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maaslin.R
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maaslin.R
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maaslin_ui <- function(id) {
ns <- NS(id)
res <- div(
class = "maaslin-body",
fluidRow(
column(5,
shinydashboardPlus::box(
width = 12, title = "Maaslin2 Analysis",
status = "warning",
collapsible = TRUE,
# column(
# width = 5, class = "maaslin2",
fluidRow(
column(width = 6,
style=list("padding-right: 5px;"),
numericInput(
ns("min_abundance"),
"Min abundance:",
min = 0,
max = 1,
value = 0
)
),
column(width = 6,
style=list("padding-left: 5px;"),
numericInput(
ns("min_prevalence"),
"Min prevalence:",
value = 0.1
)
)
),
fluidRow(
column(width = 6,
style=list("padding-right: 5px;"),
numericInput(
ns("min_variance"),
"Min variance:",
value = 0.0
)
),
column(width = 6,
style=list("padding-left: 5px;"),
numericInput(
ns("max_significance"),
"Q-value cutoff:",
value = 0.25
)
)
),
fluidRow(
column(width = 6,
style=list("padding-right: 5px;"),
numericInput(
ns("topn"),
"Top features",
min = 1,
value = 50,
step = 1
)
),
column(width = 6,
style=list("padding-left: 5px;"),
pickerInput(
ns("level"),
"Taxonomic level:",
choices = NULL
)
)
),
fluidRow(
column(width = 6,
style=list("padding-right: 5px;"),
pickerInput(
ns("method"),
"Analysis method:",
c("LM", "CPLM", "NEGBIN", "ZINB")
)
),
column(width = 6,
style=list("padding-left: 5px;"),
pickerInput(
ns("standardize"),
"Standardize(or not):",
choices = c("TRUE", "FALSE")
)
)
),
fluidRow(
column(width = 6,
style=list("padding-right: 5px;"),
pickerInput(
ns("normalization"),
label = "Normalization method:",
choices = c("TSS", "CLR", "CSS", "NONE", "TMM"),
selected = "NONE"
)
),
column(width = 6,
style=list("padding-left: 5px;"),
pickerInput(
ns("transform"),
label = "Transform method:",
choices = c("LOG", "LOGIT", "AST", "NONE"),
selected = "AST"
)
)
),
actionButton(ns("btn"), "Submit"),
tri_select_input_ui("maaslin", NULL)
)
),
column(7,
jqui_resizable(
plotOutput(ns("plot"), width = "800px"),
operation = c("enable", "disable", "destroy", "save", "load"),
options = list(
minHeight = 100, maxHeight = 900,
minWidth = 300, maxWidth = 1200
)
)
#tri_select_input_ui("maaslin", NULL)
)
)
#tri_select_input_ui("maaslin", NULL)
#)
# shinydashboardPlus::box(
# width = 12, title = "Maaslin2 Analysis",
# status = "warning",
# collapsible = TRUE,
# # column(
# # width = 5, class = "maaslin2",
# fluidRow(
# column(width = 6,
# style=list("padding-right: 5px;"),
# numericInput(
# ns("min_abundance"),
# "Min abundance:",
# min = 0,
# max = 1,
# value = 0
# )
# ),
# column(width = 6,
# style=list("padding-left: 5px;"),
# numericInput(
# ns("min_prevalence"),
# "Min prevalence:",
# value = 0.1
# )
# )
# ),
#
# fluidRow(
# column(width = 6,
# style=list("padding-right: 5px;"),
# numericInput(
# ns("min_variance"),
# "Min variance:",
# value = 0.0
# )
# ),
# column(width = 6,
# style=list("padding-left: 5px;"),
# numericInput(
# ns("max_significance"),
# "Q-value cutoff:",
# value = 0.25
# )
# )
# ),
#
# fluidRow(
# column(width = 6,
# style=list("padding-right: 5px;"),
# numericInput(
# ns("topn"),
# "Top features",
# min = 1,
# value = 50,
# step = 1
# )
# ),
# column(width = 6,
# style=list("padding-left: 5px;"),
# pickerInput(
# ns("level"),
# "Taxonomic level:",
# choices = NULL
# )
# )
# ),
# fluidRow(
# column(width = 6,
# style=list("padding-right: 5px;"),
# pickerInput(
# ns("method"),
# "Analysis method:",
# c("LM", "CPLM", "NEGBIN", "ZINB")
# )
# ),
# column(width = 6,
# style=list("padding-left: 5px;"),
# pickerInput(
# ns("standardize"),
# "Standardize(or not):",
# choices = c("TRUE", "FALSE")
# )
# )
# ),
# fluidRow(
# column(width = 6,
# style=list("padding-right: 5px;"),
# pickerInput(
# ns("normalization"),
# label = "Normalization