@@ -1,5 +1,5 @@

 Package: scone

-Version: 1.1.2-9001

+Version: 1.1.3

 Title: Single Cell Overview of Normalized Expression data

 Description: SCONE is an R package for comparing and ranking the performance of

 	different normalization schemes for single-cell RNA-seq and other 

@@ -60,6 +60,7 @@ importFrom(grDevices,pdf)

 importFrom(graphics,abline)

 importFrom(graphics,arrows)

 importFrom(graphics,barplot)

+importFrom(graphics,boxplot)

 importFrom(graphics,hist)

 importFrom(graphics,legend)

 importFrom(graphics,lines)

@@ -91,6 +92,7 @@ importFrom(stats,dist)

 importFrom(stats,dnbinom)

 importFrom(stats,fitted.values)

 importFrom(stats,glm)

+importFrom(stats,lm)

 importFrom(stats,mad)

 importFrom(stats,median)

 importFrom(stats,model.matrix)

@@ -101,7 +103,10 @@ importFrom(stats,prcomp)

 importFrom(stats,quantile)

 importFrom(stats,quasibinomial)

 importFrom(stats,sd)

+importFrom(stats,setNames)

+importFrom(stats,var)

 importFrom(utils,capture.output)

 importFrom(utils,head)

 importFrom(utils,sessionInfo)

+importFrom(utils,write.csv)

 importFrom(utils,write.table)

@@ -33,7 +33,8 @@ TMM_FN = function(ei) {

   return(eo)

 }

-#' Relative log-expression (RLE; DESeq) scaling normalization wrapper function

+#' Relative log-expression (RLE; DESeq) scaling normalization wrapper

+#' function

 #' @importFrom edgeR calcNormFactors

 #' @details SCONE scaling wrapper for \code{\link[edgeR]{calcNormFactors}}).

 #' @export

@@ -24,6 +24,9 @@

 #'

 #' @importFrom RColorBrewer brewer.pal

 #' @importFrom rARPACK svds

+#' @importFrom graphics boxplot

+#' @importFrom utils write.csv

+#' @importFrom stats setNames var

 #' @export

 #'

 #' @return An object that represents the SCONE report app.

@@ -66,15 +69,15 @@ sconeReport = function(x, methods,

     stop("reshape2 package needed for sconeReport()")

   }

-  if (!require("plotly", quietly = TRUE)) {

+  if (!requireNamespace("plotly", quietly = TRUE)) {

     stop("plotly package needed for sconeReport()")

   }

-  if (!require("visNetwork", quietly = TRUE)) {

+  if (!requireNamespace("visNetwork", quietly = TRUE)) {

     stop("visNetwork package needed for sconeReport()")

   }

-  if (!require("ggplot2", quietly = TRUE)) {

+  if (!requireNamespace("ggplot2", quietly = TRUE)) {

     stop("ggplot2 package needed for sconeReport()")

   }

@@ -223,18 +226,18 @@ sconeReport = function(x, methods,

                             ),

                             shiny::tabPanel("PCA",

                                      shiny::br(),

-                                     shiny::p(paste0("This panel shows principal ",

+                                shiny::p(paste0("This panel shows principal ",

                                               "component analysis ",

                                               "(PCA) results",

                                               " on different subsets ",

                                               "of genes.")),

                                      shiny::br(),

-                                     shiny::h6("Variance Explained (All Genes)"),

+                                  shiny::h6("Variance Explained (All Genes)"),

                                      shiny::p(paste0("Use this plot",

                                               " to decide on the ",

                                               "dimensionality of the reduced",

                                               " spaced used for evaluation.")),

-                                     shiny::plotOutput("plot_scree",width = "650px",

+                                shiny::plotOutput("plot_scree",width = "650px",

                                                 height = "400px"),

                                      shiny::br(),

                                      shiny::h6("2D (All Genes)"),

@@ -264,7 +267,7 @@ sconeReport = function(x, methods,

                             ),

                             shiny::tabPanel("QC",

                                      shiny::br(),

-                                     shiny::p(paste0("This panel shows the absolute",

+                              shiny::p(paste0("This panel shows the absolute",

                                               " correlations between",

                                               " Principal",

                                               " Components (PCs) of",

@@ -326,7 +329,7 @@ sconeReport = function(x, methods,

                             ),

                             shiny::tabPanel("Control Genes",

                                      shiny::br(),

-                                     shiny::p(paste0("Heatmap of control genes, ",

