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schedule:
- cron: '0 8 * * 4'

name: R-CMD-check
name: R-CMD-check.yml

jobs:
## pre-job to determine if a job has been run for the same SHA (e.g. on a different branch)
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243 changes: 108 additions & 135 deletions README.md
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<!-- PLEASE DO NOT EDIT ./README.md BY HAND, EDIT ./inst/README.Rmd AND RENDER TO CREATE ./README.md -->

[![R build
status](https://github.com/mixOmicsteam/mixOmics/workflows/R-CMD-check/badge.svg)](https://github.com/mixOmicsteam/mixOmics/actions)
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[![dependencies](http://bioconductor.org/shields/dependencies/release/mixOmics.svg)](http://bioconductor.org/packages/release/bioc/html/mixOmics.html#since)

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

This repository contains the `R` package [now hosted on
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.

Expand All @@ -21,72 +21,51 @@ and our stable and development `GitHub` versions.
(**macOS users only:** Ensure you have installed
[XQuartz](https://www.xquartz.org/) first.)

### From Bioconductor

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/) (if you use legacy
R versions (\<=3.5.0) refer to the instructions at the end of the
mentioned page).
instructions](https://www.bioconductor.org/install/).

``` r
## install BiocManager if not installed
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
```

Ensure the following returns `TRUE`, or follow the guidelines provided
by the output.

``` r
BiocManager::valid()
```

For installation in R, see options a) and b). For Docker containers, see
c).

#### a) Latest `Bioconductor` Release

You can then install `mixOmics` using the following code:

``` r
## install mixOmics
BiocManager::install('mixOmics')
```

#### b) `GitHub` Versions

##### Stable version

Install the latest stable version (see below for latest
[development](https://github.com/ajabadi/mixOmics#development-version)
version) of `mixOmics` from `GitHub` (as bug-free as it can be):

``` r
BiocManager::install("mixOmicsTeam/mixOmics")
## load mixOmics
library(mixOmics)
```

Check after installation that the following code does not throw any
error (especially Mac users - refer to [installation
instructions](#installation)) and that the welcome message confirms you
have installed [the latest
version](https://github.com/mixOmicsTeam/mixOmics/blob/master/DESCRIPTION#L4):
### From Github

Bioconductor versions are updated twice a year, between these updates
you can downlod the latest stable version of `mixOmics` from `Github`
using:

``` r
library(mixOmics)
#> Loaded mixOmics ?.?.?
BiocManager::install('mixOmicsTeam/mixOmics')
```

##### Development version

You can also install the [development
version](https://github.com/mixOmicsTeam/mixOmics/blob/devel/DESCRIPTION#L4)
for new features yet to be widely tested (see [What’s
New](/https://github.com/ajabadi/mixOmics#whats-new)):
version](https://github.com/mixOmicsTeam/mixOmics/tree/development) for
new features yet to be widely tested:

``` r
BiocManager::install("mixOmicsTeam/mixOmics@devel")
BiocManager::install("mixOmicsTeam/mixOmics@development")
```

#### c) `Docker` container of the stable GitHub version
### 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.

<details>
<summary>
Expand All @@ -101,8 +80,8 @@ Click to expand
**if your OS is not compatible with the latest version** download an
older version of Docker from the following link:

- MacOS: <https://docs.docker.com/docker-for-mac/release-notes/>
- Windows: <https://docs.docker.com/docker-for-windows/release-notes/>
- MacOS: <https://docs.docker.com/docker-for-mac/release-notes/>
- Windows: <https://docs.docker.com/docker-for-windows/release-notes/>

Then open your system’s command line interface (e.g. Terminal for MacOS
and Command Promot for Windows) for the following steps.
Expand Down Expand Up @@ -132,7 +111,7 @@ to the following:
> REPOSITORY TAG IMAGE ID CREATED SIZE
> mixomicsteam/mixomics latest e755393ac247 2 weeks ago 4.38GB

4) Active the container
4) Activate the container

Running the following command activates the container. You must change
`your_password` to a custom password of your own. You can also customise
Expand Down Expand Up @@ -197,9 +176,9 @@ tests on our datasets.
Set up development environment
</summary>

