@@ -257,13 +257,15 @@ TCGAanalyze_Preprocessing <- function(

 #'

 #'  # If the groups are not specified group1 == group2 and all samples are used

 #'  \dontrun{

-#'  tabSurvKM <- TCGAanalyze_SurvivalKM(clinical_patient_Cancer,

-#'                                      dataBRCAcomplete,

-#'                                      Genelist = rownames(dataBRCAcomplete),

-#'                                      Survresult = TRUE,

-#'                                      p.cut = 0.2,

-#'                                      ThreshTop = 0.67,

-#'                                      ThreshDown = 0.33)

+#'  tabSurvKM <- TCGAanalyze_SurvivalKM(

+#'    clinical_patient_Cancer,

+#'    dataBRCAcomplete,

+#'    Genelist = rownames(dataBRCAcomplete),

+#'    Survresult = TRUE,

+#'    p.cut = 0.2,

+#'     ThreshTop = 0.67,

+#'     ThreshDown = 0.33

+#'   )

 #' }

 TCGAanalyze_SurvivalKM <- function(

         clinical_patient,

@@ -359,9 +361,9 @@ TCGAanalyze_SurvivalKM <- function(

             samples_down_mRNA_selected <- names(mRNAselected_values_ordered[firstelementDOWN:numberOfSamples])

             # Which samples are in the intermediate group (above ThreshLow and below ThreshTop)

-            samples_UNCHANGED_mRNA_selected <- names(mRNAselected_values_newvector[which((mRNAselected_values_newvector) > mRNAselected_values_ordered_down &

-                                                                                             mRNAselected_values_newvector < mRNAselected_values_ordered_top

-            )])

+            samples_UNCHANGED_mRNA_selected <- names(mRNAselected_values_newvector[

+                which((mRNAselected_values_newvector) > mRNAselected_values_ordered_down &  mRNAselected_values_newvector < mRNAselected_values_ordered_top

+                )])

             cfu_onlyTOP <- cfu_complete[cfu_complete[, "bcr_patient_barcode"] %in% samples_top_mRNA_selected, ]

             cfu_onlyDOWN <- cfu_complete[cfu_complete[, "bcr_patient_barcode"] %in% samples_down_mRNA_selected, ]

@@ -1417,9 +1419,13 @@ TCGAanalyze_EAcomplete <- function(TFname, RegulonList) {

 #' \dontrun{

 #' EAGenes <- get("EAGenes")

 #' RegulonList <- rownames(dataDEGsFiltLevel)

-#' ResBP <- TCGAanalyze_EA(GeneName="DEA genes Normal Vs Tumor",

-#'                            RegulonList,DAVID_BP_matrix,

-#'                            EAGenes,GOtype = "DavidBP")

+#' ResBP <- TCGAanalyze_EA(

+#'   GeneName="DEA genes Normal Vs Tumor",

+#'   RegulonList = RegulonList,

+#'   TableEnrichment = DAVID_BP_matrix,

+#'    EAGenes = EAGenes,

+#'    GOtype = "DavidBP"

+#'  )

 #'}

 TCGAanalyze_EA <- function (

         GeneName,

@@ -1833,9 +1839,9 @@ gaiaCNVplot <- function (calls,  threshold = 0.01) {

     rownames(Calls) <- NULL

     Chromo <- Calls[, grep("chr", colnames(calls), ignore.case = TRUE)]

     Gains <- apply(Calls, 1, function(x)

-            ifelse(x[grep("aberration", colnames(calls), ignore.case = TRUE)] == 1, x["score"], 0))

+        ifelse(x[grep("aberration", colnames(calls), ignore.case = TRUE)] == 1, x["score"], 0))

     Losses <- apply(Calls, 1, function(x)

-            ifelse(x[grep("aberration", colnames(calls), ignore.case = TRUE)] == 0, x["score"], 0))

+        ifelse(x[grep("aberration", colnames(calls), ignore.case = TRUE)] == 0, x["score"], 0))

     plot(

         Gains,

         ylim = c(-max(Calls[, "score"] + 2), max(Calls[, "score"] + 2)),

@@ -414,6 +414,7 @@ GDCquery_clinic <- function(

 #' clinical.drug <- GDCprepare_clinic(query,"drug")

 #' clinical.radiation <- GDCprepare_clinic(query,"radiation")

