update ggpavis

tidyomics · May 19, 2024 · 161135d · 161135d
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -60,7 +60,12 @@ Suggests:
     rmarkdown,
     pkgdown
 Biarch: true
-Remotes: lmweber/ggspavis
+Remotes: 
+    lmweber/ggspavis,
+    stemangiola/tidySummarizedExperiment,
+    stemangiola/tidySpatialExperiment,
+    stemangiola/tidybulk,
+    stemangiola/tidygate
 URL: https://tidyomics.github.io/tidySpatialWorkshop2024
 BugReports: https://github.com/tidyomics/tidySpatialWorkshop2024/issues/new/choose
 VignetteBuilder: knitr

diff --git a/vignettes/Session_1_sequencing_assays.Rmd b/vignettes/Session_1_sequencing_assays.Rmd
@@ -522,15 +522,16 @@ Those two clusters group the white matter from the rest of the layers.
 
 ```{r, fig.width=7, fig.height=8}
 ## Plot in tissue map
-ggspavis::plotSpots(spatial_data, annotate = "label") + scale_color_brewer(palette = "Paired")
+ggspavis::plotSpots(spatial_data, annotate = "label") + 
+  scale_color_brewer(palette = "Paired")
 ```
 
 As for comparison, we show the manually annotated regions. We can see that while the single cell style clustering catchers, the overall tissue, architecture, a lot of details are not retrieved. We clusters cannot faithfully recapitulate the tissue morphology. However, they might represent specific cell types within morphological regions.
 
 ```{r, fig.width=7, fig.height=8}
 ## Plot ground truth in tissue map
-ggspavis::plotSpots(spatial_data, annotate = "spatialLIBD", 
-          palette = "libd_layer_colors")
+ggspavis::plotSpots(spatial_data, annotate = "spatialLIBD") +
+  scale_color_manual(values = libd_layer_colors |> str_remove("ayer")) +
 
 ```
 
@@ -691,16 +692,16 @@ pal <- c(
 )
 
 plot_bank_smooth <- lapply(spatial_data_list, function(x) {
-  plotSpots(x, annotate = sprintf("%s_smooth", "clust_M0_lam0.2_k50_res0.7"), pal = pal) +
+  ggspavis::plotSpots(x, annotate = sprintf("%s_smooth", "clust_M0_lam0.2_k50_res0.7"), pal = pal) +
     theme(legend.position = "none") +
     labs(title = "BANKSY clusters")
 })
 
 
 plot_grid(plotlist = plot_bank_smooth, ncol = 3, byrow = TRUE)
 
-plotSpots(spatial_data, annotate = "spatialLIBD", 
-          palette = "libd_layer_colors") +
+ggspavis::plotSpots(spatial_data, annotate = "spatialLIBD") +
+    scale_color_manual(values = libd_layer_colors |> str_remove("ayer")) +
   theme(legend.position = "none") +
   labs(title = "spatialLIBD regions")
 ```
@@ -720,7 +721,7 @@ We have applied cluster smoothing using `smoothLabels`. How much do you think th
 spe_joint <- do.call(cbind, spatial_data_list)
 
 
- plotSpots(spe_joint, annotate = sprintf("%s", "clust_M0_lam0.2_k50_res0.7"), size = 0.8, pal = pal) +
+ ggspavis::plotSpots(spe_joint, annotate = sprintf("%s", "clust_M0_lam0.2_k50_res0.7"), size = 0.8, pal = pal) +
     theme(legend.position = "none") +
     labs(title = "BANKSY clusters")
 
@@ -981,12 +982,12 @@ is_endothelial_oligodendrocytes = mat_df$endothelial_cell >0.1 & mat_df$oligoden
 spatial_data$is_endothelial_leptomeningeal = is_endothelial_leptomeningeal
 spatial_data$is_endothelial_oligodendrocyte = is_endothelial_oligodendrocytes
 
-plotSpots(spatial_data, annotate = "is_endothelial_leptomeningeal") +
+ggspavis::plotSpots(spatial_data, annotate = "is_endothelial_leptomeningeal") +
   scale_color_manual(values = c("TRUE"= "red", "FALSE" = "grey"))
 theme(legend.position = "none") +
   labs(title = "endothelial + leptomeningeal")
 
-plotSpots(spatial_data, annotate = "is_endothelial_oligodendrocyte") +
+ggspavis::plotSpots(spatial_data, annotate = "is_endothelial_oligodendrocyte") +
   scale_color_manual(values = c("TRUE"= "blue", "FALSE" = "grey"))
 theme(legend.position = "none") +
   labs(title = "endothelial + oligodendrocyte")

diff --git a/vignettes/Session_2_Tidy_spatial_analyses.Rmd b/vignettes/Session_2_Tidy_spatial_analyses.Rmd
@@ -263,10 +263,8 @@ We can visualise the gating
 spatial_data |> 
   
   # Plot our gate
-  plotSpots(
-    annotate = ".gate", 
-    palette = "libd_layer_colors"
-    ) +
+  ggspavis::plotSpots(annotate = ".gate") +
+    scale_color_manual(values = libd_layer_colors |> str_remove("ayer")) +
   labs(title = ".gate regions")
   
 ```
@@ -507,10 +505,8 @@ Let’s visualise the regions that spatialLIBD labelled across three Visium 10X
 
 ```{r, fig.width=7, fig.height=8}
 spatial_data_filtered |> 
-  plotSpots(
-    annotate = "spatialLIBD", 
-    palette = "libd_layer_colors"
-    ) +
+  ggspavis::plotSpots(annotate = "spatialLIBD") +
+    scale_color_manual(values = libd_layer_colors |> str_remove("ayer")) +
   theme(legend.position = "none") +
   labs(title = "spatialLIBD regions")
 ```

diff --git a/vignettes/Session_3_imaging_assays.Rmd b/vignettes/Session_3_imaging_assays.Rmd
@@ -273,8 +273,9 @@ Plot ground truth in tissue map
 
 tx_spe_sample_1 |> 
   mutate(in_tissue = TRUE) |> 
-  plotSpots(annotate = "region", 
-          palette = colorRampPalette( brewer.pal(9,"Set1") )(150) 
+  ggspavis::plotSpots(
+    annotate = "region", 
+    palette = colorRampPalette( brewer.pal(9,"Set1") )(150) 
         ) + 
   guides(color = "none")