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79 changes: 12 additions & 67 deletions README.md
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Expand Up @@ -13,19 +13,19 @@ status](https://github.com/mixOmicsteam/mixOmics/workflows/R-CMD-check.yml/badge

This repository contains the `R` package which is [hosted on
Bioconductor](http://bioconductor.org/packages/release/bioc/html/mixOmics.html)
and our stable and development `GitHub` versions.
and our development `GitHub` versions. Go to www.mixomics.org for
information on how to use mixOmics.

## Installation

(**macOS users only:** Ensure you have installed
[XQuartz](https://www.xquartz.org/) first.)

### From Bioconductor
### From Bioconductor (recommended)

The best way to install `mixOmics` is using `Bioconductor`. You can see
the landing page for the release version of `mixOmics` on Bioconductor
[here](https://bioconductor.org/packages/release/bioc/html/mixOmics.html).

Make sure you have the latest R version and the latest `BiocManager`
package installed following [these
instructions](https://www.bioconductor.org/install/).
Expand All @@ -45,22 +45,20 @@ library(mixOmics)
### From Github

Bioconductor versions are updated twice a year, between these updates
you can downlod the latest stable version of `mixOmics` from `Github`
using:
you can download the latest version of `mixOmics` from `Github`. Note
that this latest version of mixOmics is under development and may not be
stable, check the gitHub page for releases which have passed package
testing.

``` r
BiocManager::install('mixOmicsTeam/mixOmics')
```

You can also install the [development
version](https://github.com/mixOmicsTeam/mixOmics/tree/development) for
new features yet to be widely tested:
## install devtools
install.packages("devtools")

``` r
BiocManager::install("mixOmicsTeam/mixOmics@development")
## install latest github version of mixOmics
devtools::install_github("mixOmicsTeam/mixOmics")
```

### From `Docker` container
### From Docker container

You can install our latest stable Github version of `mixOmics` via our
Docker container. You can do this by downloading and using the Docker
Expand Down Expand Up @@ -212,59 +210,6 @@ suggestions to improve the package. We hope to create an active
community of users, data analysts, developers and R programmers alike!
Thank you!

## About the `mixOmics` team

`mixOmics` is collaborative project between Australia (Melbourne),
France (Toulouse), and Canada (Vancouver). The core team includes
Kim-Anh Lê Cao - <https://lecao-lab.science.unimelb.edu.au> (University
of Melbourne), Florian Rohart - <http://florian.rohart.free.fr>
(Toulouse) and Sébastien Déjean -
<https://perso.math.univ-toulouse.fr/dejean/>. We also have key
contributors, past (Benoît Gautier, François Bartolo) and present (Al
Abadi, University of Melbourne) and several collaborators including
Amrit Singh (University of British Columbia), Olivier Chapleur (IRSTEA,
Paris), Antoine Bodein (Universite de Laval) - **it could be you too, if
you wish to be involved!**.

The project started at the *Institut de Mathématiques de Toulouse* in
France, and has been fully implemented in Australia, at the *University
of Queensland*, Brisbane (2009 – 2016) and at the *University of
Melbourne*, Australia (from 2017). We focus on the development of
computational and statistical methods for biological data integration
and their implementation in `mixOmics`.

## Why this toolkit?

`mixOmics` offers a wide range of novel multivariate methods for the
exploration and integration of biological datasets with a particular
focus on variable selection. Single ’omics analysis does not provide
enough information to give a deep understanding of a biological system,
but we can obtain a more holistic view of a system by combining multiple
’omics analyses. Our `mixOmics` R package proposes a whole range of
multivariate methods that we developed and validated on many biological
studies to gain more insight into ’omics biological studies.

## Want to know more?

www.mixOmics.org (tutorials and resources)

Our latest bookdown vignette:
<https://mixomicsteam.github.io/mixOmics-Vignette/>

## Different types of methods

We have developed 17 novel multivariate methods (the package includes 19
methods in total). The names are full of acronyms, but are represented
in this diagram. *PLS* stands for *Projection to Latent Structures*
(also called Partial Least Squares, but not our preferred nomenclature),
*CCA* for *Canonical Correlation Analysis*.

That’s it! Ready! Set! Go!

Thank you for using `mixOmics`!

![](http://mixomics.org/wp-content/uploads/2012/04/framework-mixOmics-June2016.jpg)

## What’s New

#### November 2024
Expand Down
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Expand Up @@ -42,17 +42,15 @@ pkg_license_badge <- sprintf("https://img.shields.io/badge/license-%s-lightgrey.