- Install the latest version of R
- Install RStudio
- Clone this repo, checkout master branch, pull origin and then run:
- Install the latest version of R
- Install RStudio
- Clone this repo, checkout master branch, pull origin and then run:

``` r
install.packages("renv", Ncpus=4)
Expand Down Expand Up @@ -291,95 +270,89 @@ Thank you for using `mixOmics`!

#### March 2022

- bug fix implemented for [Issue
\#196](https://github.com/mixOmicsTeam/mixOmics/issues/196).
`perf()` can now handle features with a `(s)pls` which have near
zero variance.
- bug fix implemented for [Issue
\#192](https://github.com/mixOmicsTeam/mixOmics/issues/192).
`predict()` can now handle when the testing and training data have
their columns in different orders.
- bug fix implemented for [Issue
\#178](https://github.com/mixOmicsTeam/mixOmics/issues/178). If the
`indY` parameter is used in `block.spls()`, `circosPlot()` can now
properly identify the
![Y](https://latex.codecogs.com/png.image?%5Cdpi%7B110%7D&space;%5Cbg_white&space;Y "Y")
dataframe.
- bug fix implemented for [Issue
\#172](https://github.com/mixOmicsTeam/mixOmics/issues/172).
`perf()` now returns values for the `choice.ncomp` component when
`nrepeat`
![\< 3](https://latex.codecogs.com/png.image?%5Cdpi%7B110%7D&space;%5Cbg_white&space;%3C%203 "< 3")
whereas before it would just return `NA`s.
- bug fix implemented for [Issue
\#171](https://github.com/mixOmicsTeam/mixOmics/issues/171). `cim()`
now can take `pca` objects as input.
- bug fix implemented for [Issue
\#161](https://github.com/mixOmicsTeam/mixOmics/issues/161).
`tune.spca()` can now handle `NA` values appropriately.
- bug fix implemented for [Issue
\#150](https://github.com/mixOmicsTeam/mixOmics/issues/150).
Provided users with a specific error message for when `plotArrow()`
is run on a `(mint).(s)plsda` object.
- bug fix implemented for [Issue
\#122](https://github.com/mixOmicsTeam/mixOmics/issues/122).
Provided users with a specific error message for when a `splsda`
object that has only one sample associated with a given class is
passed to `perf()`.
- bug fix implemented for [Issue
\#120](https://github.com/mixOmicsTeam/mixOmics/issues/120).
`plotLoadings()` now returns the loading values for features from
**all** dataframes rather than just the last one when operating on a
`(mint).(block).(s)plsda` object.
- bug fix implemented for [Issue
\#43](https://github.com/mixOmicsTeam/mixOmics/issues/43).
Homogenised the way in which `tune.mint.splsda()` and
`perf.mint.splsda()` calculate balanced error rate (BER) as there
was disparity between them. Also made the global BER a weighted
average of BERs across each study.
- enhancement implemented for [Issue
\#30/#34](https://github.com/mixOmicsTeam/mixOmics/issues/34). The
parameter `verbose.call` was added to most of the methods. This
parameter allows users to access the specific values input into the
call of a function from its output.
- bug fix implemented for [Issue
\#24](https://github.com/mixOmicsTeam/mixOmics/issues/24).
`background.predict()` can now operate on `mint.splsda` objects and
can be used as part of `plotIndiv()`.
- bug fix implemented for [Issue
\#196](https://github.com/mixOmicsTeam/mixOmics/issues/196). `perf()`
can now handle features with a `(s)pls` which have near zero variance.
- bug fix implemented for [Issue
\#192](https://github.com/mixOmicsTeam/mixOmics/issues/192).
`predict()` can now handle when the testing and training data have
their columns in different orders.
- bug fix implemented for [Issue
\#178](https://github.com/mixOmicsTeam/mixOmics/issues/178). If the
`indY` parameter is used in `block.spls()`, `circosPlot()` can now
properly identify the $Y$ dataframe.
- bug fix implemented for [Issue
\#172](https://github.com/mixOmicsTeam/mixOmics/issues/172). `perf()`
now returns values for the `choice.ncomp` component when `nrepeat`
$< 3$ whereas before it would just return `NA`s.
- bug fix implemented for [Issue
\#171](https://github.com/mixOmicsTeam/mixOmics/issues/171). `cim()`
now can take `pca` objects as input.
- bug fix implemented for [Issue
\#161](https://github.com/mixOmicsTeam/mixOmics/issues/161).