 #' clinical.admin <- GDCprepare_clinic(query,"admin")

+#' \dontrun{

 #' query <- GDCquery(

 #'    project = "TCGA-COAD",

 #'    data.category = "Biospecimen",

@@ -426,6 +427,7 @@ GDCquery_clinic <- function(

 #' clinical.drug <- GDCprepare_clinic(query,"sample")

 #' clinical.radiation <- GDCprepare_clinic(query,"portion")

 #' clinical.admin <- GDCprepare_clinic(query,"slide")

+#' }

 GDCprepare_clinic <- function(

         query,

         clinical.info,

@@ -16,11 +16,13 @@

 #' @importFrom methods is

 #' @export

 #' @examples

-#' query <- GDCquery(project = "TCGA-ACC",

-#'                  data.category =  "Copy number variation",

-#'                  legacy = TRUE,

-#'                  file.type = "hg19.seg",

-#'                  barcode = c("TCGA-OR-A5LR-01A-11D-A29H-01", "TCGA-OR-A5LJ-10A-01D-A29K-01"))

+#' query <- GDCquery(

+#'   project = "TCGA-ACC",

+#'   data.category =  "Copy number variation",

+#'   legacy = TRUE,

+#'   file.type = "hg19.seg",

+#'   barcode = c("TCGA-OR-A5LR-01A-11D-A29H-01", "TCGA-OR-A5LJ-10A-01D-A29K-01")

+#'  )

 #' # data will be saved in  GDCdata/TCGA-ACC/legacy/Copy_number_variation/Copy_number_segmentation

 #' GDCdownload(query, method = "api")

 #' \dontrun{

@@ -472,7 +472,7 @@ GDCquery <- function(

                                        is_ffpe = ifelse("is_ffpe" %in% colnames(x),any(is_ffpe),NA),

                                        sample_type =  paste(sample_type,collapse = ";"),

                                        aliquot.submiter.id = paste(unlist(rbindlist(x$samples))[grep("portions.analytes.aliquots.submitter_id",names(unlist(rbindlist(x$samples))))],collapse = ";")

-                                       )

+                                   )

                                }) %>% as.data.frame

         } else {

             aux <- plyr::laply(results$cases,

@@ -719,12 +719,17 @@ getGDCquery <- function(project, data.category, data.type, legacy, workflow.type

     # Close json request

     options.filter <- paste0(options.filter, URLencode(']}'))

-    url <- paste0(baseURL,paste(options.pretty,

-                                options.expand,

-                                option.size,

-                                options.filter,

-                                option.format,

-                                sep = "&"))

+    url <- paste0(

+        baseURL,

+        paste(

+            options.pretty,

+            options.expand,

+            option.size,

+            options.filter,

+            option.format,

+            sep = "&"

+        )

+    )

     return(url)

 }

@@ -741,11 +746,13 @@ addFilter <- function(field, values){

 expandBarcodeInfo <- function(barcode){

     if(any(grepl("TARGET",barcode))) {

-        ret <- DataFrame(barcode = barcode,

-                         code = substr(barcode, 8, 9),

-                         case.unique.id = substr(barcode, 11, 16),

-                         tissue.code = substr(barcode, 18, 19),

-                         nucleic.acid.code = substr(barcode, 24, 24))

+        ret <- DataFrame(

+            barcode = barcode,

+            code = substr(barcode, 8, 9),

+            case.unique.id = substr(barcode, 11, 16),

+            tissue.code = substr(barcode, 18, 19),

+            nucleic.acid.code = substr(barcode, 24, 24)

+        )

         ret <- merge(ret,getBarcodeDefinition(), by = "tissue.code", sort = FALSE, all.x = TRUE)

         ret <- ret[match(barcode,ret$barcode),]

     }

@@ -763,62 +770,72 @@ expandBarcodeInfo <- function(barcode){

 getBarcodeDefinition <- function(type = "TCGA"){

     if(type == "TCGA"){

-        tissue.code <- c('01','02','03','04','05','06','07','08','09','10','11',

-                         '12','13','14','20','40','50','60','61')

-        shortLetterCode <- c("TP","TR","TB","TRBM","TAP","TM","TAM","THOC",

-                             "TBM","NB","NT","NBC","NEBV","NBM","CELLC","TRB",

-                             "CELL","XP","XCL")

