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update first of march
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@fdabbagh
fdabbagh committed Feb 28, 2018
1 parent 54c5091 commit 3285396
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Showing 4 changed files with 140 additions and 37 deletions.
112 changes: 87 additions & 25 deletions app/server.r
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Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@

# Done TODOs -------------------------------------------------------------------

#1 Only show download tabs and button after the data or plot has been generated so the user won't get an error (DONE!)
Expand All @@ -9,7 +8,7 @@
#6 maybe start splitting the server into chuncks inside the server folder and source the chuncks (almost DONE!)
#7 Check for shiny as a R package (it's doable, need to understand how packages are organized first)
#8 Having some global variables so I won't need to fetch from DeepBlue many times (DONE!)
#9 Change all the plots to be in Plotly instead of ggplot
#9 Change all the plots to be in Plotly instead of ggplot (Done!!)
#10 Advanced option for plotting (choosing which PCAs to plot and filtering option) (DONE!)
#11 metadata to be interactive upon clicking on list of experiments (DONE!)
#12 RUV for batch effect
Expand All @@ -18,22 +17,25 @@
#15 genomic ranges R package
#16 Have a download button for the adjusted matrix (Done !!)
#17 Need to have the back button only in the calculate matrix page and the next is added once the calculation is done (Done!!)
#18 Fix the corrplot download
#18 Fix the corrplot download (done!!)
#19 Score matrices and tables other than the first, lines don't need to be selected (Done!)
#20 Filter coverage files from the beginning with a check box (Done!)
#21 Make batch effect analysis matrices as a list
#22 Notification to choose a chromosome (Done!)


# TODOs -------------------------------------------------------------------
#9 Change all the plots to be in Plotly instead of ggplot
#7 Check for shiny as a R package
#12 RUV for batch effect (from Markus' scripts to understand how it works)
#13 select expression, for gene expression data
#15 genomic ranges R package
#18 Fix the corrplot download
#It's working, but for some reason the PDFs are taking long time to show
#The plot maybe a bit too big, even thought the pdf file has a small size
#21 Make batch effect analysis matrices as a list
#22 Notification to choose a chromosome
#22 I can't retrieve chromosomes anymore?


#Problems need to be solved
#1 Can't find chromosomes for each genome anymore (solved!!)
#2 I can't get the rna-seq for most of the projects
#3

#New UI with shiny dashboard
library(foreach)
Expand All @@ -58,22 +60,24 @@ library(shinydashboard)

#importing functions
for(f in list.files("../functions/")){
source(paste0('../functions/',f), local = TRUE)
source(file.path('../functions/',f), local = TRUE)
}

# Server function ---------------------------------------------------------
function(input, output, session) {

#identifying some variables and reactive variables
#Need to review some of these variables and get rid of some
inserted_inputs <- c()
echo <- c()
to <- c()
user_key <- c()
genomes <- c()
# genomes <- c()
listed_experiments <- reactiveVal(FALSE)
calculated_matrix <- reactiveVal(FALSE)
calculated_adjusted_matrix <- reactiveVal(FALSE)
logged_in <- reactiveVal("")
batch_adjusted_matrices <- reactiveVal(list())

observe(hideTab(inputId = "plot_box", target = "Download Plot"))
observe(hideTab(inputId = "corr_plot_box", target = "Downlad Plot"))
Expand All @@ -86,7 +90,6 @@ function(input, output, session) {
# # listing genomes ---------------------------------------------------------
source("../server/listing_genomes.r", local = TRUE)


# Listing Experiments -----------------------------------------------------
source("../server/listing_experiments.r", local = TRUE)

Expand Down Expand Up @@ -159,13 +162,28 @@ function(input, output, session) {

#update the keys for batch effects once we calculate the score matrix
observeEvent(filtered_score_matrix(),{
updateSelectInput(session, inputId = "batch",
updateSelectInput(session, inputId = "batch_combat",
choices = colnames(attr(filtered_score_matrix(), "meta")))

updateSelectInput(session, inputId = "adj_var",
updateSelectInput(session, inputId = "adj_var_combat",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "interest_var_combat",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "interest_var",
updateSelectInput(session, inputId = "adj_var_sva",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "interest_var_sva",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "batch_supervised_sva",
choices = colnames(attr(filtered_score_matrix(), "meta")))

updateSelectInput(session, inputId = "adj_var_supervised_sva",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "interest_var_supervised_sva",
choices = c("",colnames(attr(filtered_score_matrix(), "meta"))))

updateSelectInput(session, inputId = "color_by",
Expand All @@ -177,22 +195,66 @@ function(input, output, session) {
selected = "biosource_name")
})

