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README.md
<!-- README.md is generated from README.Rmd. Please edit that file --> # Knowledge-based multi-modal integration using anansi <img src="man/figures/anansi_hex.png" align="right" width="120" alt="The anansi hex sticker" /> <!-- badges: start --> [![GitHub issues](https://img.shields.io/github/issues/thomazbastiaanssen/anansi)](https://github.com/thomazbastiaanssen/anansi/issues) [![GitHub pulls](https://img.shields.io/github/issues-pr/thomazbastiaanssen/anansi)](https://github.com/thomazbastiaanssen/anansi/pulls) [![R BiocCheck](https://github.com/thomazbastiaanssen/anansi/actions/workflows/test.yml/badge.svg)](https://github.com/thomazbastiaanssen/anansi/actions/workflows/test.yml) [![Codecov test coverage](https://codecov.io/gh/thomazbastiaanssen/anansi/graph/badge.svg)](https://app.codecov.io/gh/thomazbastiaanssen/anansi) <!-- badges: end --> ## Introduction The `anansi` package computes and compares the association between the features of two ’omics data sets that are known to interact based on a database such as KEGG. Studies including both functional microbiome and metabolomics data are becoming more common. Often, it would be helpful to integrate both data sets in order to see if they corroborate each others patterns. However, all-vs-all association analyses are imprecise and likely to yield spurious associations. This package takes a knowledge-based approach to constrain association search space, only considering metabolite-function interactions that have been recorded in a pathway database. In addition, it provides a framework to assess differential associations. While `anansi` is geared towards metabolite-function interactions in the context of host-microbe interactions, it is perfectly capable of handling any other pair of data sets where some features interact canonically. ## Installation instructions Get the latest stable `R` release from [CRAN](http://cran.r-project.org/). Then install `anansi` from [Bioconductor](http://bioconductor.org/) using the following code: ``` r if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("anansi") ``` And the development version from [GitHub](https://github.com/thomazbastiaanssen/anansi) with `remotes`: ``` r install.packages("remotes") remotes::install_github("thomazbastiaanssen/anansi") ``` ## Getting started using anansi [See the vignettes on the package site.](https://thomazbastiaanssen.github.io/anansi/articles/anansi.html) Additionally, a [preprint](https://arxiv.org/abs/2305.10832) is available. ## Citation Below is the citation output from using `citation('anansi')` in R. ``` r print(citation("anansi"), bibtex = TRUE) #> To cite anansi in publications use: #> #> Bastiaanssen TFS, Quinn TP, Cryan JF (2023) Knowledge-based #> Integration of Multi-Omic Datasets with Anansi: Annotation-based #> Analysis of Specific Interactions arXiv. doi: #> 10.48550/arXiv.2305.10832 #> #> A BibTeX entry for LaTeX users is #> #> @Article{, #> title = {Knowledge-based Integration of Multi-Omic Datasets with Anansi: Annotation-based Analysis of Specific Interactions}, #> author = {Thomaz F S Bastiaanssen and Thomas P Quinn and John F Cryan}, #> journal = {arXiv}, #> year = {2023}, #> doi = {10.48550/arXiv.2305.10832}, #> } ``` ## Code of Conduct Please note that the `anansi` project is released with a [Contributor Code of Conduct](http://bioconductor.org/about/code-of-conduct/). By contributing to this project, you agree to abide by its terms.