Merge pull request #59 from william-hutchison/master

Added aggregate cells function to README and vignette

Author: stemangiola

README.Rmd

@@ -48,6 +48,8 @@ Utilities | Description
 `tidy` | Add `tidySingleCellExperiment` invisible layer over a SingleCellExperiment object
 `as_tibble` | Convert cell-wise information to a `tbl_df`
 `join_features` | Add feature-wise information, returns a `tbl_df`
+`aggregate_cells` | Aggregate cell gene-transcription abundance as pseudobulk tissue
+
 
 ## Installation
 
@@ -459,3 +461,14 @@ If the dataset was not so small, and interactions could be identified, you would
 ```{r}
 tidySingleCellExperiment::pbmc_small_nested_interactions
 ```
+
+# Aggregating cells 
+
+Sometimes, it is necessary to aggregate the gene-transcript abundance from a group of cells into a single value. For example, when comparing groups of cells across different samples with fixed-effect models.
+
+In tidySingleCellExperiment, cell aggregation can be achieved using the `aggregate_cells` function.
+ 
+```{r}
+pbmc_small_tidy %>%
+ aggregate_cells(groups, assays = "counts")
+```

README.md

@@ -49,11 +49,13 @@ both Bioconductor and tidyverse worlds.
 | `ggplot2` | `ggplot` (`tidySingleCellExperiment::ggplot`) |
 | `plotly` | `plot_ly` (`tidySingleCellExperiment::plot_ly`) |
 
-| Utilities | Description |
-|-----------------|-----------------------------------------------------------------------------------|
-| `tidy` | Add `tidySingleCellExperiment` invisible layer over a SingleCellExperiment object |
-| `as_tibble` | Convert cell-wise information to a `tbl_df` |
-| `join_features` | Add feature-wise information, returns a `tbl_df` |
+| Utilities | Description |
+|------------------|-----------------------------------------------------------------------------------|
+| `tidy` | Add `tidySingleCellExperiment` invisible layer over a SingleCellExperiment object |
+| `as_tibble` | Convert cell-wise information to a `tbl_df` |
+| `join_features` | Add feature-wise information, returns a `tbl_df` |
+| `aggregate_cells`| Aggregate cell gene-transcription abundance as pseudobulk tissue |
+
 
 ## Installation
 
@@ -98,7 +100,7 @@ pbmc_small_tidy
 ```
 
  ## # A SingleCellExperiment-tibble abstraction: 80 × 17
- ## # Features=230 | Cells=80 | Assays=counts, logcounts
+ ## # [90mFeatures=230 | Cells=80 | Assays=counts, logcounts[0m
  ## .cell orig.…¹ nCoun…² nFeat…³ RNA_s…⁴ lette…⁵ groups RNA_s…⁶ file ident
  ## <chr> <fct> <dbl> <int> <fct> <fct> <chr> <fct> <chr> <fct>
  ## 1 ATGCCAGAA… Seurat… 70 47 0 A g2 0 ../d… 0 
@@ -168,7 +170,7 @@ pbmc_small_polished %>%
 ```
 
  ## # A SingleCellExperiment-tibble abstraction: 80 × 18
- ## # Features=230 | Cells=80 | Assays=counts, logcounts
+ ## # [90mFeatures=230 | Cells=80 | Assays=counts, logcounts[0m
  ## .cell sample orig.…¹ nCoun…² nFeat…³ RNA_s…⁴ lette…⁵ groups RNA_s…⁶ file 
  ## <chr> <chr> <fct> <dbl> <int> <fct> <fct> <chr> <fct> <chr>
  ## 1 ATGCCAGA… sampl… Seurat… 70 47 0 A g2 0 ../d…
@@ -290,7 +292,7 @@ pbmc_small_pca
 ```
 
  ## # A SingleCellExperiment-tibble abstraction: 80 × 18
- ## # Features=230 | Cells=80 | Assays=counts, logcounts
+ ## # [90mFeatures=230 | Cells=80 | Assays=counts, logcounts[0m
  ## .cell orig.…¹ nCoun…² nFeat…³ RNA_s…⁴ lette…⁵ groups RNA_s…⁶ file sample
  ## <chr> <fct> <dbl> <int> <fct> <fct> <chr> <fct> <chr> <chr> 
  ## 1 ATGCCAGA… Seurat… 70 47 0 A g2 0 ../d… sampl…
@@ -353,7 +355,7 @@ pbmc_small_cluster %>% select(label, everything())
 ```
 