method:",
# choices = c("TSS", "CLR", "CSS", "NONE", "TMM"),
# selected = "NONE"
# )
# ),
# column(width = 6,
# style=list("padding-left: 5px;"),
# pickerInput(
# ns("transform"),
# label = "Transform method:",
# choices = c("LOG", "LOGIT", "AST", "NONE"),
# selected = "AST"
# )
# )
# )
# # numericInput(
# # ns("min_abundance"),
# # "Min abundance:",
# # min = 0,
# # max = 1,
# # value = 0
# # ),
# # numericInput(
# # ns("min_prevalence"),
# # "Min prevalence:",
# # value = 0.1
# # ),
# # numericInput(
# # ns("min_variance"),
# # "Min variance:",
# # value = 0.0
# # ),
# # numericInput(
# # ns("max_significance"),
# # "Q-value cutoff:",
# # value = 0.25
# # ),
# # numericInput(
# # ns("topn"),
# # "Top features",
# # min = 1,
# # value = 50,
# # step = 1
# # ),
# # pickerInput(
# # ns("level"),
# # "Taxonomic level:",
# # choices = NULL
# # ),
# # pickerInput(
# # ns("method"),
# # "Analysis method:",
# # c("LM", "CPLM", "NEGBIN", "ZINB")
# # ),
# # pickerInput(
# # ns("standardize"),
# # "Standardize(or not):",
# # choices = c("TRUE", "FALSE")
# # ),
# # pickerInput(
# # ns("normalization"),
# # label = "Normalization method:",
# # choices = c("TSS", "CLR", "CSS", "NONE", "TMM"),
# # selected = "NONE"
# # ),
# # pickerInput(
# # ns("transform"),
# # label = "Transform method:",
# # choices = c("LOG", "LOGIT", "AST", "NONE"),
# # selected = "AST"
# # )
# #),
# # column(
# # width = 7,
# div(
# style = "margin-top: 25px",
# tri_select_input_ui("maaslin", NULL)
# )
# #),
# fluidRow(),
# actionButton(ns("btn"), "Submit")
# ),
# shinydashboardPlus::box(
# width = 12,
# title = "Plot Download",
# status = "success",
# solidHeader = FALSE,
# collapsible = TRUE,
# plotOutput(ns("plot")),
# numericInput(ns("width_slider"), "width:", 10,1, 20),
# numericInput(ns("height_slider"), "height:", 8, 1, 20),
# radioButtons(inputId = ns('extPlot'),
# label = 'Output format',
# choices = c('PDF' = '.pdf',"PNG" = '.png','TIFF'='.tiff'),
# inline = TRUE),
# downloadButton(ns("downloadPlot"), "Download Plot"),
# downloadButton(ns("downloadTable"), "Download Table")
# ),
# fluidRow(),
# jqui_resizable(
# plotOutput(ns("plot"), width = "800px"),
# operation = c("enable", "disable", "destroy", "save", "load"),
# options = list(
# minHeight = 100, maxHeight = 900,
# minWidth = 300, maxWidth = 1200
# )
# ),
#DTOutput(ns("tbl"), width = "500px", height = "400px")
)
}
maaslin_mod <- function(id, mpse) {
moduleServer(
id,
function(input, output, session) {
effects <- reactiveValues(
total = NULL,
fixed = NULL,
random = NULL
)
observe({
req(inherits(mpse, "MPSE"))
lev <- sapply(mp_extract_sample(mpse)[, -1], function(n) length(unique(n)))
group <- names(lev[lev > 1])
taxa <- names(mp_extract_taxonomy(mpse))[-1]
effects$total <- group
updatePickerInput(session, "level",
choices = taxa,
selected = taxa[3]
)
updateSelectInput(session, "total_effects", choices = group)
})
observeEvent(input$total_to_fixed, {
effects$fixed <- c(effects$fixed, input$total_effects)
effects$total <- effects$total[!effects$total %in% input$total_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$fixed_to_total, {
effects$total <- c(effects$total, input$fixed_effects)
effects$fixed <- effects$fixed[!effects$fixed %in% input$fixed_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$total_to_random, {
effects$random <- c(effects$random, input$total_effects)
effects$total <- effects$total[!effects$total %in% input$total_effects]
updateSelectInput(session, "random_effects", choices = effects$random)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$random_to_total, {
effects$total <- c(effects$total, input$random_effects)
effects$random <- effects$random[!effects$random %in% input$random_effects]
updateSelectInput(session, "random_effects", choices = effects$random)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$fixed_to_random, {
