diff --git a/CHANGELOG.md b/CHANGELOG.md
index c81d1d99..cc58e59f 100755
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -62,6 +62,8 @@ Code contributions to the new version:
 - Added several improvements in lablog_viralrecon (created log files, modified check_references function behaviour, enabled config files regeneration) [#306](https://github.com/BU-ISCIII/buisciii-tools/pull/306)
 - Fixed bug when lablog_viralrecon tries to download references that don't belong to any family. [#310](https://github.com/BU-ISCIII/buisciii-tools/pull/310)
 - Added mvmoneo to SFTP users. [#317](https://github.com/BU-ISCIII/buisciii-tools/pull/317)
+- Added scripts for time series RNAseq and updated differential expression code for differentially expressed transcripts [#316](https://github.com/BU-ISCIII/buisciii-tools/pull/316).
+- Added bbaladron to SFTP users [#316](https://github.com/BU-ISCIII/buisciii-tools/pull/316).
 
 ### Modules
 
diff --git a/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/differential_expression.R b/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/differential_expression.R
index 160d69dc..f1a7f397 100644
--- a/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/differential_expression.R
+++ b/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/differential_expression.R
@@ -363,9 +363,17 @@ differential_plots <- function(res_de, de_results, ntd_subset, dds_subset){
   rownames(df) <- colnames(ntd_subset)
   to_plot <- assay_ntd[select,]
   to_plot_geneid <- as.data.frame(rownames(to_plot))
-  colnames(to_plot_geneid) <- "GeneID"
-  to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
-  rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  if ( opt$differential_expression == "DEG") {
+    colnames(to_plot_geneid) <- "GeneID"
+    to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
+    rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  }
+
+  if ( opt$differential_expression == "DET") { 
+    colnames(to_plot_geneid) <- "TranscriptID"
+    rownames(to_plot) <- to_plot_geneid$TranscriptID
+  }
+
   pdf(file="Differential_expression/DESeq2/heatmapCount_top20_differentially_expressed.pdf")
   pheatmap(to_plot, cluster_rows=TRUE, show_rownames=TRUE,
            cluster_cols=TRUE, annotation_col=df, main="Top 20 significant genes")
@@ -444,9 +452,16 @@ quality_plots <- function(data_subset){
   
   to_plot <- assay(data_subset$subset_ntd)[select,]
   to_plot_geneid <- as.data.frame(rownames(to_plot))
-  colnames(to_plot_geneid) <- "GeneID"
-  to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
-  rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  if ( opt$differential_expression == "DEG") {
+    colnames(to_plot_geneid) <- "GeneID"
+    to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
+    rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  }
+
+  if ( opt$differential_expression == "DET") { 
+    colnames(to_plot_geneid) <- "TranscriptID"
+    rownames(to_plot) <- to_plot_geneid$TranscriptID
+  }
   
   pdf(file="Quality_plots/DESeq2/heatmapCount_top20_highest_expression.pdf")
   pheatmap(to_plot, cluster_rows=FALSE, show_rownames=TRUE,
@@ -550,13 +565,14 @@ cat(blue("########################\nStarting with loading data\n################
 
 ####LOAD TRANSCRIPT RELATION DATA FILE #########################
 if (opt$differential_expression != "DEM") {
-  tx2gene <- read.table(file.path(opt$rnaseq_dir, "star_salmon", "salmon_tx2gene.tsv"), header = F)
+  tx2gene <- read.table(file.path(opt$rnaseq_dir, "star_salmon", "tx2gene.tsv"), header = F)
   colnames(tx2gene) <- c("TXNAME", "GENEID", "gene_name")
   if ( opt$differential_expression == "DEG") {
     gene_genename <- tx2gene[,c(2:3)]
     gene_genename <- gene_genename %>% distinct()
   }
 }
+
 ####LOAD CLINICAL DATA FILE #########################
