diff --git a/DESCRIPTION b/DESCRIPTION index 3b490fe..2431ba5 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: pagoda2 Title: Single Cell Analysis and Differential Expression -Version: 1.0.7 +Version: 1.0.8 Authors@R: c(person("Nikolas","Barkas", email="nikolas_barkas@hms.harvard.edu", role="aut"), person("Viktor", "Petukhov", email="viktor.s.petuhov@ya.ru", role="aut"), person("Peter", "Kharchenko", email = "peter_kharchenko@hms.harvard.edu", role = "aut"), person("Simon", "Steiger", email = "simon.steiger@gmail.com", role = "ctb"), person("Evan", "Biederstedt", email="evan.biederstedt@gmail.com", role=c("cre", "aut"))) Description: Analyzing and interactively exploring large-scale single-cell RNA-seq datasets. 'pagoda2' primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. 'pagoda2' was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos, . This package interacts with data available through the 'p2data' package, which is available in a 'drat' repository. To access this data package, see the instructions at . The size of the 'p2data' package is approximately 6 MB. License: GPL-3 diff --git a/README.md b/README.md index 9cfd3ef..2073611 100644 --- a/README.md +++ b/README.md @@ -101,5 +101,5 @@ If you find `pagoda2` useful for your publication, please cite: ``` Nikolas Barkas, Viktor Petukhov, Peter Kharchenko and Evan Biederstedt (2021). pagoda2: Single Cell Analysis and Differential -Expression. R package version 1.0.7. +Expression. R package version 1.0.8. ``` diff --git a/doc/pagoda2.walkthrough.R b/doc/pagoda2.walkthrough.R index 8518561..e9d01fb 100644 --- a/doc/pagoda2.walkthrough.R +++ b/doc/pagoda2.walkthrough.R @@ -102,7 +102,7 @@ r$plotEmbedding(type='PCA', show.legend=FALSE, mark.groups=TRUE, min.cluster.siz ## ---- fig.height=6, fig.width=6----------------------------------------------- -r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50,verbose=FALSE) +r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50, verbose=FALSE) r$plotEmbedding(type='PCA', embeddingType='tSNE', show.legend=FALSE, mark.groups=TRUE, min.cluster.size=1, shuffle.colors=FALSE, font.size=3, alpha=0.3, title='clusters (tSNE)', plot.theme=theme_bw() + theme(plot.title = element_text(hjust = 0.5))) diff --git a/doc/pagoda2.walkthrough.Rmd b/doc/pagoda2.walkthrough.Rmd index db4626d..e563ea1 100644 --- a/doc/pagoda2.walkthrough.Rmd +++ b/doc/pagoda2.walkthrough.Rmd @@ -193,7 +193,7 @@ r$plotEmbedding(type='PCA', show.legend=FALSE, mark.groups=TRUE, min.cluster.siz We next can construct and plot a tSNE embedding. (This can take some time to complete.) ```{r, fig.height=6, fig.width=6} -r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50,verbose=FALSE) +r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50, verbose=FALSE) r$plotEmbedding(type='PCA', embeddingType='tSNE', show.legend=FALSE, mark.groups=TRUE, min.cluster.size=1, shuffle.colors=FALSE, font.size=3, alpha=0.3, title='clusters (tSNE)', plot.theme=theme_bw() + theme(plot.title = element_text(hjust = 0.5))) ``` diff --git a/doc/pagoda2.walkthrough.html b/doc/pagoda2.walkthrough.html index 60078aa..5b2be5e 100644 --- a/doc/pagoda2.walkthrough.html +++ b/doc/pagoda2.walkthrough.html @@ -475,7 +475,7 @@

Part 2: Analysing Data with Pagoda2

We next can construct and plot a tSNE embedding. (This can take some time to complete.)

-
r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50,verbose=FALSE)
+
r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50, verbose=FALSE)
 r$plotEmbedding(type='PCA', embeddingType='tSNE', show.legend=FALSE, mark.groups=TRUE, min.cluster.size=1, shuffle.colors=FALSE, font.size=3, alpha=0.3, title='clusters (tSNE)', plot.theme=theme_bw() + theme(plot.title = element_text(hjust = 0.5)))
 

 
diff --git a/doc/pagoda2.walkthrough.md b/doc/pagoda2.walkthrough.md
index 1b588cc..214bc30 100644
--- a/doc/pagoda2.walkthrough.md
+++ b/doc/pagoda2.walkthrough.md
@@ -327,7 +327,7 @@ r$plotEmbedding(type='PCA', show.legend=FALSE, mark.groups=TRUE, min.cluster.siz
 We next can construct and plot a tSNE embedding. (This can take some time to complete.)
 
 ```r
-r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50,verbose=FALSE)
+r$getEmbedding(type='PCA', embeddingType='tSNE', perplexity=50, verbose=FALSE)
 r$plotEmbedding(type='PCA', embeddingType='tSNE', show.legend=FALSE, mark.groups=TRUE, min.cluster.size=1, shuffle.colors=FALSE, font.size=3, alpha=0.3, title='clusters (tSNE)', plot.theme=theme_bw() + theme(plot.title = element_text(hjust = 0.5)))
 ```
 
diff --git a/inst/rookServerDocs/js/aspectsTableViewer.js b/inst/rookServerDocs/js/aspectsTableViewer.js
index 327b438..3a83b39 100644
--- a/inst/rookServerDocs/js/aspectsTableViewer.js
+++ b/inst/rookServerDocs/js/aspectsTableViewer.js
@@ -108,7 +108,7 @@ aspectsTableViewer.prototype.generateTables = function() {
             tooltip: 'Export Selected',
             handler: function(){
               var grid = Ext.getCmp('genesetsAspectTable');
-              var csvContent = "data:text/csv;charset=utf-8\n";
+              var csvContent = "data:text/csv; charset=utf-8,";
 
               var columns = grid.columnManager.columns;
               var columnsCount = columns.length;
@@ -117,15 +117,9 @@ aspectsTableViewer.prototype.generateTables = function() {
                       csvContent += columns[i].text + ",";
                   }
               }
-              csvContent = csvContent.substring(0, csvContent.length-1);
+              csvContent = csvContent.substring(0, csvContent.length - 1);
               csvContent += "\r";
 
-              for (var j = 0; j -1;
 
@@ -235,7 +228,7 @@ aspectsTableViewer.prototype.generateTables = function() {
 
           for (var i = 0; i < rowsCount; i++) {
               var row = rows[i].data;
-              for (var j = 0; j