Progeny New website

.gitignore

@@ -9,3 +9,5 @@ vignettes/17ea135933f4_TableS4A.xlsx
 vignettes/17ea37d9483_Cell_line_RMA_proc_basalExp.txt.zip
 vignettes/BiocFileCache.sqlite
 README.html
+vignettes/2fe218797e34_Cell_line_RMA_proc_basalExp.txt.zip
+vignettes/2fe2590a3b08_TableS4A.xlsx

DESCRIPTION

@@ -1,11 +1,27 @@
 Package: progeny
 Title: Pathway RespOnsive GENes for activity inference from gene expression
-Version: 1.9.6
-Author: Michael Schubert <mschu.dev@gmail.com>,
-	 Igor Bulanov,
-	 Alberto Valdeolivas,	
-	 Christian Holland
-Maintainer: Alberto Valdeolivas <alvaldeolivas@gmail.com>
+Version: 1.9.7
+Authors@R: c(
+    person(given = "Michael",
+           family = "Schubert",
+           role = "aut"),
+    person(given = "Alberto",
+           family = "Valdeolivas",
+           role = c("cre","ctb"),
+           email = "alvaldeolivas@gmail.com",
+           comment = c(ORCID = "0000-0001-5482-9023")),
+    person(given = "Christian H.",
+           family = "Holland",
+           role = "ctb",
+           email = "cholland2408@gmail.com",
+           comment = c(ORCID = "0000-0002-3060-5786")),
+    person(given = "Igor",
+           family = "Bulanov",
+           role = "ctb"),
+    person(given = "Aurélien",
+           family = "Dugourd",
+           role = "ctb")
+           )
 Description: This package provides a function to infer pathway activity
     from gene expression using PROGENy. It contains the linear model we
     inferred in the publication "Perturbation-response genes reveal signaling
@@ -41,4 +57,4 @@ Suggests:
     tibble,
     testthat (>= 2.1.0)
 VignetteBuilder: knitr
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.0

NEWS → NEWS.md

@@ -1,7 +1,10 @@
-progeny v2.0.0 (Release date: 2020-03-25)
-==============
+## Progeny v1.9.7 (Release date: 2020-04-27)
 
-Changes:
+* PROGENy website development
+
+## Progeny v1.9.6 (Release date: 2020-04-27) 
+
+Major update with the following main points:
 
 * Added the mouse model matrix containing 14 pathways
 

R/progenyPermutations.r

@@ -1,6 +1,4 @@
-#'This function is designed to compute progeny pathway scores and assesses
-#'their significance using a gene sampling-based permutation strategy, for 
-#'a series of experimental samples/contrasts.
+#'Compute progeny pathway scores and assesses significance based on permutations
 #'
 #'@param df A data.frame of n*m+1 dimension, where n is the number of omic
 #'features to be considered and m is the number of samples/contrasts.

R/progenySuppFunc.r

@@ -145,8 +145,8 @@ progenyScatter <- function(df,weight_matrix,dfID = 1, weightID = 1,
 #' #assign a path to store your plots
 #' dirpath <- "./progeny_plots/"
 #' 
-#' #save it
-#' saveProgenyPlots(plots, contrast_names, dirpath)
+#' # save it
+#' # saveProgenyPlots(plots, contrast_names, dirpath)
 #' @return This function produces the pdf files of plots taken from the 
 #' progenyScatter function
 #'@export

README.md

@@ -1,5 +1,9 @@
-PROGENy: Pathway RespOnsive GENes for activity inference
-========================================================
+<img src="man/Figures/tool_logo.png" align="left" height="100">
+
+# PROGENy: Pathway RespOnsive GENes for activity inference  
+
+
+## Overview
 