 samples_clin_data <- load_sample_data(clinical_data = opt$sample_data, group = opt$group_col)
 
diff --git a/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/time_series_differential_expression.R b/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/time_series_differential_expression.R
new file mode 100644
index 00000000..ce5b964e
--- /dev/null
+++ b/bu_isciii/templates/rnaseq/ANALYSIS/DATE_ANALYSIS01_RNASEQ/02-differential_expression/time_series_differential_expression.R
@@ -0,0 +1,413 @@
+#!/usr/bin/env Rscript
+
+################################################
+################################################
+## LOAD LIBRARIES                             ##
+################################################
+################################################
+
+####DESeq2 libraries
+library(DESeq2)
+library(tximport)
+library(readr)
+
+####fishpond libraries
+library(fishpond)
+library(tximeta)
+library(SummarizedExperiment)
+####Other libraries
+library(optparse)
+#library(xlsx)
+#options(java.parameters = "-Xmx4G")
+library(dplyr)
+library(pheatmap)
+library(RColorBrewer)
+library(ggplot2)
+library(vsn)
+library(crayon)
+library(tidytable)
+library(data.table)
+
+
+################################################
+################################################
+## PARSE COMMAND-LINE PARAMETERS              ##
+################################################
+################################################
+cat(cyan$bgRed$bold("########################\nStarting diferential expression pipeline\n###############################\n"))
+
+option_list <- list(
+  make_option(c("-r", "--rnaseq_dir"    ), type="character" , default='../../01-rnaseq'      , metavar="path"   , help="Path to rna-seq results"                                                      ),
+  make_option(c("-c", "--clinical_data" ), type="character" , default='../clinical_data.txt' , metavar="path"   , help="Path to clinical data file"                                                   ),
+  make_option(c("-g", "--group_col"     ), type="character" , default='Group'                , metavar="string" , help="Colname with the sample classes in sample_data of the experiment for the DE." ),
+  make_option(c("-n", "--norm_counts"   ), type="logical"   , default=FALSE                  , metavar="boolean", help="Create table with normalized counts"                                          ),
+  make_option(c("-q", "--quality_plots" ), type="logical"   , default=TRUE                   , metavar="boolean", help="Create quality plots or not."                                                 ),
+  make_option(c("-t", "--time_order"    ), type="character" , default=NULL                   , metavar="string" , help="Order to plot the dates as list, eg: 15D,45D,3M."                                                     )
+)
+
+opt_parser <- OptionParser(option_list=option_list)
+opt        <- parse_args(opt_parser)
+
+cat(blue$bold("########################\nRunning analysis with the following params:\n###############################\n"))
+cat(blue("-Path to RNAseq input folder: ")) + cat(blue(opt$rnaseq_dir))+cat(blue("\n"))
+cat(blue("-Path to samples clinical data: ")) + cat(blue(opt$clinical_data))+cat(blue("\n"))
+cat(blue("-Column with the group info: ")) + cat(blue(opt$group_col))+cat(blue("\n"))
+
+if (is.null(opt$time_order)) {
+    print_help(opt_parser)
+    stop("You need to specify the order for the dates.", call.=FALSE)
+} else {
+  time_order <- unlist(strsplit(opt$time_order, ","))
+}
+
+if (opt$norm_counts) {
+  cat(blue("-Saving normalized counts to file\n"))
+} else{
+  cat(blue("-Not saving normalized counts to file\n"))
+}
+if (opt$quality_plots) {
+  cat(blue("-Creating quality plots\n"))
+} else{
+  cat(blue("-Skipping quality plots\n"))
+}
+
+cat(blue("Time order: ")) + cat(blue(time_order)) +cat(blue("\n"))
