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Merge branch 'release/v1.1.3'
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DESCRIPTION

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Package: scone
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Version: 1.1.2
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Version: 1.1.3
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Title: Single Cell Overview of Normalized Expression data
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Description: SCONE is an R package for comparing and ranking the performance of
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different normalization schemes for single-cell RNA-seq and other

NAMESPACE

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@@ -60,6 +60,7 @@ importFrom(grDevices,pdf)
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importFrom(graphics,abline)
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importFrom(graphics,arrows)
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importFrom(graphics,barplot)
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importFrom(graphics,boxplot)
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importFrom(graphics,hist)
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importFrom(graphics,legend)
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importFrom(graphics,lines)
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importFrom(stats,dnbinom)
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importFrom(stats,fitted.values)
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importFrom(stats,glm)
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importFrom(stats,lm)
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importFrom(stats,mad)
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importFrom(stats,median)
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importFrom(stats,model.matrix)
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importFrom(stats,quantile)
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importFrom(stats,quasibinomial)
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importFrom(stats,sd)
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importFrom(stats,setNames)
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importFrom(stats,var)
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importFrom(utils,capture.output)
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importFrom(utils,head)
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importFrom(utils,sessionInfo)
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importFrom(utils,write.csv)
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importFrom(utils,write.table)

R/SCONE_DEFAULTS.R

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@@ -33,7 +33,8 @@ TMM_FN = function(ei) {
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return(eo)
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}
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#' Relative log-expression (RLE; DESeq) scaling normalization wrapper function
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#' Relative log-expression (RLE; DESeq) scaling normalization wrapper
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#' function
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#' @importFrom edgeR calcNormFactors
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#' @details SCONE scaling wrapper for \code{\link[edgeR]{calcNormFactors}}).
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#' @export

R/sconeReport.R

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#'
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#' @importFrom RColorBrewer brewer.pal
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#' @importFrom rARPACK svds
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#' @importFrom graphics boxplot
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#' @importFrom utils write.csv
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#' @importFrom stats setNames var
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#' @export
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#'
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#' @return An object that represents the SCONE report app.
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stop("reshape2 package needed for sconeReport()")
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}
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if (!require("plotly", quietly = TRUE)) {
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if (!requireNamespace("plotly", quietly = TRUE)) {
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stop("plotly package needed for sconeReport()")
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}
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if (!require("visNetwork", quietly = TRUE)) {
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if (!requireNamespace("visNetwork", quietly = TRUE)) {
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stop("visNetwork package needed for sconeReport()")
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}
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if (!require("ggplot2", quietly = TRUE)) {
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if (!requireNamespace("ggplot2", quietly = TRUE)) {
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stop("ggplot2 package needed for sconeReport()")
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}
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),
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shiny::tabPanel("PCA",
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shiny::br(),
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shiny::p(paste0("This panel shows principal ",
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shiny::p(paste0("This panel shows principal ",
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"component analysis ",
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"(PCA) results",
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" on different subsets ",
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"of genes.")),
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shiny::br(),
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shiny::h6("Variance Explained (All Genes)"),
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shiny::h6("Variance Explained (All Genes)"),
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shiny::p(paste0("Use this plot",
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" to decide on the ",
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"dimensionality of the reduced",
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" spaced used for evaluation.")),
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shiny::plotOutput("plot_scree",width = "650px",
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shiny::plotOutput("plot_scree",width = "650px",
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height = "400px"),
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shiny::br(),
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shiny::h6("2D (All Genes)"),
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),
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shiny::tabPanel("QC",
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shiny::br(),
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shiny::p(paste0("This panel shows the absolute",
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shiny::p(paste0("This panel shows the absolute",
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" correlations between",
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" Principal",
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" Components (PCs) of",
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),
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shiny::tabPanel("Control Genes",
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shiny::br(),
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shiny::p(paste0("Heatmap of control genes, ",
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shiny::p(paste0("Heatmap of control genes, ",
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"colored by all",
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" three categories.")),
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shiny::br(),
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fill = cc[sort(unique(factor(strat_col())))])
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})
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output$plot3d_base <- shiny::renderPlotly({
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output$plot3d_base <- plotly::renderPlotly({
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PC1 <- PC2 <- PC3 <- NULL
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df <- setNames(data.frame(pc_obj_base()$x[,1:3]),
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c("PC1", "PC2", "PC3"))
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abs(cor(qc,pc_obj_base()$x))
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})
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output$qccorPlot <- shiny::renderPlotly({
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output$qccorPlot <- plotly::renderPlotly({
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metric <- value <- PC <- NULL
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df = reshape2::melt(cor_qc()[,1:input$dim])
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fill = cc[sort(unique(factor(strat_col())))])
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})
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output$plot3d_qc <- shiny::renderPlotly({
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output$plot3d_qc <- plotly::renderPlotly({
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if(ncol(pc_obj_qc()$x) >= 3){
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PC1 <- PC2 <- PC3 <- NULL
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df <- setNames(data.frame(pc_obj_qc()$x[,1:3]),

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