# ComBat matrix -----------------------------------------------------
# Batch adjusted matrix -----------------------------------------------------

#calculating the new matrix after batch effect
batch_adjusted_matrix <- eventReactive(input$calculate_batch_matrix,{

batch_adjusted_matrix <- combat_batch_effect(filtered_score_matrix = filtered_score_matrix(),
batch = input$batch,
adjustment_var = input$adj_var,
interest_var = input$interest_var)

isolate({
if(input$batch_effect_choice == "combat"){
temp_matrices <- batch_adjusted_matrices()
temp_matrices[[paste(input$batch_effect_choice, input$batch_combat,
input$adj_var_combat, input$interest_var_combat, collapse = "-")]]<-
combat_batch_effect(filtered_score_matrix = filtered_score_matrix(),
batch = input$batch_combat,
adjustment_var = input$adj_var_combat,
interest_var = input$interest_var_combat)

batch_adjusted_matrices(temp_matrices)
# batch_adjusted_matrices[[paste(input$batch_effect_choice, input$batch_combat,
# input$adj_var_combat,
# input$interest_var_combat, collapse = "-")]] <-
#
# combat_batch_effect(filtered_score_matrix = filtered_score_matrix(),
# batch = input$batch_combat,
# adjustment_var = input$adj_var_combat,
# interest_var = input$interest_var_combat)

}else if(input$batch_effect_choice == "sva"){
temp_matrices <- batch_adjusted_matrices()

temp_matrices[[paste(input$batch_effect_choice, input$batch_sva,
input$adj_var_sva, input$interest_var_sva, collapse = "-")]]<-

sva_batch_effect(filtered_score_matrix = filtered_score_matrix(),
adjustment_var = input$adj_var_sva,
interest_var = input$interest_var_sva)

batch_adjusted_matrices(temp_matrices)

# batch_adjusted_matrices[[paste(input$batch_effect_choice, input$batch_sva,
# input$adj_var_sva,
# input$interest_var_sva, collapse = "-")]] <-
#
# sva_batch_effect(filtered_score_matrix = filtered_score_matrix(),
# adjustment_var = input$adj_var_sva,
# interest_var = input$interest_var_sva)
}
updateSelectInput(session, "corrected_matrices", choices = names(temp_matrices))
return(batch_adjusted_matrices())
})

})
output$batch_matrix_summary <- DT::renderDataTable({
matrix_summary_table(matrix_summary = summary(batch_adjusted_matrix()),
col_names = colnames(batch_adjusted_matrix()))
observeEvent(input$corrected_matrices,{
if(is.null(input$corrected_matrices)){
output$batch_matrix_summary <- NULL
}
output$batch_matrix_summary <- DT::renderDataTable({
matrix_summary_table(matrix_summary = summary(batch_adjusted_matrix()[[input$corrected_matrices]]),
col_names = colnames(batch_adjusted_matrix()[[input$corrected_matrices]]))
})
})

#Show the download button
observeEvent(batch_adjusted_matrix(), {
if(calculated_adjusted_matrix() == FALSE){
Expand Down
19 changes: 9 additions & 10 deletions app/ui.r
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Original file line number Diff line number Diff line change
Expand Up @@ -229,32 +229,31 @@ dashboardPage(title = "Batch Effect Analysis and Visualization",
selectInput("key_pie", "Select Key to check the value distribution", c("")),
plotlyOutput("batch_pie_plot", width = "auto", height = "auto"))),
br(),br(),
selectInput("corrected_matrices", "Batch Corrected Matrices", choices = NULL),
actionButton("calculate_batch_matrix", "Adjust matrix using ComBat")
),
shinydashboard::box(width = 6,
conditionalPanel(
condition = "input.batch_effect_choice == 'combat'",

