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Added aggregate cells function to README and vignette #59

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Mar 24, 2023
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Added aggregate cells function to README and vignette #59

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e2b1f7f
Added aggregate cells function to README and vignette
william-hutchison Mar 23, 2023
4ba2d8c
Fixed a typo
william-hutchison Mar 23, 2023
f42f5f0
Updated aggregate cells function description
william-hutchison Mar 24, 2023
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13 changes: 13 additions & 0 deletions README.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -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

Expand Down Expand Up @@ -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")
```
51 changes: 41 additions & 10 deletions README.md
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Expand Up @@ -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

Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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…
Expand Down Expand Up @@ -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…
Expand Down Expand Up @@ -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…
Expand Down Expand Up @@ -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…
Expand Down Expand Up @@ -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

12 changes: 12 additions & 0 deletions vignettes/introduction.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -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

Expand Down Expand Up @@ -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}
Expand Down