dernière maj avant soumission

nouvelle version

Dockerfile

@@ -21,7 +21,7 @@ ADD MCQR /mcqr/MCQR/
 
 RUN R CMD build --resave-data MCQR
 
-RUN R CMD INSTALL MCQR_0.6.4.tar.gz
+RUN R CMD INSTALL MCQR_0.6.5.tar.gz
 
 ADD Tools/Python /mcqr/Tools/Python/
 VOLUME /mcqr/docker_output

MCQR/DESCRIPTION

 Package: MCQR
 Type: Package
 Title: a R Package for Analysis of Mass-Spectrometry-Based Proteomics Data
-Version: 0.6.4
-Date: 2022-08-05
+Version: 0.6.5
+Date: 2022-08-08
 Authors@R: c(person("Balliau", "Thierry", email="thierry.balliau@inrae.fr", role=c("aut", "cre")),
 						 person("Blein-Nicolas", "Mélisande", email="melisande.blein-nicolas@inrae.fr", role=c("aut")),
 						 person("Langella", "Olivier", email="olivier.langella@universite-paris-sud.fr", role=c("aut")),
 						 person("Zivy", "Michel", email="michel.zivy@universite-paris-saclay.fr", role=c("aut")),
 						 person("Aubert-Frambourg", "Anne", email="anne.aubert-frambourg@inrae", role=c("aut")))
-Description: This package is offering a standardised toolkit to process and analyse quantification data from bottom-up proteomics experiments, including label-free shotgun experiments, isotopic labeling experiments, fractionation-based experiments and experiments based on enrichment in post-translational modifications. MCQR contains all the necessary functions to analyse spectral counts (SC) or extracted ion current (XIC) data. It also contains functions to export analysis results as graphical representations in pdf format or as data tables in tsv or txt format. MCQR is directly interoperable with MassChroQ (Valot et al. 2011, <doi.org/10.1002/pmic.201100120>) and X!TandemPipeline (Langella et al. 2017, <doi.org/10.1021/acs.jproteome.6b00632>). It can also take input data from other quantification software provided that they are adequately formatted.
+Description: Standardised toolkit to process and analyse quantification data from bottom-up proteomics experiments, including label-free shotgun experiments, isotopic labeling experiments, fractionation-based experiments and experiments based on enrichment in post-translational modifications. MCQR contains all the necessary functions to analyse spectral counts (SC) or extracted ion current (XIC) data. It also contains functions to export analysis results as graphical representations in pdf format or as data tables in tsv or txt format. MCQR is directly interoperable with MassChroQ (Valot et al. 2011, <doi.org/10.1002/pmic.201100120>) and X!TandemPipeline (Langella et al. 2017, <doi.org/10.1021/acs.jproteome.6b00632>). It can also take input data from other quantification software provided that they are adequately formatted.
 URL: https://forgemia.inra.fr/pappso/mcqr
 Encoding: UTF-8
 License: GPL (>= 3)

MCQR/R/mcq_write_scenarios.R

@@ -13,7 +13,7 @@ mcq.write.scenarios <- function(directory="."){
   status=TRUE
   i=1
   lanceur = c("lanceur_reference.R", "lanceur_reference_sds.R", "lanceur_reference_phospho.R")
-    while(status & (i<length(lanceur))){
+    while(status & (i<length(lanceur)+1)){
       status = file.copy(system.file("extdata", lanceur[i], package="MCQR"), directory, overwrite = TRUE)
       i= i+1
     }

MCQR/man/MCQR-package.Rd

@@ -3,16 +3,14 @@
 \alias{MCQR}
 \docType{package}
 \title{MCQR: a R package for analysis of mass-spectrometry-based proteomics data}
-\description{Offering a standardised toolkit to process and analyse quantification data from bottom-up proteomics experiments, including label-free shotgun experiments, isotopic labeling experiments, fractionation-based experiments and experiments based on enrichment in post-translational modifications. MCQR contains all the necessary functions to analyse spectral counts (SC) or extracted ion current (XIC) data. It also contains functions to export analysis results as graphical representations in pdf format or as data tables in tsv or txt format. MCQR is directly interoperable with MassChroQ (Valot et al. 2011, https://doi.org/10.1002/pmic.201100120) and X!TandemPipeline (Langella et al. 2017, https://doi.org/10.1021/acs.jproteome.6b00632). It can also take input data from other quantification software provided that they are adequately formatted.}
+\description{
+Standardised toolkit to process and analyse quantification data from bottom-up proteomics experiments, including label-free shotgun experiments, isotopic labeling experiments, fractionation-based experiments and experiments based on enrichment in post-translational modifications.
+
+MCQR contains all the necessary functions to analyse spectral counts (SC) or extracted ion current (XIC) data.It also contains functions to export analysis results as graphical representations in pdf format or as data tables in tsv or txt format.
+
+MCQR is directly interoperable with MassChroQ (Valot et al. 2011, https://doi.org/10.1002/pmic.201100120) and X!TandemPipeline (Langella et al. 2017, https://doi.org/10.1021/acs.jproteome.6b00632). It can also take input data from other quantification software provided that they are adequately formatted.}
 \details{
-\tabular{ll}{
-Package: \tab MCQR\cr
-Type: \tab Package\cr
-Version: \tab 0.6.4\cr
-Date: \tab 2022-08-05\cr
-License: \tab GPLv3\cr
-Depends: \tab methods\cr
-}
+You can find more information in http://pappso.inrae.fr/bioinfo/mcqr/. Tutorial videos are also available at http://pappso.inrae.fr/formations/tutoriels/.
 }
 \author{
 the PAPPSO team (pappso-projetsbioinfo@groupes.renater.fr)
@@ -21,6 +19,11 @@ Maintainer: Thierry Balliau <thierry.balliau@inrae.fr>
 
 \keyword{ package }
 \examples{
+  # execute 'mcq.write.scenarios to get examples of analysis'
+  \dontrun{
+    mcq.write.scenarios(".")
+  }
+  # you can open one of it with your favorite R IDE to guide you throw the steps
   # Execute 'mcq.read.masschroq'
   	myxic <- mcq.read.masschroq(
     protFile=system.file("extdata", "XIC_result_prot.tsv", package = "MCQR", mustWork = TRUE),

changelog.md

+# Version 0.6.5
+First submission in cran
+
+* bug fixe in mcq.write.scenarios that does not write lanceur_reference_phospo.R
+* update description in DESCRIPTION and mcqr-package.Rd and details in mcqr-package.Rd
+* update authors list and role for cran submission
 * modification of call 'if(class(object) == "name of class")' by 'if(is(object, "name of class"))' for cran compatibility