correction d'un bug sur mcq.compute.protein.abundance en TOP3 qui fait la...

correction d'un bug sur mcq.compute.protein.abundance en TOP3 qui fait la somme des log au lieu de la siomme des aires

MCQR/DESCRIPTION

@@ -2,7 +2,7 @@ Package: MCQR
 Type: Package
 Title: a R Package for Analysis of Mass-Spectrometry-Based Proteomics Data
 Version: 0.6.7
-Date: 2022-11-29
+Date: 2022-12-02
 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")),

MCQR/R/mcq_compute_protein_abundance.R

@@ -109,18 +109,22 @@ mcq.compute.protein.abundance = function (object, method="sum") {
 			  # controle nb pep
 			  if(length(unique(mean_pep$ncount)) != 1){
 			    warning(cat("missing values for some peptide for Protein ", unique(tab$protein)))
-			  }
-			  mean_pep <- setorderv(mean_pep, "mean_int", order=-1, na.last=TRUE)
-			  mean_pep <- head(mean_pep, topN)
-			  mean_pep$ncount = length(unique(mean_pep$peptiz))
-			  return(mean_pep)
+					return(NULL)
+			  }else{
+				  mean_pep <- setorderv(mean_pep, "mean_int", order=-1, na.last=TRUE)
+				  mean_pep <- head(mean_pep, topN)
+				  mean_pep$ncount = length(unique(mean_pep$peptiz))
+				  return(mean_pep)
+				}
 			}
 
 
 			list_tab_pep <- lapply(list_tab_pep, select_topN, topN)
 			select_peptiz = rbindlist(list_tab_pep)
 			tab = tab[tab$peptiz %in% select_peptiz$peptiz,]
+			tab$q <- 10^tab$q
 			tprot <- as.data.frame(tab[, list(q =sum(q)), by=c("accession", "msrun")])
+			tprot$q <- log10(tprot$q)
 		}
 
 		#Add nb of peptides used to compute the abundance of a protein in a msrun

MCQR/inst/extdata/lanceur_reference.R

-# Lanceur version 0.6.7
+# Lanceur version 0.6.8
 
 
 #-------------------------------------------------------------------------------------------------------------------------------------------------------------------

MCQR/inst/extdata/lanceur_reference_phospho.R

-# Lanceur version 0.6.7
+# Lanceur version 0.6.8
 
 ### lanceur reference phoshpo label fraction
 

MCQR/inst/extdata/lanceur_reference_sds.R

-# Lanceur version 0.6.7
+# Lanceur version 0.6.8
 
 
 #-------------------------------------------------------------------------------------------------------------------------------------------------------------------

MCQR/man/mcq.compute.protein.abundance.Rd

@@ -10,10 +10,10 @@
 
 \arguments{
 	\item{object}{an object of class 'cmcq.pepq.masschroq' or 'cmcq.pepq.by.track'.}
-	\item{method}{a character string indicating the method to aggregate peptide intensity values into protein abundance. Must be "model", "sum" or "mean".}
+	\item{method}{a character string indicating the method to aggregate peptide intensity values into protein abundance. Must be "model", "sum", "mean" or "TopN" with N between 1 to 5.}
 }
 
-\details{If method="sum" or method="model", protein abundances are computed as the sum or the mean of non log-transformed peptide intensity values. The protein abundance values thus obtained are log-transformed for subsequent statistical analysis. If method="model", protein abundances are computed as adjusted means from a linear mixed model derived from Blein-Nicolas et al. (2012) taking into account a peptide effect as fixed effect and a sample effect as random effect. In that case, only proteins represented by a minimum of 2 peptide-mz can be considered (those represented by a single peptide-mz are removed from the dataset.}
+\details{If method="sum" or method="model", protein abundances are computed as the sum or the mean of non log-transformed peptide intensity values. The protein abundance values thus obtained are log-transformed for subsequent statistical analysis. If method="model", protein abundances are computed as adjusted means from a linear mixed model derived from Blein-Nicolas et al. (2012) taking into account a peptide effect as fixed effect and a sample effect as random effect. In that case, only proteins represented by a minimum of 2 peptide-mz can be considered (those represented by a single peptide-mz are removed from the dataset).For TopN method, the N Most intense peptide in average for the experiment are selected, then summed to obtain protein values. if there are no more than N peptides in the dataset then all peptides are retained for the calculation.}
 
 \value{'mcq.compute.protein.abundance' returns an object of class 'cmcq.protq.xic'.}