-

-        tissue.definition <- c("Primary Tumor",

-                               "Recurrent Tumor",

-                               "Primary Blood Derived Cancer - Peripheral Blood",

-                               "Recurrent Blood Derived Cancer - Bone Marrow",

-                               "Additional - New Primary",

-                               "Metastatic",

-                               "Additional Metastatic",

-                               "Human Tumor Original Cells",

-                               "Primary Blood Derived Cancer - Bone Marrow",

-                               "Blood Derived Normal",

-                               "Solid Tissue Normal",

-                               "Buccal Cell Normal",

-                               "EBV Immortalized Normal",

-                               "Bone Marrow Normal",

-                               "Control Analyte",

-                               "Recurrent Blood Derived Cancer - Peripheral Blood",

-                               "Cell Lines",

-                               "Primary Xenograft Tissue",

-                               "Cell Line Derived Xenograft Tissue")

+        tissue.code <- c(

+            '01','02','03','04','05','06','07','08','09','10','11',

+            '12','13','14','20','40','50','60','61'

+        )

+        shortLetterCode <- c(

+            "TP","TR","TB","TRBM","TAP","TM","TAM","THOC",

+            "TBM","NB","NT","NBC","NEBV","NBM","CELLC","TRB",

+            "CELL","XP","XCL"

+        )

+

+        tissue.definition <- c(

+            "Primary Tumor",

+            "Recurrent Tumor",

+            "Primary Blood Derived Cancer - Peripheral Blood",

+            "Recurrent Blood Derived Cancer - Bone Marrow",

+            "Additional - New Primary",

+            "Metastatic",

+            "Additional Metastatic",

+            "Human Tumor Original Cells",

+            "Primary Blood Derived Cancer - Bone Marrow",

+            "Blood Derived Normal",

+            "Solid Tissue Normal",

+            "Buccal Cell Normal",

+            "EBV Immortalized Normal",

+            "Bone Marrow Normal",

+            "Control Analyte",

+            "Recurrent Blood Derived Cancer - Peripheral Blood",

+            "Cell Lines",

+            "Primary Xenograft Tissue",

+            "Cell Line Derived Xenograft Tissue")

         aux <- data.frame(tissue.code = tissue.code,shortLetterCode,tissue.definition)

     } else {

-        tissue.code <- c('01','02','03','04','05','06','07','08','09','10','11',

-                         '12','13','14','15','16','17','20','40','41','42','50','60','61','99')

-

-        tissue.definition <- c("Primary Tumor", # 01

-                               "Recurrent Tumor", # 02

-                               "Primary Blood Derived Cancer - Peripheral Blood", # 03

-                               "Recurrent Blood Derived Cancer - Bone Marrow", # 04

-                               "Additional - New Primary", # 05

-                               "Metastatic", # 06

-                               "Additional Metastatic", # 07

-                               "Tissue disease-specific post-adjuvant therapy", # 08

-                               "Primary Blood Derived Cancer - Bone Marrow", # 09

-                               "Blood Derived Normal", # 10

-                               "Solid Tissue Normal",  # 11

-                               "Buccal Cell Normal",   # 12

-                               "EBV Immortalized Normal", # 13

-                               "Bone Marrow Normal", # 14

-                               "Fibroblasts from Bone Marrow Normal", # 15

-                               "Mononuclear Cells from Bone Marrow Normal", # 16

-                               "Lymphatic Tissue Normal (including centroblasts)", # 17

-                               "Control Analyte", # 20

-                               "Recurrent Blood Derived Cancer - Peripheral Blood", # 40

-                               "Blood Derived Cancer- Bone Marrow, Post-treatment", # 41

-                               "Blood Derived Cancer- Peripheral Blood, Post-treatment", # 42

-                               "Cell line from patient tumor", # 50

-                               "Xenograft from patient not grown as intermediate on plastic tissue culture dish", # 60

-                               "Xenograft grown in mice from established cell lines", #61

-                               "Granulocytes after a Ficoll separation") # 99

-        aux <- DataFrame(tissue.code = tissue.code,tissue.definition)

+

+        tissue.code <- c(

+            '01','02','03','04','05','06','07','08','09','10','11',

+            '12','13','14','15','16','17','20','40','41','42','50','60','61','99'

+        )

