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Package: tpeold
Title: Interface for Finding TPE-OLD Candidates
Version: 0.0.0.9000
Authors@R:
person(
"Elias",
"Projahn",
email = "elias@johrpan.de",
role = c("aut", "cre")
)
Description: This package provides a Shiny interface for analyzing genes and
finding TPE-OLD candidates based on known TPE-OLD genes.
License: AGPL (>= 3)
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.2
Imports:
data.table,
DT,
geposan,
gprofiler2,
plotly,
rlang,
rclipboard,
shiny,
shinyjs

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GNU Affero General Public License
=================================
_Version 3, 19 November 2007_
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### 13. Remote Network Interaction; Use with the GNU General Public License.
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### 14. Revised Versions of this License.
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If the Program specifies that a proxy can decide which future versions
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### 15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
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HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT
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DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR
CORRECTION.
### 16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
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CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES,
INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES
ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT
NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR
LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM
TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER
PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
### 17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
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copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
## How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these
terms.
To do so, attach the following notices to the program. It is safest to
attach them to the start of each source file to most effectively state
the exclusion of warranty; and each file should have at least the
"copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper
mail.
If your software can interact with users remotely through a computer
network, you should also make sure that it provides a way for users to
get its source. For example, if your program is a web application, its
interface could display a "Source" link that leads users to an archive
of the code. There are many ways you could offer source, and different
solutions will be better for different programs; see section 13 for
the specific requirements.
You should also get your employer (if you work as a programmer) or
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. For more information on this, and how to apply and follow
the GNU AGPL, see <https://www.gnu.org/licenses/>.

5
NAMESPACE Normal file
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@ -0,0 +1,5 @@
# Generated by roxygen2: do not edit by hand
export(run_app)
import(data.table)
import(shiny)

8
R/app.R Normal file
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@ -0,0 +1,8 @@
#' Run the application server.
#'
#' @param port The port to serve the application on.
#'
#' @export
run_app <- function(port = 3464) {
shiny::runApp(shiny::shinyApp(ui, server), port = port)
}

22
data.R → R/data.R
View file

@ -1,6 +1,4 @@
library(data.table)
#' Species IDs of known replicatively aging species.
# Species IDs of known replicatively aging species.
species_ids_replicative <- c(
"bihybrid",
"btaurus",
@ -29,14 +27,14 @@ species_ids_replicative <- c(
"tgelada"
)
#' Species from [geposan] and their aging status.
# Species from [geposan] and their aging status.
species <- geposan::species[, .(
id,
name,
replicative = id %chin% species_ids_replicative
)]
#' Gene names of genes for verified TPE-OLD genes.
# Gene names of genes for verified TPE-OLD genes.
genes_verified_tpe_old <- c(
"C1S",
"DSP",
@ -45,7 +43,7 @@ genes_verified_tpe_old <- c(
"TERT"
)
#' Gene names of genes with a suggested TPE-OLD.
# Gene names of genes with a suggested TPE-OLD.
genes_suggested_tpe_old <- c(
"AKAP3",
"ANO2",
@ -60,7 +58,7 @@ genes_suggested_tpe_old <- c(
"TSPAN9"
)
#' Genes from [geposan] and their TPE-OLD status.
# Genes from [geposan] and their TPE-OLD status.
genes <- geposan::genes[, .(
id,
name,
@ -69,7 +67,7 @@ genes <- geposan::genes[, .(
verified = name %chin% genes_verified_tpe_old
)]
#' All available methods from [geposan] and additional information on them.
# All available methods from [geposan] and additional information on them.
methods <- list(
list(
id = "clusteriness",
@ -93,10 +91,10 @@ methods <- list(
)
)
#' Gene IDs of known or suggested TPE-OLD genes.
# Gene IDs of known or suggested TPE-OLD genes.
genes_tpe_old <- genes[suggested | verified == TRUE, id]
#' Preset for [geposan] including all species and TPE-OLD genes for reference.
# Preset for [geposan] including all species and TPE-OLD genes for reference.
preset_all_species <- geposan::preset(
methods = c("clusteriness", "correlation", "proximity", "neural"),
species = species$id,
@ -104,8 +102,8 @@ preset_all_species <- geposan::preset(
reference_genes = genes_tpe_old
)
#' Preset for [geposan] including only replicatively aging species as well as
#' TPE-OLD genes for reference.
# Preset for [geposan] including only replicatively aging species as well as
# TPE-OLD genes for reference.
preset_replicative_species <- geposan::preset(
methods = c("clusteriness", "correlation", "proximity", "neural"),
species = species_ids_replicative,

14
methods.R → R/methods.R
View file

@ -1,6 +1,4 @@
library(shiny)
#' Construct UI for the methods editor.
# Construct UI for the methods editor.
methods_ui <- function(id) {
initial_weight <- 100 / length(methods)
@ -36,11 +34,11 @@ methods_ui <- function(id) {
)
}
#' Construct server for the methods editor.
#'
#' @param analysis The reactive containing the results to be weighted.
#'
#' @return A reactive containing the weighted results.
# Construct server for the methods editor.
#
# @param analysis The reactive containing the results to be weighted.
#
# @return A reactive containing the weighted results.
methods_server <- function(id, analysis) {
moduleServer(id, function(input, output, session) {
observeEvent(input$optimize_button, {