effects$random <- c(effects$random, input$fixed_effects)
effects$fixed <- effects$fixed[!effects$fixed %in% input$fixed_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "random_effects", choices = effects$random)
})
observeEvent(input$random_to_fixed, {
effects$fixed <- c(effects$fixed, input$random_effects)
effects$random<- effects$random[!effects$random %in% input$random_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "random_effects", choices = effects$random)
})
res <- eventReactive(input$btn, {
req(inherits(mpse, "MPSE"))
input$btn
level <- isolate({
input$level
})
min_abundance <- isolate({
input$min_abundance
})
min_prevalence <- isolate({
input$min_prevalence
})
min_prevalence <- isolate({
input$min_prevalence
})
min_variance <- isolate({
input$min_variance
})
topn <- isolate({
input$topn
})
max_significance <- isolate({
input$max_significance
})
transform <- isolate({input$transform})
standardize <- isolate({as.logical(input$standardize)})
normalization <- isolate({
input$normalization
})
method <- isolate({
input$method
})
fixed_effects <- isolate({
effects$fixed
})
random_effects <- isolate({
effects$random
})
rdfn <- randomFile()
abuda <- maaslin2_input_abuda(mpse, level)
metada <- mp_extract_sample(mpse)
print(rdfn)
reference <- lapply(effects$fixed, function(n) {
x <- metada[[n]]
if (is.character(x) && length(unique(x)) > 2) {
return(paste(n, x[1], sep = ","))
}
})
reference <- paste0(unlist(reference), collapse = ";")
fit_data <- Maaslin2(
input_data = abuda,
input_metadata = metada,
output = rdfn,
min_abundance = min_abundance,
min_prevalence = min_prevalence,
min_variance = min_variance,
max_significance = max_significance,
heatmap_first_n = topn,
standardize = standardize,
normalization = normalization,
transform = transform,
analysis_method = method,
# fixed_effects = c("age", "BMI", "gender"),
fixed_effects = effects$fixed,
random_effects = effects$random,
reference = reference,
plot_heatmap = F,
plot_scatter = F
)
sign_res <- paste(rdfn, "significant_results.tsv", sep = "/")
p <- Maaslin2:::maaslin2_heatmap(sign_res, title = NULL)
return(list(plot = p, tbl = fit_data$results))
})
output$plot <- renderPlot(res = 200, {
req(inherits(res(), "list"))
res()$plot
})
output$downloadPlot <- downloadHandler(
filename = function(){
paste("plot", input$extPlot, sep='')},
content = function(file){
req(inherits(res(), "list"))
ggsave(file,
plot = res()$plot,
width = input$width_slider,
height = input$height_slider,
dpi = 300)
})
# output$downloadTable <- downloadHandler(
# filename = function(){ "MP_Data.csv" },
# content = function(file){
# req(p_PCA())
# table <- mp_pcoa() %>% mp_extract_sample
# n <- names(table)[sapply(table, class) == "list"]
# write.csv(table %>% select(-c(n)),
# file,
# row.names = FALSE)
# })
output$tbl<- renderDT({
req(inherits(res(), "list"))
res()$tbl
})
}
)
}
maaslin2_input_abuda <- function(mpse, taxa.level) {
abuda <- mpse %>%
mp_cal_abundance(Abundance, force = TRUE) %>%
mp_extract_abundance(taxa.class = !!sym(taxa.level)) %>%
tidyr::unnest(AbundanceBySample) %>%
select(Sample, label, RelAbundanceBySample) %>%
tidyr::pivot_wider(id_cols = Sample, names_from = label, values_from = RelAbundanceBySample)
abuda[, -1] <- abuda[, -1] / 100
return(abuda)
}
randomFile <- function(n = 1) {
a <- do.call(paste0, replicate(5, sample(c(LETTERS, letters), n, TRUE), FALSE))
filename <- paste0(a, sprintf("%04d", sample(9999, n, TRUE)), sample(LETTERS, n, TRUE))
paste(tempdir(), filename, sep = "/")
}
total_effects_box <- function(id, choices) {
ns <- NS(id)
res <- div(
style = "float: left;",
# style = "display: inline-block;",
div(
class = "sel-header",
style = "text-align: center; width: 200px; height: 30px; background: #3c8dbc;",