+

+        tissue.definition <- c(

+            "Primary Tumor", # 01

+            "Recurrent Tumor", # 02

+            "Primary Blood Derived Cancer - Peripheral Blood", # 03

+            "Recurrent Blood Derived Cancer - Bone Marrow", # 04

+            "Additional - New Primary", # 05

+            "Metastatic", # 06

+            "Additional Metastatic", # 07

+            "Tissue disease-specific post-adjuvant therapy", # 08

+            "Primary Blood Derived Cancer - Bone Marrow", # 09

+            "Blood Derived Normal", # 10

+            "Solid Tissue Normal",  # 11

+            "Buccal Cell Normal",   # 12

+            "EBV Immortalized Normal", # 13

+            "Bone Marrow Normal", # 14

+            "Fibroblasts from Bone Marrow Normal", # 15

+            "Mononuclear Cells from Bone Marrow Normal", # 16

+            "Lymphatic Tissue Normal (including centroblasts)", # 17

+            "Control Analyte", # 20

+            "Recurrent Blood Derived Cancer - Peripheral Blood", # 40

+            "Blood Derived Cancer- Bone Marrow, Post-treatment", # 41

+            "Blood Derived Cancer- Peripheral Blood, Post-treatment", # 42

+            "Cell line from patient tumor", # 50

+            "Xenograft from patient not grown as intermediate on plastic tissue culture dish", # 60

+            "Xenograft grown in mice from established cell lines", #61

+            "Granulocytes after a Ficoll separation"

+        ) # 99

+        aux <- DataFrame(tissue.code = tissue.code, tissue.definition)

     }

     return(aux)

@@ -945,8 +962,8 @@ TCGAquery_recount2<-function(project, tissue=c()){

     tissue<-unlist(lapply(strsplit(tissue, " "), function(x) paste(x, collapse = "_")))

     Res<-list()

-    if(tolower(project)=="gtex"){

-        for(t_i in tissue){

+    if (tolower(project) == "gtex"){

+        for (t_i in tissue){

             if(t_i%in%tissuesGTEx){

                 con<-"http://duffel.rail.bio/recount/v2/SRP012682/rse_gene_"

                 con<-paste0(con,t_i,".Rdata")

@@ -1010,12 +1027,14 @@ GDCquery_ATAC_seq <- function(

     results$data_type <- "ATAC-seq"

     results$data_category <- "ATAC-seq"

     results$project <- "ATAC-seq"

-    ret <- data.frame(results=I(list(results)),

-                      tumor = I(list(tumor)),

-                      project = I(list("ATAC-seq")),

-                      data.type = I(list("ATAC-seq")),

-                      data.category = I(list("ATAC-seq")),

-                      legacy = I(list(FALSE)))

+    ret <- data.frame(

+        results=I(list(results)),

+        tumor = I(list(tumor)),

+        project = I(list("ATAC-seq")),

+        data.type = I(list("ATAC-seq")),

+        data.category = I(list("ATAC-seq")),

+        legacy = I(list(FALSE))

+    )

     return(ret)

 }

@@ -884,19 +884,23 @@ unlistlabels <- function(lab) {

 #' GDCdownload(query)

 #' mut <- GDCprepare(query)

 #' TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:10], rm.empty.columns = TRUE)

-#' TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:10],

-#'                  filename = "onco.pdf",

-#'                  color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"))

+#' TCGAvisualize_oncoprint(

+#'   mut = mut, genes = mut$Hugo_Symbol[1:10],

+#'   filename = "onco.pdf",

+#'   color = c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown")

+#' )

 #' clin <- GDCquery_clinic("TCGA-ACC","clinical")

 #' clin <- clin[,c("bcr_patient_barcode","disease","gender","tumor_stage","race","vital_status")]

-#' TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:20],

-#'                 filename = "onco.pdf",

-#'                 annotation = clin,

-#'                 color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"),

-#'                 rows.font.size=10,

-#'                 heatmap.legend.side = "right",

-#'                 dist.col = 0,

-#'                 label.font.size = 10)

+#' TCGAvisualize_oncoprint(

+#'    mut = mut, genes = mut$Hugo_Symbol[1:20],

+#'    filename = "onco.pdf",

+#'    annotation = clin,

+#'    color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"),

+#'    rows.font.size=10,

+#'    heatmap.legend.side = "right",

+#'    dist.col = 0,

+#'    label.font.size = 10

+#' )