![](http://mixomics.org/wp-content/uploads/2019/07/MixOmics-Logo-1.png)

This repository contains the `R` package which is [hosted on Bioconductor](http://bioconductor.org/packages/release/bioc/html/mixOmics.html) and our stable and development `GitHub` versions.
This repository contains the `R` package which is [hosted on Bioconductor](http://bioconductor.org/packages/release/bioc/html/mixOmics.html) and our development `GitHub` versions. Go to www.mixomics.org for information on how to use mixOmics.

## Installation

(**macOS users only:** Ensure you have installed [XQuartz](https://www.xquartz.org/) first.)

### From Bioconductor
### From Bioconductor (recommended)

The best way to install `mixOmics` is using `Bioconductor`. You can see the landing page for the release version of `mixOmics` on Bioconductor [here](https://bioconductor.org/packages/release/bioc/html/mixOmics.html).

Make sure you have the latest R version and the latest `BiocManager` package installed following [these instructions](https://www.bioconductor.org/install/).
The best way to install `mixOmics` is using `Bioconductor`. You can see the landing page for the release version of `mixOmics` on Bioconductor [here](https://bioconductor.org/packages/release/bioc/html/mixOmics.html). Make sure you have the latest R version and the latest `BiocManager` package installed following [these instructions](https://www.bioconductor.org/install/).

```{r}
## install BiocManager if not installed
Expand All @@ -68,20 +66,17 @@ library(mixOmics)

### From Github

Bioconductor versions are updated twice a year, between these updates you can downlod the latest stable version of `mixOmics` from `Github` using:
Bioconductor versions are updated twice a year, between these updates you can download the latest version of `mixOmics` from `Github`. Note that this latest version of mixOmics is under development and may not be stable, check the gitHub page for releases which have passed package testing.

```{r}
BiocManager::install('mixOmicsTeam/mixOmics')
```

You can also install the [development version](https://github.com/mixOmicsTeam/mixOmics/tree/development) for new features yet to be widely tested:
## install devtools
install.packages("devtools")
```{r}
BiocManager::install("mixOmicsTeam/mixOmics@development")
## install latest github version of mixOmics
devtools::install_github("mixOmicsTeam/mixOmics")
```


### From `Docker` container
### From Docker container

You can install our latest stable Github version of `mixOmics` via our Docker container. You can do this by downloading and using the Docker desktop application or via the command line as described below.

Expand Down Expand Up @@ -203,33 +198,5 @@ devtools::check()
We wish to make our discussions transparent so please direct your analysis questions to our discussion forum https://mixomics-users.discourse.group. This forum is aimed to host discussions on choices of multivariate analyses, as well as comments and suggestions to improve the package. We hope to create an active community of users, data analysts, developers and R programmers alike! Thank you!


## About the `mixOmics` team

`mixOmics` is collaborative project between Australia (Melbourne), France (Toulouse), and Canada (Vancouver). The core team includes Kim-Anh Lê Cao - https://lecao-lab.science.unimelb.edu.au (University of Melbourne), Florian Rohart - http://florian.rohart.free.fr (Toulouse) and Sébastien Déjean - https://perso.math.univ-toulouse.fr/dejean/. We also have key contributors, past (Benoît Gautier, François Bartolo) and present (Al Abadi, University of Melbourne) and several collaborators including Amrit Singh (University of British Columbia), Olivier Chapleur (IRSTEA, Paris), Antoine Bodein (Universite de Laval) - **it could be you too, if you wish to be involved!**.

The project started at the _Institut de Mathématiques de Toulouse_ in France, and has been fully implemented in Australia, at the _University of Queensland_, Brisbane (2009 – 2016) and at the _University of Melbourne_, Australia (from 2017). We focus on the development of computational and statistical methods for biological data integration and their implementation in `mixOmics`.

## Why this toolkit?

`mixOmics` offers a wide range of novel multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. Single ‘omics analysis does not provide enough information to give a deep understanding of a biological system, but we can obtain a more holistic view of a system by combining multiple ‘omics analyses. Our `mixOmics` R package proposes a whole range of multivariate methods that we developed and validated on many biological studies to gain more insight into ‘omics biological studies.


## Want to know more?

www.mixOmics.org (tutorials and resources)

Our latest bookdown vignette: https://mixomicsteam.github.io/mixOmics-Vignette/

## Different types of methods

We have developed 17 novel multivariate methods (the package includes 19 methods in total). The names are full of acronyms, but are represented in this diagram.
_PLS_ stands for _Projection to Latent Structures_ (also called Partial Least Squares, but not our preferred nomenclature), _CCA_ for _Canonical Correlation Analysis_.

That's it! Ready! Set! Go!

Thank you for using `mixOmics`!

![](http://mixomics.org/wp-content/uploads/2012/04/framework-mixOmics-June2016.jpg)

```{r, eval=TRUE, child = 'README-WhatsNew.Rmd'}
```

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