Roxygen the package, add badges, logo and update pkgdown site.

.Rbuildignore

@@ -1,3 +1,12 @@
+genlogo.R
+.gitignore
+^codecov\.yml$
+^revdep$
+^_pkgdown\.yml$
+^figure$
+^pkgdown$
+^Meta$
+#^doc$
 #All packages
 ^.*\.Rproj$
 ^\.Rproj\.user$
@@ -11,7 +20,10 @@
 #If README too big, not on CRAN but only on git
 ^man/figures*$
 ^README\.Rmd$
-^README\.md$
+#^README\.md$
 #Specific
 ^fullrespdf*$
 ^inst/animation*$
+^articles*$
+^review*$
+^\.github$

.github/.gitignore

@@ -0,0 +1 @@
+*.html

.github/workflows/R-CMD-check.yaml

@@ -0,0 +1,32 @@
+# For help debugging build failures open an issue on the RStudio community with the 'github-actions' tag.
+# https://community.rstudio.com/new-topic?category=Package%20development&tags=github-actions
+on:
+  push:
+    branches:
+      - main
+      - master
+  pull_request:
+    branches:
+      - main
+      - master
+
+name: R-CMD-check
+
+jobs:
+  R-CMD-check:
+    runs-on: macOS-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@v2
+      - uses: r-lib/actions/setup-r@v1
+      - name: Install dependencies
+        run: |
+          install.packages(c("remotes", "rcmdcheck"))
+          remotes::install_deps(dependencies = TRUE)
+        shell: Rscript {0}
+      - name: Check
+        run: |
+          options(crayon.enabled = TRUE)
+          rcmdcheck::rcmdcheck(args = "--no-manual", error_on = "error")
+        shell: Rscript {0}

.gitignore

@@ -1,5 +1,19 @@
-.Rproj.user
+# History files
 .Rhistory
+.Rapp.history
+# Session Data files
 .RData
+# User-specific files
 .Ruserdata
+# Example code in package build process
+*-Ex.R
+# Output files from R CMD build
+/*.tar.gz
+# Output files from R CMD check
+/*.Rcheck/
+# RStudio files
+.Rproj.user/
+.Rproj.user/*
 .DS_Store
+#doc
+Meta

CascadeData.Rproj

@@ -13,4 +13,6 @@ RnwWeave: knitr
 LaTeX: pdfLaTeX
 
 BuildType: Package
+PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: CascadeData
 Type: Package
 Title: Experimental Data of Cascade Experiments in Genomics
-Version: 1.2
-Date: 2019-02-06
+Version: 1.3
+Date: 2021-03-18
 Depends: R (>= 2.10)
 Imports: 
 Suggests: 
@@ -16,6 +16,6 @@ Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>
 Description: These experimental expression data (5 leukemic 'CLL' B-lymphocyte of aggressive form from 'GSE39411', <doi:10.1073/pnas.1211130110>), after B-cell receptor stimulation, are used as examples by packages such as the 'Cascade' one, a modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.
 License: GPL (>= 2)
 Encoding: UTF-8
-RoxygenNote: 6.1.1
-URL: http://www-irma.u-strasbg.fr/~fbertran/, https://github.com/fbertran/CascadeData
-BugReports: https://github.com/fbertran/CascadeData/issues
+RoxygenNote: 7.1.1
+URL: https://fbertran.github.io/CascadeData/, https://github.com/fbertran/CascadeData/
+BugReports: https://github.com/fbertran/CascadeData/issues/

NAMESPACE

@@ -0,0 +1,2 @@
+# Generated by roxygen2: do not edit by hand
+

NEWS.md

@@ -1,3 +1,7 @@
+# CascadeData 1.3
+
+* Roxygen the package, add badges, logo and update pkgdown site.
+
 # CascadeData 1.2
 
 * Added references for the dataset and GSE accession number.