  ## # A SingleCellExperiment-tibble abstraction: 80 × 19
- ## # Features=230 | Cells=80 | Assays=counts, logcounts
+ ## # [90mFeatures=230 | Cells=80 | Assays=counts, logcounts[0m
  ## .cell label orig.…¹ nCoun…² nFeat…³ RNA_s…⁴ lette…⁵ groups RNA_s…⁶ file 
  ## <chr> <fct> <fct> <dbl> <int> <fct> <fct> <chr> <fct> <chr>
  ## 1 ATGCCAGAA… 2 Seurat… 70 47 0 A g2 0 ../d…
@@ -503,7 +505,7 @@ pbmc_small_cell_type %>%
  ## workflow to reflect the new vocabulary (.cell)
 
  ## # A SingleCellExperiment-tibble abstraction: 80 × 23
- ## # Features=230 | Cells=80 | Assays=counts, logcounts
+ ## # [90mFeatures=230 | Cells=80 | Assays=counts, logcounts[0m
  ## cell first…¹ orig.…² nCoun…³ nFeat…⁴ RNA_s…⁵ lette…⁶ groups RNA_s…⁷ file 
  ## <chr> <chr> <fct> <dbl> <int> <fct> <fct> <chr> <fct> <chr>
  ## 1 ATGCCAG… CD4+ T… Seurat… 70 47 0 A g2 0 ../d…
@@ -757,3 +759,32 @@ tidySingleCellExperiment::pbmc_small_nested_interactions
  ## # … with 90 more rows, and abbreviated variable names ¹​receptor, ²​ligand.name,
  ## # ³​receptor.name, ⁴​destination, ⁵​interaction.type
  ## # ℹ Use `print(n = ...)` to see more rows
+
+# Aggregating cells 
+
+Sometimes, it is necessary to aggregate the gene-transcript abundance from a group of cells into a single value. For example, when comparing groups of cells across different samples with fixed-effect models.
+
+In tidySingleCellExperiment, cell aggregation can be achieved using the `aggregate_cells` function.
+ 
+``` r
+pbmc_small_tidy %>%
+ aggregate_cells(groups, assays = "counts")
+```
+
+ ## # A SummarizedExperiment-tibble abstraction: 460 × 2
+ ## # Features=230 | Samples=2 | Assays=counts
+ ## .feature .sample counts groups .aggregated_cells orig.ident file feature
+ ## <chr> <chr> <dbl> <chr> <int> <fct> <chr> <chr>
+ ## 1 ACAP1 g1 9 g1 44 SeuratProject ../data/sample1/out… ACAP1
+ ## 2 ACRBP g1 29 g1 44 SeuratProject ../data/sample1/out… ACRBP
+ ## 3 ACSM3 g1 2 g1 44 SeuratProject ../data/sample1/out… ACSM3
+ ## 4 ADAR g1 33 g1 44 SeuratProject ../data/sample1/out… ADAR
+ ## 5 AIF1 g1 209 g1 44 SeuratProject ../data/sample1/out… AIF1
+ ## 6 AKR1C3 g1 14 g1 44 SeuratProject ../data/sample1/out… AKR1C3
+ ## 7 ALOX5AP g1 19 g1 44 SeuratProject ../data/sample1/out… ALOX5AP
+ ## 8 ANXA2 g1 87 g1 44 SeuratProject ../data/sample1/out… ANXA2
+ ## 9 ARHGDIA g1 23 g1 44 SeuratProject ../data/sample1/out… ARHGDIA
+ ## 10 ASGR1 g1 9 g1 44 SeuratProject ../data/sample1/out… ASGR1
+ ## # … with 40 more rows
+ ## # ℹ Use `print(n = ...)` to see more rows
+

vignettes/introduction.Rmd

@@ -45,6 +45,7 @@ Utilities | Description
 `tidy` | Add `tidySingleCellExperiment` invisible layer over a SingleCellExperiment object
 `as_tibble` | Convert cell-wise information to a `tbl_df`
 `join_features` | Add feature-wise information, returns a `tbl_df`
+`aggregate_cells` | Aggregate cell gene-transcription abundance as pseudobulk tissue
 
 ## Installation
 
@@ -457,6 +458,17 @@ If the dataset was not so small, and interactions could be identified, you would
 tidySingleCellExperiment::pbmc_small_nested_interactions
 ```
 
+# Aggregating cells 
+
+Sometimes, it is necessary to aggregate the gene-transcript abundance from a group of cells into a single value. For example, when comparing groups of cells across different samples with fixed-effect models.
+
+In tidySingleCellExperiment, cell aggregation can be achieved using the `aggregate_cells` function.
+ 
+```{r}
+pbmc_small_tidy %>%
+ aggregate_cells(groups, assays = "counts")
+```
+
 # Session Info
 
 ```{r}