors. We create a filtered set of gene-gene interactions by:
+ filtering for genes that participate in relevant GO terms
+ filtering for gene-pairs that exceed an interaction confidence score threshold
+ filtering for gene-pairs where one gene is enriched in OPCs and the other is enriched in endothelial cells.
The filtered dataset provides a candidate network of interactions for biologic interrogation.
## Execution
Execute the notebooks in the following order:
1. [`enrichment.ipynb`](enrichment.ipynb) — calculate transcriptional fold changes for OPCs and endothelial cells. Integrate Gene Ontology annotations.
2. [`interaction.ipynb`](interaction.ipynb) — integrate protein interactions with expression and GO data. Filter interactions according to user-defined parameters. Create an interaction network.
## Datasets
The following datasets are created:
+ [`enrichment.tsv`](data/enrichment.tsv) — text file with expression fold changes and GO annotations.
+ [`filtered.xlsx`](data/filtered.xlsx) — spreadsheet with the filtered interactions.
+ [`network.graphml`](data/filtered.xlsx) — network constructed using the filtered interactions. This file can be loaded into [Cytoscape 3](http://www.cytoscape.org/) using the menu option: File ▶ Import ▶ File.
## Resources
Expression data is from the [Brain RNA-Seq database](http://web.stanford.edu/group/barres_lab/brain_rnaseq.html) [Zhang et al (2014) [_J Neurosci_](https://doi.org/10.1523/JNEUROSCI.1860-14.2014 "An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex")].
Differential expression for Dominant Active-catenin mice was retrieved from a [processed version](https://github.com/dhimmel/opcendo/issues/1) of [GSE19403](http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19403 "Gene Expression Omnibus GSE19403") [Fancy et al (2011) [_Nat Neurosci_](https://doi.org/10.1038/nn.2855 "Axin2 as regulatory and therapeutic target in newborn brain injury and remyelination")].
Protein-protein interactions are extracted from the [STRING database](http://string-db.org/) version 10 [Szklarczyk et al (2015) [_Nucl Acids Res_](https://doi.org/10.1093/nar/gku1003 "STRING v10: protein–protein interaction networks, integrated over the tree of life")].
Gene Ontology annotations are retrieved from [user-friendly GO Annotations](http://git.dhimmel.com/gene-ontology/) [Himmelstein et al (2015) [_Zenodo_](https://doi.org/10.5281/zenodo.21711 "gene-ontology: Initial zenodo release")].
## Installation
_Instructions for biologists:_
If you don't already have python, install [Anaconda for Python 3.5](https://www.continuum.io/downloads).
Next clone this repository to your computer. You can also [download and extract a zip](https://github.com/dhimmel/opcendo/archive/master.zip).
Launch Jupyter (`jupyter notebook` in terminal or using the Anaconda GUI) and navigate to the `opcendo` directory.
## License
All original content in this repository is released under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/ "Creative Commons · Public Domain Dedication"). STRING data is licensed as [CC BY 3.0](http://creativecommons.org/licenses/by/3.0/). The Gene Ontology data is licensed as [CC BY 4.0](http://creativecommons.org/licenses/by/4.0/). Brain RNA-Seq data is included with permission from its creator Steven Sloan. Data from Fancy et al 2011 is included with permission.