R/CascadeData-package.R

@@ -0,0 +1,45 @@
+#' Experimental Data of Cascade Experiments in Genomics
+#' 
+#' These are the data from the agressive subject group the from GSE39411
+#' dataset, \url{https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39411},
+#' Vallat, L., Kemper, C. A., Jung, N., Maumy-Bertrand, M., Bertrand, F.,
+#' \dots{}, Bahram, S. (2013). Reverse-engineering the genetic circuitry of a
+#' cancer cell with predicted intervention in chronic lymphocytic leukemia.
+#' Proceedings of the National Academy of Sciences, 110(2), 459-464,
+#' \doi{10.1073/pnas.1211130110}
+#' 
+#' 5 leukemic CLL B-lymphocyte of aggressive form were stimulated in vitro with
+#' an anti-IgM antibody, activating the B-cell receptor (BCR). We analyzed the
+#' gene expression at 4 time points (60, 90, 210 and 390 minutes). Each gene
+#' expression measurement is performed both in stimulated cells and in control
+#' unstimulated cells.
+#' 
+#' The data were normalized and are ready to use.
+#' 
+#' These Experimental Data are used as examples by packages such as the Cascade
+#' one \doi{10.1093/bioinformatics/btt705} in one of its vignettes. The Cascade
+#' package is a modeling tool allowing gene selection, reverse engineering, and
+#' prediction in Cascade networks.
+#' 
+#' Data were collected on HG-U133_Plus_2, Affymetrix Human Genome U133 Plus 2.0
+#' Array.
+#' 
+#' @name CascadeData-package
+#' @aliases CascadeData-package CascadeData
+#' @docType package
+#' @author This package has been written by Frederic Bertrand, Myriam
+#' Maumy-Bertrand and Nicolas Jung with biological insights from Laurent
+#' Vallat.
+#' 
+#' Maintainer: Frederic Bertrand <frederic.bertrand@@math.unistra.fr>
+#' @references Jung, N., Bertrand, F., Bahram, S., Vallat, L., and
+#' Maumy-Bertrand, M. (2013). Cascade: a R-package to study, predict and
+#' simulate the diffusion of a signal through a temporal gene network.
+#' \emph{Bioinformatics}, btt705.
+#' 
+#' Vallat, L., Kemper, C. A., Jung, N., Maumy-Bertrand, M., Bertrand, F., ... &
+#' Bahram, S. (2013). Reverse-engineering the genetic circuitry of a cancer
+#' cell with predicted intervention in chronic lymphocytic leukemia.
+#' \emph{Proceedings of the National Academy of Sciences}, 110(2), 459-464.
+#' @keywords package
+NULL

R/Datasets.R

@@ -0,0 +1,68 @@
+#' Stimulated dataset
+#' 
+#' This is the stimulated data part of the GSE39411 dataset,
+#' \url{https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39411}. Data were
+#' normalized and are ready to use.
+#' 
+#' 5 leukemic CLL B-lymphocyte of aggressive form were stimulated in vitro with
+#' an anti-IgM antibody, activating the B-cell receptor (BCR). We analyzed the
+#' gene expression at 4 time points (60, 90, 210 and 390 minutes). Each gene
+#' expression measurement is performed both in stimulated cells and in control
+#' unstimulated cells. This is the stimulated cells dataset.
+#' 
+#' Data were collected on HG-U133_Plus_2, Affymetrix Human Genome U133 Plus 2.0
+#' Array.
+#' 
+#' @name micro_S
+#' @docType data
+#' @format A data frame with 54613 probesets measured 6 times throught 4 time
+#' points.
+#' @references Vallat, L., Kemper, C. A., Jung, N., Maumy-Bertrand, M.,
+#' Bertrand, F., \dots{}, Bahram, S. (2013). Reverse-engineering the genetic
+#' circuitry of a cancer cell with predicted intervention in chronic
+#' lymphocytic leukemia. Proceedings of the National Academy of Sciences,
+#' 110(2), 459-464, \doi{10.1073/pnas.1211130110}.
+#' @keywords datasets
+#' @examples
+#' 
+#' data(micro_S)
+#' 
+NULL
+
+
+
+
+
+#' Unstimulated control dataset
+#' 
+#' This is the unstimulated data part of the GSE39411 dataset,
+#' \url{https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39411}. Data were
+#' normalized and are ready to use.
+#' 
+#' 5 leukemic CLL B-lymphocyte of aggressive form were stimulated in vitro with
+#' an anti-IgM antibody, activating the B-cell receptor (BCR). We analyzed the
+#' gene expression at 4 time points (60, 90, 210 and 390 minutes). Each gene
+#' expression measurement is performed both in stimulated cells and in control
+#' unstimulated cells. This is the unstimulated cells dataset.
+#' 
+#' Data were collected on HG-U133_Plus_2, Affymetrix Human Genome U133 Plus 2.0
+#' Array.
+#' 
+#' @name micro_US
+#' @docType data
+#' @format A data frame with 54613 probesets measured 6 times throught 4 time
+#' points.
+#' @references Vallat, L., Kemper, C. A., Jung, N., Maumy-Bertrand, M.,
+#' Bertrand, F., \dots{}, Bahram, S. (2013). Reverse-engineering the genetic
+#' circuitry of a cancer cell with predicted intervention in chronic
+#' lymphocytic leukemia. Proceedings of the National Academy of Sciences,
+#' 110(2), 459-464, \doi{10.1073/pnas.1211130110}.
+#' @keywords datasets
+#' @examples
+#' 
+#' data(micro_US)
+#' 
+NULL
+
+
+