+                                  shiny::p(paste0("Heatmap of control genes, ",

                                               "colored by all",

                                               " three categories.")),

                                      shiny::br(),

@@ -56,6 +56,7 @@

 #' @importFrom cluster silhouette

 #' @importFrom rARPACK svds

 #' @importFrom matrixStats rowMedians colMedians colIQRs

+#' @importFrom stats lm

 #'

 #' @export

 #'

@@ -269,7 +270,8 @@ score_matrix <- function(expr,

       # Max cor with quality factors.

       if (!is.null(qc_factors)) {

         EXP_QC_COR <-

-          EXP_QC_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2, function(y) {

+          EXP_QC_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2,

+                                                      function(y) {

             lm(y ~ qc_factors[is_cond,])$residual

           })) ^ 2) / sum(scale(proj[is_cond,], scale = FALSE) ^ 2))

       }

@@ -277,7 +279,8 @@ score_matrix <- function(expr,

       # Max cor with UV factors.

       if (!is.null(uv_factors)) {

         EXP_UV_COR  <-

-          EXP_UV_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2, function(y) {

+          EXP_UV_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2,

+                                                      function(y) {

             lm(y ~ uv_factors[is_cond,])$residual

           })) ^ 2) / sum(scale(proj[is_cond,], scale = FALSE) ^ 2))

       }

@@ -285,7 +288,8 @@ score_matrix <- function(expr,

       # Max cor with WV factors.

       if (!is.null(wv_factors)) {

         EXP_WV_COR <-

-          EXP_WV_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2, function(y) {

+          EXP_WV_COR + cond_w * (1 - sum(unlist(apply(proj[is_cond,], 2,

+                                                      function(y) {

             lm(y ~ wv_factors[is_cond,])$residual

           })) ^ 2) / sum(scale(proj[is_cond,], scale = FALSE) ^ 2))

       }

@@ -296,8 +296,8 @@ impute_null <- function(expression,impute_args) {

 #'   \item{p_nodrop}{ 1 - the probability P(drop|Y), useful as weights in 

 #'   weighted PCA} \item{expected_state}{ the expected

 #'   value E[Z] (1 = "on")} \item{loglik}{ the log-likelihood} 

-#'   \item{convergence}{for all genes, 0 if the algorithm converged and 1 if maxiter was 

-#'   reached} }

+#'   \item{convergence}{for all genes, 0 if the algorithm converged and

+#'   1 if maxiter was reached} }

 #'   

 #' @examples

 #' mat <- matrix(rpois(1000, lambda = 3), ncol=10)

@@ -1,3 +1,10 @@

+Changes in version 1.1.3 (2018-10-19)

+========================

+

+* Modified COR scores to reflect R^2 for regression on UV/WV/QC rather than max correlation.

+* Bug fix for shiny report.

+* Updated vignette.

+

 Changes in version 1.1.2 (2017-7-3)

 ========================

@@ -2,7 +2,8 @@

 % Please edit documentation in R/SCONE_DEFAULTS.R

 \name{DESEQ_FN}

 \alias{DESEQ_FN}

-\title{Relative log-expression (RLE; DESeq) scaling normalization wrapper function}

+\title{Relative log-expression (RLE; DESeq) scaling normalization wrapper

+function}

 \usage{

 DESEQ_FN(ei)

 }

@@ -13,7 +14,8 @@ DESEQ_FN(ei)

 RLE normalized matrix.

 }

 \description{

-Relative log-expression (RLE; DESeq) scaling normalization wrapper function

+Relative log-expression (RLE; DESeq) scaling normalization wrapper

+function

 }

 \details{

 SCONE scaling wrapper for \code{\link[edgeR]{calcNormFactors}}).

@@ -40,8 +40,8 @@ a list with the following elements: \itemize{ \item{W}{ coefficients

   \item{p_nodrop}{ 1 - the probability P(drop|Y), useful as weights in 

   weighted PCA} \item{expected_state}{ the expected

   value E[Z] (1 = "on")} \item{loglik}{ the log-likelihood} 

-  \item{convergence}{for all genes, 0 if the algorithm converged and 1 if maxiter was 

-  reached} }

+  \item{convergence}{for all genes, 0 if the algorithm converged and

+  1 if maxiter was reached} }

 }

 \description{

 This function implements Newton's method for solving zero of