selectInput('batch', "Select a batch to adjust for",c("")),
selectInput("adj_var", "Adjustment Variable",c("")),
selectInput("interest_var", "Variable of interest", c(""))
selectInput('batch_combat', "Select a batch to adjust for",c("")),
selectInput("adj_var_combat", "Adjustment Variable",c("")),
selectInput("interest_var_combat", "Variable of interest", c(""))
),
conditionalPanel(
condition = "input.batch_effect_choice == 'sva'",

selectInput("adj_var", "Adjustment Variable",c("")),
selectInput("interest_var", "Variable of interest", c(""))
selectInput("adj_var_sva", "Adjustment Variable",c("")),
selectInput("interest_var_sva", "Variable of interest", c(""))
),
conditionalPanel(
condition = "input.batch_effect_choice == 'supervised_sva'",

selectInput('batch', "Select a batch to adjust for",c("")),
selectInput("adj_var", "Adjustment Variable",c("")),
selectInput("interest_var", "Variable of interest", c(""))
selectInput('batch_supervised_sva', "Select a batch to adjust for",c("")),
selectInput("adj_var_supervised_sva", "Adjustment Variable",c("")),
selectInput("interest_var_supervised_sva", "Variable of interest", c(""))
),
downloadButton("downloadAdjustedMatrix", "Download Data")


)
),

Expand Down
3 changes: 1 addition & 2 deletions functions/inserted_chr_list.r
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,7 @@ inserted_chr_list <- function(user_key, id_genome, genomes){
where = "afterEnd",
ui = tags$div(
selectInput('chr', 'Select a Chromosome, or nothign for the whole genome',
c("",deepblue_info(id = genomes$id[grep(id_genome, genomes$name)],
user_key = user_key)$chromosomes$name),selected = "",
c("",deepblue_chromosomes(genome = input$genome, user_key = user_key)),selected = "",
multiple = TRUE),
id = id_genome
)
Expand Down
43 changes: 43 additions & 0 deletions functions/rna_seq_data.r
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Original file line number Diff line number Diff line change
@@ -0,0 +1,43 @@
rna_seq_data <- function(project,
experiments_info_meta,
user_key){

all_genes <- readr::read_tsv("../genecode_v23_genes.tsv")
protein_coding_genes <- all_genes[all_genes$gene_type == "protein_coding" &
all_genes$source == "HAVANA",]
protein_coding_genes_id <- protein_coding_genes$gene_id

if(project == "TEPIC reprocessed IHEC data"){
output_format <- "CHROMOSOME,START,END,@STRAND(gencode v23),@GENE_NAME(gencode v23),@SAMPLE_ID,TPM"
}else if(project == "DEEP"){
output_format <- "CHROMOSOME,START,END,@STRAND(gencode v23),@GENE_NAME(gencode v23),@SAMPLE_ID,FPKM"
}

gene_expr_query <- deepblue_select_expressions(
expression_type = "gene",
gene_model = "gencode v23",
identifiers = protein_coding_genes_id,
project = project,
user_key = user_key)

gene_expr_request_id <- deepblue_get_regions(
query_id = gene_expr_query,
output_format ="CHROMOSOME,START,END,@STRAND(gencode v23),@GENE_NAME(gencode v23),@SAMPLE_ID,TPM,FPKM",
user_key = user_key)

while(deepblue_info(gene_expr_request_id)$state == "running"){
Sys.sleep(10)
}

gene_expr_regions <- deepblue_download_request_data(gene_expr_request_id)

gene_expr_df <- as.data.frame(gene_expr_regions) %>%
spread(key = `X.SAMPLE_ID`, value = TPM)

sample_cols <- grep(colnames(gene_expr_df), pattern = "s[0-9].", value = TRUE)
gene_expr_matrix <- data.matrix(gene_expr_df[,sample_cols])
rownames(gene_expr_matrix) <- gene_expr_df$X.GENE_NAME.gencode.v23.

attr(gene_expr_df, "meta") <- experiments_info_meta
return(gene_expr_df)
}

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