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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%"
)
```
# tima <img src='https://raw.githubusercontent.com/taxonomicallyinformedannotation/tima/main/man/figures/logo.svg' align="right" height="139" />
<!-- badges: start -->
[](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[](https://CRAN.R-project.org/package=tima)
[](https://github.com/taxonomicallyinformedannotation/tima/actions/workflows/R-CMD-check.yaml)
[](https://taxonomicallyinformedannotation.r-universe.dev/tima)
[](https://app.codecov.io/gh/taxonomicallyinformedannotation/tima)
[](https://hub.docker.com/r/adafede/tima-r/)
[](https://doi.org/10.5281/zenodo.5797920)
<!-- badges: end -->
The initial work is available at <https://doi.org/10.3389/fpls.2019.01329>, with many improvements made since then.
The workflow is illustrated below.
\
This repository contains everything needed to perform **T**axonomically **I**nformed **M**etabolite **A**nnotation.
## Requirements
Here is what you *minimally* need:
- A feature list (.csv) (see [example features](https://github.com/taxonomicallyinformedannotation/tima-example-files/blob/main/example_features.csv))
- A spectral file corresponding to the feature list (.mgf) (see [example spectra](https://github.com/taxonomicallyinformedannotation/tima-example-files/blob/main/example_spectra_mini.mgf))
- The biological source(s) of the sample(s) you are annotating (.csv) (see [example metadata](https://github.com/taxonomicallyinformedannotation/tima-example-files/blob/main/example_metadata.tsv)) (File is optional if only a single organism)
Optionally, you may want to add:
- An in-house structure-organism pairs library (we provide **[LOTUS](https://lotusnprod.github.io/lotus-manuscript/)** as starting point for each user)
- Your own manual or automated annotations (we currently support annotations coming from SIRIUS (with some limitations))
## Installation
As the package is not (yet) available on CRAN, you will need to install with:
``` r
install.packages(
"tima",
repos = c(
"https://taxonomicallyinformedannotation.r-universe.dev",
"https://bioc.r-universe.dev",
"https://cloud.r-project.org"
)
)
```
Then, you should be able to install the rest with:
``` r
tima::install()
```
Normally, everything you need should then be installed (as tested in [here](https://github.com/taxonomicallyinformedannotation/tima-r/actions/workflows/external-use.yaml)).
If for some reason, some packages were not installed, try to install them manually.
To avoid such issues, we offer a containerized version (see [Docker](#docker)).
Once installed, you are ready to go through our [documentation](https://taxonomicallyinformedannotation.github.io/tima/articles/), with the major steps detailed.
In case you do not have your data ready, you can obtain some example data using:
``` r
tima::get_example_files()
```
Once you are done, you can open a small GUI to adapt your parameters and launch your job:
``` r
tima::run_app()
```
This command will open a small app in your default browser.
### Docker
A container is also available, together with a small compose file.
Main commands are below:
``` bash
docker pull adafede/tima-r
# docker build . -t adafede/tima-r
```
``` bash
docker run --user tima-user -v "$(pwd)/.tima/data:/home/tima-user/.tima/data" -p 3838:3838 adafede/tima-r Rscript -e "tima::run_app()"
# docker run --user tima-user -v "$(pwd)/.tima/data:/home/tima-user/.tima/data" adafede/tima-r Rscript -e "tima::tima_full()"
```
Or alternatively (if you did pull the repository and are located at the right place):
``` bash
docker compose up tima-run-app
# docker compose up tima-full
```
## Main Citations
According to which steps you used, please give credit to the authors of the tools/resources used.
### TIMA
General: <https://doi.org/10.3389/fpls.2019.01329>
⚠️ Do not forget to cite which version you used: <https://doi.org/10.5281/zenodo.5797920>
### LOTUS
General: <https://doi.org/10.7554/eLife.70780>
⚠️ Do not forget to cite which version you used: <https://doi.org/10.5281/zenodo.5794106>
### ISDB
General: <https://doi.org/10.1021/acs.analchem.5b04804>
⚠️ Do not forget to cite which version you used: <https://doi.org/10.5281/zenodo.5607185>
### GNPS
General: <https://doi.org/10.1038/nbt.3597>
### SIRIUS
General: <https://doi.org/10.1038/s41592-019-0344-8>
- *CSI:FingerId*: <https://doi.org/10.1073/pnas.1509788112>
- *ZODIAC*: <https://doi.org/10.1038/s42256-020-00234-6>
- *CANOPUS*: <https://doi.org/10.1038/s41587-020-0740-8>
- *COSMIC*: <https://doi.org/10.1038/s41587-021-01045-9>
### Others
- The *RforMassSpectrometry* packages suite for MS2 matching: <https://doi.org/10.3390/metabo12020173>
- ECMDB 2.0: <https://doi.org/10.1093/nar/gkv1060>
- HMDB 5.0: <https://doi.org/10.1093/nar/gkab1062>
- MassBank: <https://doi.org/10.5281/zenodo.3378723>
- NPClassifier: <https://doi.org/10.1021/acs.jnatprod.1c00399>
- ROTL: <https://doi.org/10.1111/2041-210X.12593>
- Spectral entropy: <https://doi.org/10.1038/s41592-021-01331-z>