35
rank_plot.R → R/rank_plot.R
View file

@ -1,23 +1,20 @@
library(data.table)
library(plotly)
#' Draw a plot displaying the rank of reference genes.
#'
#' The input table should contain the following columns:
#'
#' - `gene` Gene IDs of genes to display.
#' - `name` Name of genes to display.
#' - `score` Score of the genes.
#' - `rank` Rank of the genes based on the score.
#'
#' @param results Results to display.
#' @param reference_gene_ids IDs of reference genes.
#' @param cutoff Cut-off score.
# Draw a plot displaying the rank of reference genes.
#
# The input table should contain the following columns:
#
# - `gene` Gene IDs of genes to display.
# - `name` Name of genes to display.
# - `score` Score of the genes.
# - `rank` Rank of the genes based on the score.
#
# @param results Results to display.
# @param reference_gene_ids IDs of reference genes.
# @param cutoff Cut-off score.
rank_plot <- function(results, reference_gene_ids, cutoff) {
first_not_included_rank <- results[score < cutoff, min(rank)]
last_rank <- results[, .N]
plot <- plot_ly() |> add_trace(
plot <- plotly::plot_ly() |> plotly::add_trace(
data = results,
x = ~rank,
y = ~score,
@ -25,7 +22,7 @@ rank_plot <- function(results, reference_gene_ids, cutoff) {
type = "scatter",
mode = "line",
hoverinfo = "skip"
) |> add_trace(
) |> plotly::add_trace(
data = results[gene %chin% reference_gene_ids],
x = ~rank,
y = ~score,
@ -33,13 +30,13 @@ rank_plot <- function(results, reference_gene_ids, cutoff) {
name = ~name,
width = 10,
type = "bar"
) |> layout(
) |> plotly::layout(
xaxis = list(title = "Ranks"),
yaxis = list(title = "Score")
)
if (first_not_included_rank <= last_rank) {
plot <- plot |> layout(
plot <- plot |> plotly::layout(
shapes = list(
type = "rect",
fillcolor = "black",

22
scatter_plot.R → R/scatter_plot.R
View file

@ -1,24 +1,20 @@
library(data.table)
library(plotly)
#' Draw a scatter plot containing gene positions.
#'
#' @param results Results from [`process_input()`].
#' @param species Species to be displayed.
#' @param genes Genes to be displayed.
#' @param distances Distance data to display.
scatter_plot <- function(results, species, genes, distances) {
# Draw a scatter plot containing gene positions.
#
# @param results Results from [`process_input()`].
# @param species Species to be displayed.
# @param genes Genes to be displayed.
scatter_plot <- function(results, species, genes) {
species_ids <- species[, id]
data <- merge(
genes[, .(id, name)],
distances[species %in% species_ids],
geposan::distances[species %in% species_ids],
by.x = "id", by.y = "gene"
)
data[name == "", name := "Unknown"]
plot_ly(
plotly::plot_ly(
data = data,
x = ~species,
y = ~distance,
@ -26,7 +22,7 @@ scatter_plot <- function(results, species, genes, distances) {
name = ~name,
type = "scatter",
mode = "markers"
) |> layout(
) |> plotly::layout(
xaxis = list(
title = "Species",
tickvals = species_ids,