 Aberrant cell signaling is known to cause cancer and many other diseases, as
 well as a focus of treatment. A common approach is to infer its activity on the
@@ -33,13 +37,34 @@ This is an R package for using the method described in
 }
 ```
 
+## Installation
+
+Progeny is available in [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/progeny.html). In addition, one can install the development version from the Github
+repository: 
+
+```r
+## To install the package from Bioconductor
+if (!requireNamespace("BiocManager", quietly = TRUE))
+    install.packages("BiocManager")
+
+BiocManager::install("progeny")
+
+## To install the development version from the Github repo:
+devtools::install_github("saezlab/progeny")
+```
+
+## Updates
+
+Since the original release, we have implemented some extensions in PROGENy:
+
 ### Update #1 - Extension to mouse
 
 Originally PROGENy was developed for the application to human data. 
 In a benchmark study we showed that PROGENy is also applicable to mouse data, 
-as described in Holland et al., 2019. Accordingly, we included new parameters to 
-run mouse version of PROGENy by transforming the human genes to their mouse 
-orthologs.
+as described in 
+[Holland et al., 2019](https://doi.org/10.1016/j.bbagrm.2019.194431). 
+Accordingly, we included new parameters to run mouse version of PROGENy by 
+transforming the human genes to their mouse orthologs.
 
 ### Update #2 - Expanding Pathway Collection
 
@@ -50,22 +75,22 @@ WNT.
 
 Recent technological advances in single-cell RNA-seq enable the profiling of 
 gene expression at the individual cell level. We showed that PROGENy can be 
-applied to scRNA-seq data, as described in Holland et al., 2020.
+applied to scRNA-seq data, as described in [Holland et al., 2020](https://doi.org/10.1186/s13059-020-1949-z)
 
-### Citing PROGENy
+## Citing PROGENy
 
-Besides the original paper, there are additional publication expanding the 
-usage of PROGENy.
+Besides the original paper, there are two additional publication 
+describing expansions of PROGENy usage.
 
 - If you use PROGENy for your research please cite the original publication:
 
-Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. “Perturbation-response genes reveal signaling footprints in cancer gene expression.” Nature Communications. DOI: 10.1038/s41467-017-02391-6.
+> Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. “Perturbation-response genes reveal signaling footprints in cancer gene expression.” _Nature Communications_: [10.1038/s41467-017-02391-6](https://doi.org/10.1038/s41467-017-02391-6)
 
 - If you use for mouse or you use the expanded version containing 14 pathways, 
 please cite additionally:
 
-Holland CH, Szalai B, Saez-Rodriguez J. “Transfer of regulatory knowledge from human to mouse for functional genomics analysis.” Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 2019. DOI: 10.1016/j.bbagrm.2019.194431.
+> Holland CH, Szalai B, Saez-Rodriguez J. "Transfer of regulatory knowledge from human to mouse for functional genomics analysis." _Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms._ 2019. DOI: [10.1016/j.bbagrm.2019.194431](https://doi.org/10.1016/j.bbagrm.2019.194431).
 
 - If you apply PROGENy on single-cell RNA-seq data please cite additionally:
 
-Holland CH, Tanevski J, Perales-Patón J, Gleixner J, Kumar MP, Mereu E, Joughin BA, Stegle O, Lauffenburger DA, Heyn H, Szalai B, Saez-Rodriguez, J. “Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data.” Genome Biology. 2020. DOI: 10.1186/s13059-020-1949-z.
+> Holland CH, Tanevski J, Perales-Patón J, Gleixner J, Kumar MP, Mereu E, Joughin BA, Stegle O, Lauffenburger DA, Heyn H, Szalai B, Saez-Rodriguez, J. "Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data." _Genome Biology._ 2020. DOI: [10.1186/s13059-020-1949-z](https://doi.org/10.1186/s13059-020-1949-z).

_pkgdown.yml

@@ -0,0 +1,13 @@
+destination: docs
+url: https://saezlab.github.io/progeny
+navbar:
+  structure:
+    left: [home, intro, reference, articles, tutorials, news]
+    right: [github, twitter, homepage]
+  components:
+     twitter:
+       icon: "fab fa-twitter fa-lg"
+       href: https://twitter.com/saezlab
+     homepage:
+       icon: "fas fa-university"
+       href: http://www.saezlab.org