`tune.spca()` can now handle `NA` values appropriately.
- bug fix implemented for [Issue
\#150](https://github.com/mixOmicsTeam/mixOmics/issues/150). Provided
users with a specific error message for when `plotArrow()` is run on a
`(mint).(s)plsda` object.
- bug fix implemented for [Issue
\#122](https://github.com/mixOmicsTeam/mixOmics/issues/122). Provided
users with a specific error message for when a `splsda` object that
has only one sample associated with a given class is passed to
`perf()`.
- bug fix implemented for [Issue
\#120](https://github.com/mixOmicsTeam/mixOmics/issues/120).
`plotLoadings()` now returns the loading values for features from
**all** dataframes rather than just the last one when operating on a
`(mint).(block).(s)plsda` object.
- bug fix implemented for [Issue
\#43](https://github.com/mixOmicsTeam/mixOmics/issues/43). Homogenised
the way in which `tune.mint.splsda()` and `perf.mint.splsda()`
calculate balanced error rate (BER) as there was disparity between
them. Also made the global BER a weighted average of BERs across each
study.
- enhancement implemented for [Issue
\#30/#34](https://github.com/mixOmicsTeam/mixOmics/issues/34). The
parameter `verbose.call` was added to most of the methods. This
parameter allows users to access the specific values input into the
call of a function from its output.
- bug fix implemented for [Issue
\#24](https://github.com/mixOmicsTeam/mixOmics/issues/24).
`background.predict()` can now operate on `mint.splsda` objects and
can be used as part of `plotIndiv()`.

#### July 2021

- new function `plotMarkers` to visualise the selected features in
block analyses (see
<https://github.com/mixOmicsTeam/mixOmics/issues/134>)
- `tune.spls` now able to tune the selected variables on both `X` and
`Y`. See `?tune.spls`
- new function `impute.nipals` to impute missing values using the
nipals algorithm
- new function `tune.spca` to tune the number of selected variables
for pca components
- `circosPlot` now has methods for `block.spls` objects. It can now
handle similar feature names across blocks. It is also much more
customisable. See advanced arguments in `?circosPlot`
- new `biplot` function for `pca` and `pls` objects. See
`?mixOmics::biplot`
- `plotDiablo` now takes `col.per.group` (see \#119)
- new function `plotMarkers` to visualise the selected features in block
analyses (see <https://github.com/mixOmicsTeam/mixOmics/issues/134>)
- `tune.spls` now able to tune the selected variables on both `X` and
`Y`. See `?tune.spls`
- new function `impute.nipals` to impute missing values using the nipals
algorithm
- new function `tune.spca` to tune the number of selected variables for
pca components
- `circosPlot` now has methods for `block.spls` objects. It can now
handle similar feature names across blocks. It is also much more
customisable. See advanced arguments in `?circosPlot`
- new `biplot` function for `pca` and `pls` objects. See
`?mixOmics::biplot`
- `plotDiablo` now takes `col.per.group` (see \#119)

#### April 2020

- weighted consensus plots for DIABLO objects now consider
per-component weights
- weighted consensus plots for DIABLO objects now consider per-component
weights

#### March 2020

- `plotIndiv` now supports (weighted) consensus plots for block
analyses. See the example in [this
issue](https://github.com/mixOmicsTeam/mixOmics/issues/57)
- `plotIndiv(..., ind.names=FALSE)` [warning
issue](https://github.com/mixOmicsTeam/mixOmics/issues/59) now fixed
- `plotIndiv` now supports (weighted) consensus plots for block
analyses. See the example in [this
issue](https://github.com/mixOmicsTeam/mixOmics/issues/57)
- `plotIndiv(..., ind.names=FALSE)` [warning
issue](https://github.com/mixOmicsTeam/mixOmics/issues/59) now fixed

#### January 2020

- `perf.block.splsda` now supports calculation of combined AUC
- `block.splsda` bug which could drop some classes with
`near.zero.variance=TRUE` now fixed
- `perf.block.splsda` now supports calculation of combined AUC
- `block.splsda` bug which could drop some classes with
`near.zero.variance=TRUE` now fixed
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