README.Rmd

@@ -1,12 +1,3 @@
----
-title: "Experimental Data of Cascade Experiments in Genomics"
-author: "Frédéric Bertrand and Myriam Maumy-Bertrand"
-output: github_document
----
-
-[![CRAN status](https://www.r-pkg.org/badges/version/CascadeData)](https://cran.r-project.org/package=CascadeData)
-[![DOI](https://zenodo.org/badge/167803258.svg)](https://zenodo.org/badge/latestdoi/167803258)
-
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
 ```{r setup, include = FALSE}
@@ -15,14 +6,31 @@ knitr::opts_chunk$set(
   comment = "#>",
   fig.path = "man/figures/README-",
   out.width = "100%",
-  dpi=150,fig.width=7
+  dpi=300,fig.width=7,
+  fig.keep="all"
 )
 ```
-# CascadeData
+
+# CascadeData <img src="man/figures/logo.png" align="right" width="200"/>
+
+# Experimental Data of Cascade Experiments in Genomics
+## Frédéric Bertrand and Myriam Maumy-Bertrand
+
+<!-- badges: start -->
+[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-green.svg)](https://lifecycle.r-lib.org/articles/stages.html)
+[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
+[![R-CMD-check](https://github.com/fbertran/CascadeData/workflows/R-CMD-check/badge.svg)](https://github.com/fbertran/CascadeData/actions)
+[![Codecov test coverage](https://codecov.io/gh/fbertran/CascadeData/branch/master/graph/badge.svg)](https://codecov.io/gh/fbertran/CascadeData?branch=master)
+[![CRAN status](https://www.r-pkg.org/badges/version/CascadeData)](https://cran.r-project.org/package=CascadeData)
+[![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/CascadeData)](https://cran.r-project.org/package=CascadeData)
+[![GitHub Repo stars](https://img.shields.io/github/stars/fbertran/CascadeData?style=social)](https://github.com/fbertran/CascadeData)
+[![DOI](https://zenodo.org/badge/167803258.svg)](https://zenodo.org/badge/latestdoi/167803258)
+<!-- badges: end -->
+
 
 The goal of CascadeData is to provide the experimental data [GSE39411](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39411) in a ready to use format. Vallat L, Kemper CA, Jung N, Maumy-Bertrand M, Bertrand F, ..., Bahram S, (2013), "Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia". *Proc Natl Acad Sci USA*, **110**(2):459-64, <https://dx.doi.org/10.1073/pnas.1211130110>.
 
-These are featured as examples by packages such as the Cascade one, a modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. (Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M., 2014, <http://dx.doi.org/10.1093/bioinformatics/btt705>).
+These are featured as examples by packages such as the Cascade one, a modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. (Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M., 2014, <https://dx.doi.org/10.1093/bioinformatics/btt705>).
 
 This website and these examples were created by F. Bertrand and M. Maumy-Bertrand.
 