 #' }

 #' @export

 #' @return A oncoprint plot

@@ -1431,6 +1435,7 @@ TCGAvisualize_oncoprint <- function(

 #'     title = "Title example",

 #'     xlab = expression(paste(Log[2], "FoldChange"))

 #' )

+#' \dontrun{

 #' beta_diff <- runif(200, -1, 1)

 #' fdr <- runif(200, 0.01, 1)

 #' TCGAVisualize_volcano(

@@ -1441,7 +1446,6 @@ TCGAvisualize_oncoprint <- function(

 #'     title = "Title example",

 #'     xlab = expression(paste("DNA Methylation difference (", beta, "-values)"))

 #' )

-#' \dontrun{

 #' TCGAVisualize_volcano(

 #'   x,

 #'   y,

@@ -34,11 +34,13 @@ Uses GDC API or GDC transfer tool to download gdc data

   The data from query will be save in a folder: project/data.category

 }

 \examples{

-query <- GDCquery(project = "TCGA-ACC",

-                 data.category =  "Copy number variation",

-                 legacy = TRUE,

-                 file.type = "hg19.seg",

-                 barcode = c("TCGA-OR-A5LR-01A-11D-A29H-01", "TCGA-OR-A5LJ-10A-01D-A29K-01"))

+query <- GDCquery(

+  project = "TCGA-ACC",

+  data.category =  "Copy number variation",

+  legacy = TRUE,

+  file.type = "hg19.seg",

+  barcode = c("TCGA-OR-A5LR-01A-11D-A29H-01", "TCGA-OR-A5LJ-10A-01D-A29K-01")

+ )

 # data will be saved in  GDCdata/TCGA-ACC/legacy/Copy_number_variation/Copy_number_segmentation

 GDCdownload(query, method = "api")

 \dontrun{

@@ -34,6 +34,7 @@ clinical <- GDCprepare_clinic(query,"patient")

 clinical.drug <- GDCprepare_clinic(query,"drug")

 clinical.radiation <- GDCprepare_clinic(query,"radiation")

 clinical.admin <- GDCprepare_clinic(query,"admin")

+\dontrun{

 query <- GDCquery(

    project = "TCGA-COAD",

    data.category = "Biospecimen",

@@ -47,3 +48,4 @@ clinical.drug <- GDCprepare_clinic(query,"sample")

 clinical.radiation <- GDCprepare_clinic(query,"portion")

 clinical.admin <- GDCprepare_clinic(query,"slide")

 }

+}

@@ -103,6 +103,7 @@ TCGAVisualize_volcano(

     title = "Title example",

     xlab = expression(paste(Log[2], "FoldChange"))

 )

+\dontrun{

 beta_diff <- runif(200, -1, 1)

 fdr <- runif(200, 0.01, 1)

 TCGAVisualize_volcano(

@@ -113,7 +114,6 @@ TCGAVisualize_volcano(

     title = "Title example",

     xlab = expression(paste("DNA Methylation difference (", beta, "-values)"))

 )

-\dontrun{

 TCGAVisualize_volcano(

   x,

   y,

@@ -100,18 +100,22 @@ query <- GDCquery(

 GDCdownload(query)

 mut <- GDCprepare(query)

 TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:10], rm.empty.columns = TRUE)

-TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:10],

-                 filename = "onco.pdf",

-                 color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"))

+TCGAvisualize_oncoprint(

+  mut = mut, genes = mut$Hugo_Symbol[1:10],

+  filename = "onco.pdf",

+  color = c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown")

+)

 clin <- GDCquery_clinic("TCGA-ACC","clinical")

 clin <- clin[,c("bcr_patient_barcode","disease","gender","tumor_stage","race","vital_status")]

-TCGAvisualize_oncoprint(mut = mut, genes = mut$Hugo_Symbol[1:20],

-                filename = "onco.pdf",

-                annotation = clin,

-                color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"),

-                rows.font.size=10,

-                heatmap.legend.side = "right",

-                dist.col = 0,

-                label.font.size = 10)

+TCGAvisualize_oncoprint(

+   mut = mut, genes = mut$Hugo_Symbol[1:20],

+   filename = "onco.pdf",

+   annotation = clin,

+   color=c("background"="#CCCCCC","DEL"="purple","INS"="yellow","SNP"="brown"),

+   rows.font.size=10,

+   heatmap.legend.side = "right",

+   dist.col = 0,

+   label.font.size = 10

+)

 }

 }