scone_1.1.3

YosefLab · Oct 19, 2017 · af3da30 · af3da30
1 parent 9b3474b
commit af3da30
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Showing 9 changed files with 41 additions and 19 deletions.
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -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 

diff --git a/NAMESPACE b/NAMESPACE
@@ -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)
diff --git a/R/SCONE_DEFAULTS.R b/R/SCONE_DEFAULTS.R
@@ -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

diff --git a/R/sconeReport.R b/R/sconeReport.R
@@ -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(),

diff --git a/R/scone_eval.R b/R/scone_eval.R
@@ -56,6 +56,7 @@
 #' @importFrom cluster silhouette
 #' @importFrom rARPACK svds
 #' @importFrom matrixStats rowMedians colMedians colIQRs
+#' @importFrom stats lm
 #'
 #' @export
 #'
@@ -269,23 +270,26 @@ 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))
       }
 
       # 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))
       }
 
       # 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))
       }

diff --git a/R/ziber.R b/R/ziber.R
@@ -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)

diff --git a/inst/NEWS b/inst/NEWS
@@ -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)
 ========================
 

diff --git a/man/DESEQ_FN.Rd b/man/DESEQ_FN.Rd
diff --git a/man/fast_estimate_ziber.Rd b/man/fast_estimate_ziber.Rd