Exploring Antimicrobial Resistance Mechanisms Through a Pangenome-Scale Epistatic Interactions Network
date: 1/28/2024 5:23PM
Mendeley paper collection
Antimicrobial resistance (AMR) is a major public health issue demanding combined interdisciplinary efforts to solve it. This project aims to portray the complex gene-interaction system driving AMR mechanisms by integrating pangenomics, machine learning, and network science. In this work, we aim to construct a reference-agnostic pangenomic network modelling epistatic interactions between alleles defined by their co-occurence. This network will be built on a resistance based topology to demonstrate gene interactions influencing AMR mechanisms.
Keywords: Antimicrobial Resistance (AMR), Network Science, Epistasis, Gene-Gene Interactions, Pangenome, Association, Machine Learning, Log-Odds Ratio, Allele Co-Occurrence
- 🗂️ src
- 📁 analysis
- 📄 phenotype.ipynb: exploring and manipulating all the pheno data
- 📄 memoizing_dataframes.ipynb
- 📄 {species}_{drug}_analysis.ipynb: Jupyter notebook with analysis when labels are taken for this {drug}.
- 📄 gene_associations.py
- 📄 network_analysis.py
- 📄 network_construction.py
- 📄 cluster_analysis.py
- 📄 data_analysis.py
- 📁 analysis
- 🗂️ data
- 📁 phenotypes
- 📄 {species}_{drug}.csv: Phenotypes for this drug and species (SIR readings) extracted from xlsx
- 📁 processed_phenotypes
- 📄 {species}_{drug}.csv: Processed phenotypes for this drug and species
- 📁 genomes
- 📁 {species}: pan genome analysis pipeline output (w/o eggnog)
- 📁 processed_matrices
- 📄 {species}_{drug}.csv: Labeled matrix for this drug and species (concatenated X and y)
- 📁 presence_matrices
- 📄 {species}.csv: Presence matrix for this species
- 📄 DatasetS1.json
- 📄 SIR_readings.xlsx
- 📁 phenotypes
- 🗂️ results
- 📁 {species}_{drug}
- 📄 {association_type}_top_100.csv
- 📄 {species}_{drug}_network.graphml
- 📄 annotated_{species}_{drug}_network.graphml
- 📁 {species}_{drug}
- 🗂️ figures
needs further cleaning