+
+################################################
+################################################
+## FUNCTIONS                                  ##
+################################################
+################################################
+
+################################################
+## LOAD DATA                                  ##
+################################################
+
+####LOAD CLINICAL DATA FILE#########################
+load_sample_data <- function(clinical_data, group) {
+  samples <- read.table(clinical_data, header = T)
+  compare_col <- which(colnames(samples) %in% group)
+  time_col <- which(colnames(samples) %in% c("time"))
+  samples <- samples[,c(1,compare_col, time_col)]
+  colnames(samples) <- c("names","condition", "time")
+  rownames(samples) <- samples$names
+  return(samples)
+}
+
+################################################
+## DESEQ2                                     ##
+################################################
+
+####DIFFERENTIAL EXPRESSION#########################
+
+deseq2_analysis <- function(txi_data, samples){
+  ddsTxi <- DESeqDataSetFromTximport(txi_data,
+                                     colData = samples,
+                                     design = ~ condition + time + condition:time)
+  dds <- ddsTxi[ rowSums(counts(ddsTxi)) >= 1, ]
+  dds <- DESeq(dds, test = "LRT", reduced = ~ condition + time)
+  res <- results(dds)
+  return(list(dds_matrix = dds, results =res))
+}
+
+####NORMALIZATION#########################
+
+normalized_counts <- function(dds_table){
+  ntd <- normTransform(dds_table)
+  rld <- rlog(dds_table, blind=FALSE)
+  vsd <- varianceStabilizingTransformation(dds_table, blind=FALSE)
+  return(list(dds_norm=dds_table, norm = ntd, rlogtrans =rld, varstab=vsd))
+}
+
+####DE PLOTS#########################
+
+differential_plots <- function(res_de, de_results, ntd_subset, dds_subset){
+  #MA-plotThe  MA-plot  shows  the  log2  fold  changes  from  the  treatment  over  the  meanof  normalized  counts.
+  #The  average  of  counts  normalized  by  size  factor.
+  pdf(file="Differential_expression/DESeq2/maPlot_all.pdf")
+  plotMA( res_de, ylim = c(-1, 1) )
+  dev.off()
+  
+  #############DISPERSION PLOTS################
+  pdf(file="Differential_expression/DESeq2/pvalues.pdf")
+  hist( res_de$pvalue, breaks=20, col="grey", main = "pvalues test for differential expression")
+  dev.off()
+  
+  ##############PHEATMAP##############
+  assay_ntd <- assay(ntd_subset)
+  ordered_table <- de_results[order(de_results$pvalue, -abs(de_results$log2FoldChange)),]
+  ordered_table$identifier <- rownames(ordered_table)
+  col_num <- which(colnames(ordered_table) == "identifier")
+  top_sig_genes <- ordered_table[1:20,col_num]
+  select <- which(rownames(assay_ntd) %in% top_sig_genes)
+  df <- as.data.frame(colData(dds_subset)[,c("condition")])
+  colnames(df) <- c("condition")
+  rownames(df) <- colnames(ntd_subset)
+  to_plot <- assay_ntd[select,]
+  to_plot_geneid <- as.data.frame(rownames(to_plot))
+  colnames(to_plot_geneid) <- "GeneID"
+  to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
+  rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  pdf(file="Differential_expression/DESeq2/heatmapCount_top20_differentially_expressed.pdf")
+  pheatmap(to_plot, cluster_rows=TRUE, show_rownames=TRUE,
+           cluster_cols=TRUE, annotation_col=df, main="Top 20 significant genes")
+  dev.off()
+}
+
+
+####QUALITY PLOTS#########################
+
+quality_plots <- function(norm_data){
+  ###########SAMPLE DISTANCE##############
+  sampleDists <- dist( t( assay(norm_data$rlogtrans) ) )
+  
+  sampleDistMatrix <- as.matrix( sampleDists )
+  colours = colorRampPalette(rev(brewer.pal(9, "Blues"))) (255)
+  pdf(file="Quality_plots/DESeq2/heatmap_sample_to_sample.pdf")
+  pheatmap(sampleDistMatrix,