tags$b("Groups:", style = "dispaly: block; line-height: 30px")
),
div(
tags$select(
id = ns("total_effects"),
multiple = "multiple",
style = "width: 200px; height: 400px",
lapply(choices, function(i) {
tags$option(i, value = i)
})
)
)
)
return(res)
}
trans_btn_box <- function(id) {
ns <- NS(id)
res <-
div(
style = "float: left; text-align: center; width: 80px; height: 430px;",
actionButton(ns("total_to_fixed"), NULL, icon("arrow-right"),
style = "width: 60px; height: 30px; margin-top: 60px"),
actionButton(ns("fixed_to_total"), NULL, icon("arrow-left"),
style = "width: 60px; height: 30px; margin-top: 3px"),
actionButton(ns("total_to_random"), NULL, icon("arrow-right"),
style = "width: 60px; height: 30px; margin-top: 180px"),
actionButton(ns("random_to_total"), NULL, icon("arrow-left"),
style = "width: 60px; height: 30px; margin-top: 3px")
)
return(res)
}
sel_effects_box <- function(id) {
ns <- NS(id)
res <- div(
style = "float: left;",
# style = "display: inline-block;",
div(
class = "sel-header",
style = "text-align: center; width: 200px; height: 30px; background: #00a65a;",
tags$b("Fixed effects", style = "dispaly: block; line-height: 30px")
),
div(
tags$select(
id = ns("fixed_effects"),
multiple = "multiple",
style = "width: 200px; height: 150px;"
)
),
div(
style = "text-align: center; width: 200px; height: 69px;",
actionButton(ns("fixed_to_random"), NULL, icon("arrow-down"), style = "width: 30px; height: 50px; margin-top: 10px"),
actionButton(ns("random_to_fixed"), NULL, icon("arrow-up"), style = "width: 30px; height: 50px; margin-top: 10px; text-align: center;")
),
div(
style = "text-align: center; width: 200px; height: 30px; background: #f39c12;",
tags$b("Random effects", style = "dispaly: block; line-height: 30px")
),
div(
tags$select(
id = ns("random_effects"),
multiple = "multiple",
style = "width: 200px; height: 150px"
)
)
)
return(res)
}
tri_select_input_ui <- function(id, choices) {
div(
total_effects_box(id, choices),
trans_btn_box(id),
sel_effects_box(id)
)
}
tri_select_input_mod <- function(id, choices) {
moduleServer(
id,
function(input, output, session) {
effects <- reactiveValues(
total = choices,
fixed = NULL,
random = NULL
)
observe({
updateSelectInput(session, "total_effects", choices = choices)
})
observeEvent(input$total_to_fixed, {
effects$fixed <- c(effects$fixed, input$total_effects)
effects$total <- effects$total[!effects$total %in% input$total_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$fixed_to_total, {
effects$total <- c(effects$total, input$fixed_effects)
effects$fixed <- effects$fixed[!effects$fixed %in% input$fixed_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$total_to_random, {
effects$random <- c(effects$random, input$total_effects)
effects$total <- effects$total[!effects$total %in% input$total_effects]
updateSelectInput(session, "random_effects", choices = effects$random)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$random_to_total, {
effects$total <- c(effects$total, input$random_effects)
effects$random <- effects$random[!effects$random %in% input$random_effects]
updateSelectInput(session, "random_effects", choices = effects$random)
updateSelectInput(session, "total_effects", choices = effects$total)
})
observeEvent(input$fixed_to_random, {
effects$random <- c(effects$random, input$fixed_effects)
effects$fixed <- effects$fixed[!effects$fixed %in% input$fixed_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "random_effects", choices = effects$random)
})
observeEvent(input$random_to_fixed, {
effects$fixed <- c(effects$fixed, input$random_effects)
effects$random<- effects$random[!effects$random %in% input$random_effects]
updateSelectInput(session, "fixed_effects", choices = effects$fixed)
updateSelectInput(session, "random_effects", choices = effects$random)
})
return(effects)
}
)
}