55
server.R → R/server.R
View file

@ -1,18 +1,5 @@
library(data.table)
library(DT)
library(geposan)
library(gprofiler2)
library(plotly)
library(rclipboard)
library(shiny)
source("methods.R")
source("rank_plot.R")
source("scatter_plot.R")
source("utils.R")
#' Java script function to replace gene IDs with Ensembl gene links.
js_link <- JS("function(row, data) {
# Java script function to replace gene IDs with Ensembl gene links.
js_link <- DT::JS("function(row, data) {
let id = data[1];
var name = data[2];
if (!name) name = 'Unknown';
@ -21,7 +8,7 @@ js_link <- JS("function(row, data) {
}")
server <- function(input, output, session) {
#' Show the customized slider for setting the required number of species.
# Show the customized slider for setting the required number of species.
output$n_species_slider <- renderUI({
sliderInput(
"n_species",
@ -37,7 +24,7 @@ server <- function(input, output, session) {
)
})
#' Compute the results according to the preset.
# Compute the results according to the preset.
analysis <- reactive({
# Select the preset.
preset <- if (input$species == "all") {
@ -70,7 +57,7 @@ server <- function(input, output, session) {
)
# Count included species from the preset per gene.
genes_n_species <- distances[
genes_n_species <- geposan::distances[
species %chin% preset$species_ids,
.(n_species = .N),
by = "gene"
@ -85,18 +72,18 @@ server <- function(input, output, session) {
# Rank the results.
results <- methods_server("methods", analysis)
#' Apply the cut-off score to the ranked results.
# Apply the cut-off score to the ranked results.
results_filtered <- reactive({
results()[score >= input$cutoff / 100]
})
output$genes <- renderDT({
output$genes <- DT::renderDT({
method_ids <- sapply(methods, function(method) method$id)
method_names <- sapply(methods, function(method) method$name)
columns <- c("rank", "gene", "name", "chromosome", method_ids, "score")
column_names <- c("", "Gene", "", "Chromosome", method_names, "Score")
dt <- datatable(
dt <- DT::datatable(
results_filtered()[, ..columns],
rownames = FALSE,
colnames = column_names,
@ -112,7 +99,7 @@ server <- function(input, output, session) {
)
)
formatPercentage(dt, c(method_ids, "score"), digits = 1)
DT::formatPercentage(dt, c(method_ids, "score"), digits = 1)
})
output$copy <- renderUI({
@ -126,13 +113,13 @@ server <- function(input, output, session) {
splitLayout(
cellWidths = "auto",
rclipButton(
rclipboard::rclipButton(
"copy_ids_button",
"Copy gene IDs",
genes_text,
icon = icon("clipboard")
),
rclipButton(
rclipboard::rclipButton(
"copy_names_button",
"Copy gene names",
names_text,
@ -141,7 +128,7 @@ server <- function(input, output, session) {
)
})
output$scatter <- renderPlotly({
output$scatter <- plotly::renderPlotly({
results <- results_filtered()
gene_ids <- results[input$genes_rows_selected, gene]
@ -153,7 +140,7 @@ server <- function(input, output, session) {
species[replicative == TRUE]
}
scatter_plot(results, species, genes, distances)
scatter_plot(results, species, genes)
})
output$assessment_synopsis <- renderText({
@ -190,7 +177,7 @@ server <- function(input, output, session) {
)
})
output$rank_plot <- renderPlotly({
output$rank_plot <- plotly::renderPlotly({
rank_plot(
results(),
genes[suggested | verified == TRUE, id],
@ -198,10 +185,18 @@ server <- function(input, output, session) {
)
})
output$gost <- renderPlotly({
output$gost <- plotly::renderPlotly({
if (input$enable_gost) {
result <- gost(results_filtered()[, gene], ordered_query = TRUE)
gostplot(result, capped = FALSE, interactive = TRUE)
result <- gprofiler2::gost(
results_filtered()[, gene],
ordered_query = TRUE
)
gprofiler2::gostplot(
result,
capped = FALSE,
interactive = TRUE
)
} else {
NULL
}

17
ui.R → R/ui.R
View file

@ -1,13 +1,6 @@
library(DT)
library(plotly)
library(rclipboard)
library(shiny)
source("methods.R")
ui <- fluidPage(
shinyjs::useShinyjs(),
rclipboardSetup(),
rclipboard::rclipboardSetup(),
titlePanel("TPE-OLD candidates"),
sidebarLayout(
sidebarPanel(
@ -42,12 +35,12 @@ ui <- fluidPage(
uiOutput("copy"),
div(
style = "margin-top: 16px",
DTOutput("genes", height = "1000px")
DT::DTOutput("genes", height = "1000px")
)
),
tabPanel(
"Positions",
plotlyOutput(
plotly::plotlyOutput(
"scatter",
width = "100%",
height = "600px"
@ -58,7 +51,7 @@ ui <- fluidPage(
htmlOutput("assessment_synopsis"),
div(
style = "margin-top: 16px",
plotlyOutput(
plotly::plotlyOutput(
"rank_plot",
width = "100%",
height = "600px"
@ -74,7 +67,7 @@ ui <- fluidPage(
),
conditionalPanel(
"input.enable_gost == true",
plotlyOutput(
plotly::plotlyOutput(
"gost",
width = "100%",
height = "600px"

20
utils.R → R/utils.R
View file

@ -1,10 +1,8 @@
library(rlog)
#' Run a function caching the result on the file system.
#'
#' The function will be called with the appended arguments. The [`id`] argument
#' will be used to identify the cache file on the file system and in log
#' messages.
# Run a function caching the result on the file system.
#
# The function will be called with the appended arguments. The [`id`] argument
# will be used to identify the cache file on the file system and in log
# messages.
run_cached <- function(id, func, ...) {
if (!dir.exists("cache")) {
dir.create("cache")
@ -13,8 +11,6 @@ run_cached <- function(id, func, ...) {
cache_file <- paste("cache/", id, ".rds", sep = "")
if (file.exists(cache_file)) {
log_info(sprintf("Loading %s from cache", id))
# If the cache file exists, we restore the data from it.
readRDS(cache_file)
} else {
@ -27,3 +23,9 @@ run_cached <- function(id, func, ...) {
data
}
}
# This is needed to make data.table's and shiny's symbols available within the
# package.
#' @import data.table
#' @import shiny
NULL

9
main.R
View file

@ -1,9 +0,0 @@
library(shiny)
# Initialize data first.
source("data.R")
source("server.R")
source("ui.R")
runApp(shinyApp(ui, server))

14
man/run_app.Rd Normal file
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@ -0,0 +1,14 @@
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/app.R
\name{run_app}
\alias{run_app}
\title{Run the application server.}
\usage{
run_app(port = 3464)
}
\arguments{
\item{port}{The port to serve the application on.}
}
\description{
Run the application server.
}