+           clustering_distance_rows=sampleDists,
+           clustering_distance_cols=sampleDists,
+           col=colours)
+  dev.off()
+  
+  #############PCA PLOTS################
+  pcaData <- plotPCA(norm_data$rlogtrans, intgroup=c("condition"), returnData=TRUE)
+  pcaData_2 <- plotPCA(norm_data$varstab, intgroup=c("condition"), returnData=TRUE)
+  percentVar <- round(100 * attr(pcaData, "percentVar"))
+  pdf(file="Quality_plots/DESeq2/plotPCA.pdf")
+  pca_plot_rld <- ggplot(pcaData, aes(PC1, PC2, color=condition)) +
+    geom_point(size=3) +
+    xlab(paste0("PC1: ",percentVar[1],"% variance")) +
+    ylab(paste0("PC2: ",percentVar[2],"% variance")) +
+    geom_text(aes(label = name), color = "black", size=2, position = position_nudge(y = 0.8)) +
+    labs(title="PCA: rlog") +
+    coord_fixed()
+  pca_plot_vsd <- ggplot(pcaData_2, aes(PC1, PC2, color=condition)) +
+    geom_point(size=3) +
+    xlab(paste0("PC1: ",percentVar[1],"% variance")) +
+    ylab(paste0("PC2: ",percentVar[2],"% variance")) +
+    geom_text(aes(label = name), color = "black", size=2, position = position_nudge(y = 0.8)) +
+    labs(title="PCA: vsd") +
+    coord_fixed()
+  print(pca_plot_rld)
+  print(pca_plot_vsd)
+  dev.off()
+  
+  #############BOX PLOTS################
+  pdf(file="Quality_plots/DESeq2/boxplot.pdf")
+  boxplot(assay(norm_data$norm), col="blue", las =2)
+  title(main="Boxplot: normalized counts")
+  boxplot(log10(assays(norm_data$dds_norm)[["cooks"]]), range=0, las=2)
+  title(main="Boxplot see outliers: cooks distance")
+  dev.off()
+  
+  #############DISPERSION PLOTS################
+  pdf(file="Quality_plots/DESeq2/plotDispersions.pdf")
+  plotDispEsts(norm_data$dds_norm)
+  dev.off()
+  
+  #############DESVIATION PLOT################
+  pdf(file="Quality_plots/DESeq2/plotSD.pdf")
+  meanSdPlot(assay(norm_data$norm))
+  dev.off()
+  
+  ##############HCLUST###################
+  assay_ntd <- assay(norm_data$norm)
+  pdf(file="Quality_plots/DESeq2/cluster_dendrogram.pdf")
+  plot(hclust(dist(t(assay_ntd)),method="average"))
+  dev.off()
+  
+  ##############PHEATMAP##############
+  select <- order(rowMeans(counts(norm_data$dds_norm,normalized=TRUE)),
+                  decreasing=TRUE)[1:20]
+  df <- as.data.frame(colData(norm_data$dds_norm)[,c("condition")])
+  colnames(df) <- c("Condition")
+  rownames(df) <- colnames(norm_data$norm)
+  
+  to_plot <- assay(norm_data$norm)[select,]
+  to_plot_geneid <- as.data.frame(rownames(to_plot))
+  colnames(to_plot_geneid) <- "GeneID"
+  to_plot_geneid_merged <- merge(x = to_plot_geneid, y = gene_genename, by.x="GeneID", by.y = "GENEID", all.x = TRUE, all.y = FALSE)
+  rownames(to_plot) <- to_plot_geneid_merged$gene_name
+  
+  pdf(file="Quality_plots/DESeq2/heatmapCount_top20_highest_expression.pdf")
+  pheatmap(to_plot, cluster_rows=FALSE, show_rownames=TRUE,
+           cluster_cols=TRUE, annotation_col=df, main="Normalized counts top 20 more expressed genes")
+  dev.off()
+  
+  ######FULL PHEATMAP#################
+  pdf(file="Quality_plots/DESeq2/heatmapCount_all_genes.pdf")
+  pheatmap(assay(norm_data$norm), cluster_rows=FALSE, show_rownames=FALSE,
+           cluster_cols=TRUE,main="Normalized counts", annotation_col=df)
+  dev.off()
+}
+
+####TIME SERIES PLOTS#########################
+time_series_plots <- function(gene, res, dds) {
+  plot_name <- paste(gene, "expression.pdf", sep = "_")
+  file_path <- paste("Time_series_plots", plot_name, sep = "/")
+  index = which(rownames(res) == gene, arr.ind = TRUE)
+  gene_name <- DE_results_merged[index,2]
+  fiss <- plotCounts(dds, index, 
+                    intgroup = c("time","condition"), returnData = TRUE)
+  fiss$time <- factor(fiss$time, levels = time_order)
+  p <- ggplot(fiss, aes(x = time, y = count, color = condition, group = condition)) + 
+    geom_point() + 
