@@ -1,8 +1,13 @@

 Package: StarBioTrek

 Type: Package

 Title: StarBioTrek

+<<<<<<< .mine

+Version: 1.2.1

+Date: 05-12-2017

+=======

 Version: 1.3.0

 Date: 02-08-2017

+>>>>>>> .r129550

 Author: Claudia Cava,

     Isabella Castiglioni

 Maintainer: Claudia Cava <claudia.cava@ibfm.cnr.it>

@@ -37,4 +42,4 @@ VignetteBuilder: knitr

 LazyData: true

 URL: https://github.com/claudiacava/StarBioTrek

 BugReports: https://github.com/claudiacava/StarBioTrek/issues

-RoxygenNote: 5.0.1

\ No newline at end of file

+RoxygenNote: 6.0.1

@@ -30,12 +30,12 @@ if (KEGG_path=="Carb_met") {

     a<-c[[2]]

   }

   if (KEGG_path=="Gly_bio_met") {

-    mer<-select_path_gly(Glybio_met)

+    mer<-select_path_gly(Glybio_met) 

     c<-proc_path(mer)

     a<-c[[2]]

   }

   if (KEGG_path=="Cof_vit_met") {

-    mer<-select_path_gly(Cofa_vita_met)

+    mer<-select_path_cofa(Cofa_vita_met)

     c<-proc_path(mer)

     a<-c[[2]]

   }

@@ -97,6 +97,7 @@ return(mer)

 }

 select_path_gly<-function(Glybio_met){ 

+  species<-c("- Homo sapiens (human)") 

 ac<-paste("N-Glycan biosynthesis", species)

 ad<-paste("Various types of N-glycan biosynthesis", species)

 ae<-paste("Mucin type O-Glycan biosynthesis", species)

@@ -9,4 +9,3 @@

 TCGA data

 }

 \keyword{internal}

-

@@ -20,4 +20,3 @@ GE_matrix creates a matrix of gene expression for pathways given by the user.

 \examples{

 list_path_gene<-GE_matrix(DataMatrix=tumo[,1:2],pathway=path)

 }

-

@@ -20,4 +20,3 @@ select two labels from ID barcode

 \examples{

 tumo<-SelectedSample(Dataset=Data_CANCER_normUQ_filt,typesample="tumor")[,2]

 }

-

@@ -14,4 +14,3 @@ The functions you're likely to need from \pkg{StarBioTrek} is

 Otherwise refer to the vignettes to see

 how to format the documentation.

 }

-

@@ -20,4 +20,3 @@ average creates a matrix with a summarized value for each pathway

 \examples{

 score_mean<-average(dataFilt=tumo[,1:2],path)

 }

-

@@ -20,4 +20,3 @@ ds_score_crtlk creates a matrix with  discriminating score for pathways

 \examples{

 cross_talk_st_dv<-ds_score_crtlk(dataFilt=tumo[,1:2],pathway=path)

 }

-

@@ -20,4 +20,3 @@ euc_dist_crtlk creates a matrix with euclidean distance for pairwise pathways

 \examples{

 score_euc_dista<-euc_dist_crtlk(dataFilt=tumo[,1:2],path)

 }

-

@@ -18,4 +18,3 @@ getKEGGdata creates a data frame with human KEGG pathway. Columns are the pathwa

 \examples{

 path<-getKEGGdata(KEGG_path="Transcript")

 }

-

@@ -25,4 +25,3 @@ Network category can be filtered among: physical interactions, co-localization,

 organism="Saccharomyces_cerevisiae"

 netw<-getNETdata(network="SHpd",organism)

 }

-

@@ -21,4 +21,3 @@ list_path_net creates a list of interacting genes for each human pathway.

 lista_netw<-path_net(pathway=path,data=netw)

 list_path<-list_path_net(lista_net=lista_netw,pathway=path)

 }

-

@@ -9,4 +9,3 @@

 A matrix of gene expression for pathways given by the user.

 }

 \keyword{internal}

-

@@ -20,4 +20,3 @@ GE_matrix creates a matrix of mean gene expression for pathways given by the use

 \examples{

 list_path_plot<-matrix_plot(DataMatrix=tumo[,1:2],pathway=path)

 }

-

@@ -9,4 +9,3 @@

 network data

 }

 \keyword{internal}

-

@@ -9,4 +9,3 @@

 TCGA data with normal samples

 }

 \keyword{internal}

-

@@ -9,4 +9,3 @@

 Pathway data from KEGG

 }

 \keyword{internal}

-

@@ -20,4 +20,3 @@ path_net creates a list of network data for each human pathway. The network data

 \examples{

 lista_net<-path_net(pathway=path,data=netw)

 }

-

@@ -22,4 +22,3 @@ plotting_matrix creates a matrix of gene expression for pathways given by the us

 \examples{

 mt<-plotting_cross_talk(DataMatrix=tumo[,1:2],pathway=path,path_matrix=list_path_plot)

 }

-

@@ -15,4 +15,3 @@ dataframe with human pathway data

 \description{

 getKEGGdata creates a data frame with human KEGG pathway. Columns are the pathways and rows the genes inside those pathway

 }

-

@@ -17,4 +17,3 @@ a gene expression matrix for case study 1

 \description{

 processing gene expression matrix

 }

-

@@ -9,4 +9,3 @@

 Score Matrix of pairwise pathway using euclidean distance

 }

 \keyword{internal}

-

@@ -17,4 +17,3 @@ a gene expression matrix with only pairwise pathway with a particular cut-off

 \description{

 select two labels from ID barcode

 }

-

@@ -20,4 +20,3 @@ st_dv creates a matrix with standard deviation for pathways

 \examples{

 stand_dev<-st_dv(DataMatrix=tumo[,1:2],pathway=path)

 }

-

@@ -26,4 +26,3 @@ nf <- 60

 res_class<-svm_classification(TCGA_matrix=score_euc_dist,nfs=nf,

 normal=colnames(norm[,1:10]),tumour=colnames(tumo[,1:10]))

 }

-

@@ -9,4 +9,3 @@

 TCGA data with tumour samples

 }

 \keyword{internal}

-