Merge pull request #54 from broadinstitute/devel

Devel

Former-commit-id: b7c3cf5
Former-commit-id: e2177ca

Author: GeorgescuC

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: infercnv
 Type: Package
 Title: Infer Copy Number Variation from Single-Cell RNA-Seq Data
-Version: 0.8
+Version: 0.8.1
 Date: 2017-05-25
 Authors@R: c( person("Timothy", "Tickle", email = "[email protected]", role = c("aut", "cre")), person("Itay", "Tirosh", email = "[email protected]", role = "aut"), person("Christophe", "Georgescu", email = "[email protected]", role = "aut"), person("Maxwell", "Brown", email = "[email protected]", role = "aut"), person("Brian", "Haas", email = "[email protected]", role = "aut")) 
 Author: Timothy Tickle [aut, cre], Itay Tirosh [aut], Christophe Georgescu [aut], Maxwell Brown [aut], Brian Haas [aut]

R/inferCNV.R

@@ -377,3 +377,23 @@ validate_infercnv_obj <- function(infercnv_obj) {
 
 }
 
+
+get_cell_name_by_grouping <- function(infercnv_obj) {
+
+    cell_name_groupings = list()
+    
+    groupings = c(infercnv_obj@reference_grouped_cell_indices, infercnv_obj@observation_grouped_cell_indices)
+
+    for (group_name in names(groupings)) {
+
+        cell_names = colnames(infercnv_obj@expr.data[, groupings[[ group_name ]] ] )
+
+        cell_name_groupings[[ group_name ]] = cell_names
+
+    }
+
+    return(cell_name_groupings)
+}
+
+
+

R/inferCNV_heatmap.R

@@ -145,7 +145,8 @@ plot_cnv <- function(infercnv_obj,
 
     # Row separation based on reference
     ref_idx <- unlist(infercnv_obj@reference_grouped_cell_indices)
-
+    ref_idx = ref_idx[order(ref_idx)]
+        
     # Column seperation by contig and label axes with only one instance of name
     contig_tbl <- table(contigs)[unique_contigs]
     col_sep <- cumsum(contig_tbl)
@@ -176,13 +177,14 @@ plot_cnv <- function(infercnv_obj,
         counter <- counter + 1
     }
     # restrict to just the obs indices
-    obs_annotations_groups <- obs_annotations_groups[ unlist(obs_index_groupings) ]
-    
 
+    obs_annotations_groups <- obs_annotations_groups[-ref_idx]
+    
     grouping_key_coln[1] <- floor(123/(max(nchar(obs_annotations_names)) + 4))  ## 123 is the max width in number of characters, 4 is the space taken by the color box itself and the spacing around it
     if (grouping_key_coln[1] < 1) {
         grouping_key_coln[1] <- 1
     }
+
     name_ref_groups = names(infercnv_obj@reference_grouped_cell_indices)
     grouping_key_coln[2] <- floor(123/(max(nchar(name_ref_groups)) + 4))  ## 123 is the max width in number of characters, 4 is the space taken by the color box itself and the spacing around it
     if (grouping_key_coln[2] < 1) {
@@ -195,7 +197,7 @@ plot_cnv <- function(infercnv_obj,
     # Calculate how much bigger the output needs to be to accodomate for the grouping key
     grouping_key_height <- c((grouping_key_rown[2] + 2) * 0.175, (grouping_key_rown[1] + 3) * 0.175)
 
-                                        # Rows observations, Columns CHR
+    # Rows observations, Columns CHR
     if (! is.na(output_format)) {
         if (output_format == "pdf") {
             pdf(paste(out_dir, paste(output_filename, ".pdf", sep=""), sep="/"),
@@ -219,7 +221,7 @@ plot_cnv <- function(infercnv_obj,
     ## They are more informative anyway
     obs_data <- infercnv_obj@expr.data
     if (!is.null(ref_idx)){
-        obs_data <- plot_data[, -1 * ref_idx, drop=FALSE]
+        obs_data <- plot_data[, -ref_idx, drop=FALSE]
         if (ncol(obs_data) == 1) {
             # hack for dealing with single entries
             plot_data <- cbind(obs_data, obs_data)
@@ -244,7 +246,7 @@ plot_cnv <- function(infercnv_obj,
         current_grp_idx <- current_grp_idx + 1
     }
     ref_groups <- updated_ref_groups
-
+    
     nb_breaks <- 16
     breaksList_t <-
         seq(min(min(obs_data_t, na.rm=TRUE), min(ref_data_t, na.rm=TRUE)),

