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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# Antimicrobial resistome data analysis with R/Bioconductor
<!-- badges: start -->
[](https://codecov.io/gh/NCBI-Codeathons/amr-2024-team-lahti?branch=main)
[](https://ncbiamrcodeathon.slack.com/x-p7700037081187-7765806765012-7763213820995/archives/C07L5HA3UFR)
[](https://github.com/NCBI-Codeathons/amr-2024-team-lahti/watchers)
[](https://github.com/NCBI-Codeathons/amr-2024-team-lahti/stargazers)
<!-- badges: end -->
## Project goals
_This project aims to develop [R/Bioconductor](https://www.bioconductor.org/)
tools to analyze AMR data by integrating publicly available human gut
metagenomes with ARG profiles (e.g.
[metagenomics](https://www.nature.com/subjects/metagenomics)) and
epidemiological, transmission data to study AMR gene co-migration._
## Approach
Reproducible data science workflow and dissemination material to demonstrate the
utilization of the latest Bioconductor multi-assay data integration framework in
the context of resistome profiling in large population studies. This covers
dedicated data structures and the complementary data analysis and visualization
methods. The outcomes are reported via an automated pkgdown website.
[Standout presentation](/standouts/standout-day1.odp)
## Analysis plan
1. _Prepare data_
* Prepare the [Lee et al. (2023)](https://github.com/microbiome/data/tree/main/Lee2023)
dataset for analysis in R/Bioc. See [data summary](https://ncbi-codeathons.github.io/amr-2024-team-lahti/articles/data_summary.html).
* Link the dataset to the [NDARO database](https://www.ncbi.nlm.nih.gov/pathogens/antimicrobial-resistance/)
on microbial organisms and resistance genes.
2. _Prepare documentation_
* Create minimal website for this project.
* Prepare summary of the dataset.
* Create tutorials on resistome data analysis.
* To add documents to the minimal website, see [technical guide](https://ncbi-codeathons.github.io/amr-2024-team-lahti/articles/addqmd.html)
3. _Analyse the resistome data set_
* Provide exploratory summaries of the dataset using R/Bioc methods.
* Replicate some key results from the [manuscript](https://www.nature.com/articles/s41467-023-36633-7) to verify the data.
4. _Develop methodology_
* Implement visualization methods as functions.
5. _Finalize workflow_
* Polish the data analysis workflow/s & documentation.
## Results
The main outcome of this work is the reproducible project site including data
science workflows for resistome analysis. This forms the basis for an extendable
collection of resistome analysis workflows for reanalysis of data for new
discoveries, methods development and educational purposes.
## Future work
Future work will standardize and automate some of the key tools, and release
them through open source software libraries such as
_[mia](https://microbiome.github.io/mia/)_ in R/Bioconductor.
## Team roles
* __Team Lead__ / [Leo Lahti](https://github.com/antagomir)
Conveys scientific objectives to the team, and coordinates work.
* __Tech Lead__ / [Akewak Jeba](https://github.com/ake123) & [Muluh Geraldson](https://github.com/Daenarys8)
Coordinates software installation and data acquisition, manages version control
and the team’s GitHub repository, troubleshoots technical issues with tech support
* __Writer__ / [Dattaray Mongad](https://github.com/microDM) & [Nitin Bayal](https://github.com/nixonbyl)
Ensures that all work is documented, manages GitHub README and Team Report
* __Flex__ / [Mahkameh Salehi](https://github.com/mahkamehsalehi) & [Shivang Bhanushali](https://github.com/ShivangPB)
Fills various roles and assumes responsibilities for tasks as needed
## NCBI codeathon disclaimer
This software was created as part of an NCBI codeathon(See [details](https://www.nlm.nih.gov/ncbi/workshops/2024-09_AMR-Codeathon/codeathon-details.html))
, a hackathon-style event focused on rapid innovation. While we encourage
you to explore and adapt this code, please be aware that NCBI does not
provide ongoing support for it.
For general questions about NCBI software and tools, please visit: [NCBI
Contact Page](https://www.ncbi.nlm.nih.gov/home/about/contact/)