+    stat_summary(fun = mean, geom = "line") +
+    scale_y_log10() +
+    labs(title = paste("Expression evolution of gene: ", gene_name, sep = ""))
+  pdf(file=file_path)
+  print(p)
+  dev.off()
+}
+
+####WALD TEST FOR TIME SERIES#########################
+
+wald_test <- function(dds, condition){
+  condition_test <- results(dds, name=condition, test="Wald")
+  print(condition_test[which.min(condition_test$padj),])
+}
+
+####BETAS PLOT FOR TIME SERIES#########################
+
+betas_plot <- function(res, dds) {
+  betas <- coef(dds)
+  colnames(betas)
+
+  topGenes <- head(order(res$padj),20)
+  mat <- betas[topGenes, -c(1,2)]
+  thr <- 3
+  mat[mat < -thr] <- -thr
+  mat[mat > thr] <- thr
+  pdf(file="Time_series_plots/betas_pheatmap.pdf")
+  pheatmap(mat, breaks=seq(from=-thr, to=thr, length=101),
+          cluster_col=TRUE, main = "log2FC of top20 significant genes")
+  dev.off()
+}
+
+################################################
+## WARNINGS                                   ##
+################################################
+
+test_data <- function(samples_data, txi_data){
+  if (all(rownames(samples_data) %in% colnames(txi_data$counts)) == FALSE) {
+    print("Warning: Check sample names")
+  }
+  if (all(rownames(samples_data) == colnames(txi_data$counts)) == FALSE) {
+    print("Warning: Check sample names")
+  }
+}
+
+
+##############################################################################################################################################
+##############################################################################################################################################
+##################################################### MAIN                                  ##################################################
+##############################################################################################################################################
+##############################################################################################################################################
+
+
+################################################
+################################################
+## LOAD DATA                                  ##
+################################################
+################################################
+
+cat(blue("########################\nStarting with loading data\n###############################\n"))
+
+####LOAD TRANSCRIPT RELATION DATA FILE #########################
+
+tx2gene <- read.table(file.path(opt$rnaseq_dir, "star_salmon", "tx2gene.tsv"), header = F)
+colnames(tx2gene) <- c("TXNAME", "GENEID", "gene_name")
+gene_genename <- tx2gene[,c(2:3)]
+gene_genename <- gene_genename %>% distinct()
+
+####LOAD CLINICAL DATA FILE #########################
+samples_clin_data <- load_sample_data(clinical_data = opt$clinical_data, group = opt$group_col)
+
+####LOAD ESPRESSION DATA #########################
+files <- file.path(opt$rnaseq_dir,"star_salmon", samples_clin_data$names, "quant.sf")
+names(files) <- samples_clin_data$names
+coldata <- data.frame(files, samples_clin_data, stringsAsFactors=FALSE)
+if (!all(file.exists(coldata$files))) {
+  cat(red("############WARNING############\nNo todos los ficheros existen\n###############################\n"))
+}
+
+
+################################################
+################################################
+## DIFFERENTIAL EXPRESSION                    ##
+################################################
+################################################
+
+
+################################################
+################################################
+## DIFFERENTIAL EXPRESSION DESEQ2             ##
+################################################
+################################################
+