example/example.Rmd

@@ -292,8 +292,10 @@ plot_cnv(infercnv_obj,
 
 ```{r}
 knitr::include_graphics("infercnv.finalized_view.png")
+```
+
 And that's it. You can experiment with each step to fine-tune your data exploration.  See the documentation for uploading the resulting data matrix into the Next Generation Clustered Heatmap Viewer for more interactive exploration of the infercnv-processed data:
 <https://github.com/broadinstitute/inferCNV/wiki/Next-Generation-Clustered-Heat-Map>
 
 
-```
+

scripts/inferCNV_utils.R

@@ -1,9 +1,9 @@
 
 library(tidyverse)
-
+library(futile.logger)
 
 # plot expression density by chromosome for each observation group, reference groups are shown as single 'normal' group.
-plot_density_by_chr <- function(infercnv_obj, pdf_filename=NULL, exclude_range=NULL, chrs=NULL) {
+plot_density_by_chr <- function(infercnv_obj, pdf_filename=NULL, exclude_range=NULL, include_range = NULL, chrs=NULL) {
 
     ref_group_cell_indices = infercnv:::get_reference_grouped_cell_indices(infercnv_obj)
 
@@ -15,6 +15,9 @@ plot_density_by_chr <- function(infercnv_obj, pdf_filename=NULL, exclude_range=N
     if (! is.null(pdf_filename)) {
         pdf(pdf_filename)
     }
+
+
+    chr_expr_vals = list()
 
     for (chr in chrs) {
 
@@ -40,16 +43,25 @@ plot_density_by_chr <- function(infercnv_obj, pdf_filename=NULL, exclude_range=N
             excl_range_right = exclude_range[2]
 
             df = df %>% filter(vals < excl_range_left | vals > excl_range_right)
+        } else if (! is.null(include_range)) {
+            include_range_left = include_range[1]
+            include_range_right = include_range[2]
+
+            df = df %>% filter(vals >= include_range_left & vals <= include_range_right)
         }
-        
+                
         p = df %>% ggplot(aes(vals, fill=class)) + geom_density(alpha=0.3) + scale_y_continuous(trans='log10', limits=c(1,NA)) + ggtitle(chr)
         plot(p)
+
+        chr_expr_vals[[ chr ]] = df
 
     }
 
     if (! is.null(pdf_filename)) {
         dev.off()
     }
+
+    return(chr_expr_vals)
 
 }
 
@@ -87,6 +99,8 @@ plot_dist_counts_expr_genes_by_chr <- function(infercnv_obj, pdf_filename=NULL,
     if (! is.null(pdf_filename)) {
         pdf(pdf_filename)
     }
+
+    gene_counts_dfs = list()
 
     for (chr in chrs) {
         gene_idx = which(infercnv_obj@gene_order$chr == chr)
@@ -104,11 +118,15 @@ plot_dist_counts_expr_genes_by_chr <- function(infercnv_obj, pdf_filename=NULL,
         }
         p = df %>% ggplot(aes(gene_counts, fill=class)) + geom_density(alpha=0.3) + ggtitle(chr)
         plot(p)
+
+        gene_counts_dfs[[ chr ]] = df
     }
 
     if (! is.null(pdf_filename)) {
         dev.off()
     }
+
+    return(gene_counts_dfs)
 }
 
 
@@ -133,7 +151,9 @@ compare_gene_expr_means_by_group_pair <- function(infercnv_obj, groupA, groupB,
     groupA.gene_mean = rowMeans(groupA.expr.data)
     groupB.gene_mean = rowMeans(groupB.expr.data)
 
-    plot(groupA.gene_mean, groupB.gene_mean)
+    #plot(groupA.gene_mean, groupB.gene_mean)
+    smoothScatter(groupA.gene_mean, groupB.gene_mean)
+    abline(a=0, b=1, col='magenta')
 
     df=data.frame(groupA=groupA.gene_mean, groupB=groupB.gene_mean)