@@ -60,7 +68,7 @@ Some preliminary between group comparison. First create grouping factor.
 groupf=factor(c(rep("S",ncol(micro_S)),rep("US",ncol(micro_US))))
 ```
 
-Then, create the 2 most discriminative components (probeset linear combinaison, i.e. scores) featuring 100 probesets each using sparse partial least squares discrimant analysis from the [mixOmics](https://www.bioconductor.org/packages/release/bioc/html/mixOmics.html) package, [https://doi.org/doi:10.18129/B9.bioc.mixOmics](doi:10.18129/B9.bioc.mixOmics). An optimal choice of the number of components and of the number of kept genes can be carried out using cross-validation.
+Then, create the 2 most discriminative components (probeset linear combinaison, i.e. scores) featuring 100 probesets each using sparse partial least squares discrimant analysis from the [mixOmics](https://www.bioconductor.org/packages/release/bioc/html/mixOmics.html) package, [doi:10.18129/B9.bioc.mixOmics](https://doi.org/10.18129/B9.bioc.mixOmics). An optimal choice of the number of components and of the number of kept genes can be carried out using cross-validation.
 
 First makes sure that the mixOmics Bioconductor package is installed.
 ```{r mixOmics}
@@ -100,14 +108,14 @@ if (!requireNamespace("limma", quietly = TRUE)){
 }
 ```
 
-Using the [limma](http://bioconductor.org/packages/release/bioc/html/limma.html), [https://doi.org/doi:10.18129/B9.bioc.limma](doi:10.18129/B9.bioc.limma), plotMDS function to create the multidimensional scaling plot of distances between the probeset expression profiles that were selected using splsda.
+Using the [limma](https://bioconductor.org/packages/release/bioc/html/limma.html), [doi:10.18129/B9.bioc.limma](https://doi.org/10.18129/B9.bioc.limma), plotMDS function to create the multidimensional scaling plot of distances between the probeset expression profiles that were selected using splsda.
 ```{r plotMDS}
 limma::plotMDS(cbind(micro_S,micro_US)[selectedprobesets,])
 ```
 
 ### Entrez GeneIDs
 
-The [jetset](https://cran.r-project.org/package=jetset) package enables the selection of optimal probe sets from the HG-U95Av2, HG-U133A, HG-U133 Plus 2.0, or U133 X3P microarray platforms. It requires the [org.Hs.eg.db](https://bioconductor.org/packages/release/data/annotation/html/org.Hs.eg.db.html) Bioconductor package, [https://doi.org/doi:10.18129/B9.bioc.org.Hs.eg.db](doi:10.18129/B9.bioc.org.Hs.eg.db).
+The [jetset](https://cran.r-project.org/package=jetset) package enables the selection of optimal probe sets from the HG-U95Av2, HG-U133A, HG-U133 Plus 2.0, or U133 X3P microarray platforms. It requires the [org.Hs.eg.db](https://bioconductor.org/packages/release/data/annotation/html/org.Hs.eg.db.html) Bioconductor package, [doi:10.18129/B9.bioc.org.Hs.eg.db](https://doi.org/10.18129/B9.bioc.org.Hs.eg.db).
 
 
 First makes sure that the jetset CRAN package and the org.Hs.eg.db Bioconductor package are installed.
@@ -137,7 +145,7 @@ micro_US_jetset<-micro_US[resjetset,]
 rownames(micro_US_jetset)<-names(resjetset)
 ```
 
-Then, create the 2 most discriminative components (probeset linear combinaison, i.e. scores) featuring 100 probesets each using sparse partial least squares discrimant analysis from the [mixOmics](https://www.bioconductor.org/packages/release/bioc/html/mixOmics.html) package, [https://doi.org/doi:10.18129/B9.bioc.mixOmics](doi:10.18129/B9.bioc.mixOmics). An optimal choice of the number of components and of the number of kept genes can be carried out using cross-validation.
+Then, create the 2 most discriminative components (probeset linear combinaison, i.e. scores) featuring 100 probesets each using sparse partial least squares discrimant analysis from the [mixOmics](https://www.bioconductor.org/packages/release/bioc/html/mixOmics.html) package, [doi:10.18129/B9.bioc.mixOmics](https://doi.org/10.18129/B9.bioc.mixOmics). An optimal choice of the number of components and of the number of kept genes can be carried out using cross-validation.
 
 First makes sure that the mixOmics Bioconductor package is installed.
 ```{r splsdaegid}
@@ -168,7 +176,7 @@ if (!requireNamespace("limma", quietly = TRUE)){
 }
 ```
 
-Using the [limma](http://bioconductor.org/packages/release/bioc/html/limma.html), [https://doi.org/doi:10.18129/B9.bioc.limma](doi:10.18129/B9.bioc.limma), plotMDS function to create the multidimensional scaling plot of distances between the Entrez GeneID expression profiles that were selected using splsda.
+Using the [limma](https://bioconductor.org/packages/release/bioc/html/limma.html), [doi:10.18129/B9.bioc.limma](https://doi.org/10.18129/B9.bioc.limma), plotMDS function to create the multidimensional scaling plot of distances between the Entrez GeneID expression profiles that were selected using splsda.
 ```{r plotMDSegid}
 limma::plotMDS(cbind(micro_S,micro_US)[selectedEntrezGeneIDs,])
 ```