+cat(blue("########################\nStarting with DESeq2\n###############################\n"))
+txi <- tximport(files, type="salmon", tx2gene=tx2gene)
+test_data(samples_data = samples_clin_data, txi_data = txi)
+
+cat(blue("########################\nStarting with differential expression\n###############################\n"))
+deseq2_results <- deseq2_analysis(txi_data = txi, samples = samples_clin_data)
+mcols(deseq2_results$results, use.names = T)
+DE_results <- as.data.frame(deseq2_results$results)
+
+DE_results$GeneID <- row.names(DE_results)
+DE_results_merged <- merge(x = gene_genename, y = DE_results, by.x = "GENEID", by.y= "GeneID", all.y = T, all.x=F)
+
+DE_results_merged_sig <- subset(x = DE_results_merged, padj <= 0.05 & (log2FoldChange <= -2 | log2FoldChange >= 2))
+
+dir.create("Differential_expression",showWarnings = FALSE)
+dir.create("Differential_expression/DESeq2",showWarnings = FALSE)
+write.table(x = DE_results_merged, file = "Differential_expression/DESeq2/Differential_expression.csv", sep = ",", quote = F, col.names = T, row.names = F)
+#write.xlsx(x = DE_results_merged, file = "Differential_expression/DESeq2/Differential_expression.xlsx", sheetName = "Diff_exp", col.names = TRUE, row.names = FALSE, append = FALSE, showNA = TRUE, password = NULL)
+
+
+cat(blue("########################\nStarting with normalization\n###############################\n"))
+norm_count <- normalized_counts(dds_table = deseq2_results$dds_matrix)
+
+if (opt$norm_counts) {
+  ntd_gene <- as.data.frame(assay(norm_count$norm))
+  ntd_gene$GeneID <- rownames(ntd_gene)
+  norm_name_table <- merge(x = gene_genename, y = ntd_gene, by.x = "GENEID", by.y= "GeneID", all.y = T, all.x=F)
+  write.table(x = norm_name_table, file = "normalized_expression.csv", quote = F, sep = ",", row.names = F, col.names = T)
+  #write.xlsx(x = norm_name_table, file = "normalized_expression.xlsx", sheetName = "Norm_exp", col.names = TRUE, row.names = FALSE, append = FALSE, showNA = TRUE, password = NULL)
+}
+
+cat(blue("########################\nStarting with data subsettion\n###############################\n"))
+
+differential_plots(res_de = deseq2_results$results, de_results = DE_results, ntd_subset = norm_count$norm, dds_subset = norm_count$dds_norm)
+
+if (opt$quality_plots) {
+  cat(blue("########################\nStarting with Quality plots\n###############################\n"))
+  dir.create("Quality_plots",showWarnings = FALSE)
+  dir.create("Quality_plots/DESeq2",showWarnings = FALSE)
+  quality_plots(norm_data = norm_count)
+}
+
+cat(blue("########################\nStarting with time series plots\n###############################\n"))
+
+top4 <- rownames(head(deseq2_results$dds_matrix[order(deseq2_results$results$padj),], 4))
+
+dir.create("Time_series_plots",showWarnings = FALSE)
+
+for (gene in top4) {
+  time_series_plots(gene, res = deseq2_results$results, dds = deseq2_results$dds_matrix)
+}
+
+all_conditions <- resultsNames(deseq2_results$dds_matrix)
+for (condition in all_conditions) {
+  wald_test(dds = deseq2_results$dds_matrix, condition)
+}
+
+betas_plot(res = deseq2_results$results, dds = deseq2_results$dds_matrix)
+
+save.image()
+cat(blue("########################\nNumber of genes with padj < 0.05 and log2FC >= |2|:\n"))
+cat(blue(nrow(DE_results_merged_sig)))
+cat(blue("\n###############################\n"))
+
+cat(green("########################\nPipeline completed succesfully\n###############################\n"))
diff --git a/bu_isciii/templates/sftp_user.json b/bu_isciii/templates/sftp_user.json
index 04773c8f..f8ee42f6 100755
--- a/bu_isciii/templates/sftp_user.json
+++ b/bu_isciii/templates/sftp_user.json
@@ -51,5 +51,6 @@
     "ycampos": ["LabUfiecMithocondrial"],
     "anadonoso": ["Labenterovirus"],
     "mvmoneo": ["SpainUDP"],
+    "bbaladron": ["SpainUDP"],
     "bioinfoadm": ["test"]
 }