johrpan/geposanui
1
0
Fork 0
mirror of https://github.com/johrpan/geposanui.git synced 2025-10-26 11:17:24 +01:00
Code Issues Projects Releases Packages Wiki Activity Actions

Generalize method definitions

Browse source
This commit is contained in:
Elias Projahn 2021-10-15 09:26:57 +02:00
parent d3edeefbe2
commit 9b0b3c13f5
7 changed files with 137 additions and 169 deletions
Download patch file Download diff file Expand all files Collapse all files

55
server.R
View file

@ -47,16 +47,18 @@ server <- function(input, output) {
# Compute scoring factors and the weighted score.
clusteriness_weight <- input$clusteriness / 100
correlation_weight <- input$correlation / 100
neural_weight <- input$neural / 100
total_weight <- clusteriness_weight + correlation_weight + neural_weight
clusteriness_factor <- clusteriness_weight / total_weight
correlation_factor <- correlation_weight / total_weight
neural_factor <- neural_weight / total_weight
total_weight <- 0.0
results[, score := 0.0]
results[, score := clusteriness_factor * clusteriness +
correlation_factor * correlation + neural_factor * neural]
for (method in methods) {
weight <- input[[method$id]]
total_weight <- total_weight + weight
column <- method$id
weighted <- weight * results[, ..column]
results[, score := score + weighted]
}
results[, score := score / total_weight]
# Exclude genes with too few species.
results <- results[n_species >= input$n_species]
@ -75,33 +77,22 @@ server <- function(input, output) {
# Apply the cut-off score.
results <- results[score >= input$cutoff / 100]
# Order the results based on their score. The resulting index will be
# used as the "rank".
# Order the results based on their score.
setorder(results, -score, na.last = TRUE)
results[, rank := .I]
})
output$genes <- renderDT({
method_ids <- sapply(methods, function(method) method$id)
method_names <- sapply(methods, function(method) method$name)
columns <- c("rank", "gene", "name", method_ids, "score")
column_names <- c("", "Gene", "", method_names, "Score")
dt <- datatable(
results()[, .(
.I,
gene,
name,
clusteriness,
correlation,
neural,
score
)],
results()[, ..columns],
rownames = FALSE,
colnames = c(
"",
"Gene",
"",
"Clusters",
"Correlation",
"Neural",
"Score"
),
colnames = column_names,
style = "bootstrap",
options = list(
rowCallback = js_link,
@ -109,11 +100,7 @@ server <- function(input, output) {
)
)
formatPercentage(
dt,
c("clusteriness", "correlation", "neural", "score"),
digits = 1
)
formatPercentage(dt, c(method_ids, "score"), digits = 1)
})
output$synposis <- renderText({