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Merge pull request #29 from stemangiola/examples
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Update readme with get_seurat() and genes argument
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@stemangiola
stemangiola authored Nov 7, 2022
2 parents 886c159 + c3e77b1 commit f2d26db
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31 changes: 29 additions & 2 deletions README.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@ output: github_document
always_allow_html: true
---

Load Metadata
Load the package

```{r, message=FALSE, warning=FALSE}
library(HCAquery)
Expand All @@ -16,7 +16,7 @@ options("restore_SingleCellExperiment_show" = TRUE)
```

Load the data
Load the metadata

```{r}
get_metadata()
Expand Down Expand Up @@ -65,4 +65,31 @@ sce =
sce
```

Extract only a subset of genes:

```{r}
get_metadata() |>
filter(
ethnicity == "African" &
assay %LIKE% "%10x%" &
tissue == "lung parenchyma" &
cell_type %LIKE% "%CD4%"
) |>
get_SingleCellExperiment(genes = "PUM1")
```

Extract the counts as a Seurat object:

```{r}
get_metadata() |>
filter(
ethnicity == "African" &
assay %LIKE% "%10x%" &
tissue == "lung parenchyma" &
cell_type %LIKE% "%CD4%"
) |>
get_seurat()
```



111 changes: 83 additions & 28 deletions README.md
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@@ -1,7 +1,7 @@
HCAquery
================

Load Metadata
Load the package

``` r
library(HCAquery)
Expand All @@ -12,33 +12,33 @@ library(tidySingleCellExperiment)
options("restore_SingleCellExperiment_show" = TRUE)
```

Load the data
Load the metadata

``` r
get_metadata()
```

## # Source: table<metadata> [?? x 52]
## # Database: sqlite 3.39.2 [/vast/projects/RCP/human_cell_atlas/metadata.sqlite]
## .cell .sample .samp…¹ assay assay…² cell_…³ cell_…⁴ devel…⁵ devel…⁶ disease
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 2 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 3 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… lumina… CL:000… 31-yea… HsapDv… normal
## 4 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… lumina… CL:000… 31-yea… HsapDv… normal
## 5 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 6 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 7 AAACCT… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 8 AAACGG… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## 9 AAACGG… 5f20d7… D17PrP… 10x … EFO:00… lumina… CL:000… 31-yea… HsapDv… normal
## 10 AAACGG… 5f20d7… D17PrP… 10x … EFO:00… basal … CL:000… 31-yea… HsapDv… normal
## # … with more rows, 42 more variables: disease_ontology_term_id <chr>,
## # ethnicity <chr>, ethnicity_ontology_term_id <chr>, file_id <chr>,
## # is_primary_data.x <chr>, organism <chr>, organism_ontology_term_id <chr>,
## # sample_placeholder <chr>, sex <chr>, sex_ontology_term_id <chr>,
## # tissue <chr>, tissue_ontology_term_id <chr>, dataset_id <chr>,
## # collection_id <chr>, cell_count <int>, dataset_deployments <chr>,
## # is_primary_data.y <chr>, is_valid <int>, linked_genesets <int>, …
## # Source: table<metadata> [?? x 56]
## # Database: sqlite 3.39.3 [/vast/projects/RCP/human_cell_atlas/metadata.sqlite]
## .cell sampl…¹ .sample .samp…² assay assay…³ file_…⁴ cell_…⁵ cell_…⁶ devel…⁷
## <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 2 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 3 AAACCT… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
## 4 AAACCT… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
## 5 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 6 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 7 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 8 AAACGG… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## 9 AAACGG… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
## 10 AAACGG… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
## # … with more rows, 46 more variables:
## # development_stage_ontology_term_id <chr>, disease <chr>,
## # disease_ontology_term_id <chr>, ethnicity <chr>,
## # ethnicity_ontology_term_id <chr>, file_id <chr>, is_primary_data.x <chr>,
## # organism <chr>, organism_ontology_term_id <chr>, sample_placeholder <chr>,
## # sex <chr>, sex_ontology_term_id <chr>, tissue <chr>,
## # tissue_ontology_term_id <chr>, tissue_harmonised <chr>, age_days <dbl>, …

Explore the HCA content

Expand All @@ -50,7 +50,7 @@ get_metadata() |>
```

## # Source: SQL [?? x 2]
## # Database: sqlite 3.39.2 [/vast/projects/RCP/human_cell_atlas/metadata.sqlite]
## # Database: sqlite 3.39.3 [/vast/projects/RCP/human_cell_atlas/metadata.sqlite]
## # Ordered by: desc(n)
## tissue n
## <chr> <int>
Expand Down Expand Up @@ -97,8 +97,8 @@ sce
## rowData names(0):
## colnames(1571): ACAGCCGGTCCGTTAA_F02526 GGGAATGAGCCCAGCT_F02526 ...
## TACAACGTCAGCATTG_SC84 CATTCGCTCAATACCG_F02526
## colData names(51): .sample .sample_name ... cell_annotation_azimuth_l2
## cell_annotation_blueprint_singler
## colData names(55): sample_id_db .sample ... n_cell_type_in_tissue
## n_tissue_in_cell_type
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):
Expand Down Expand Up @@ -135,8 +135,63 @@ sce
## rowData names(0):
## colnames(1571): ACAGCCGGTCCGTTAA_F02526 GGGAATGAGCCCAGCT_F02526 ...
## TACAACGTCAGCATTG_SC84 CATTCGCTCAATACCG_F02526
## colData names(51): .sample .sample_name ... cell_annotation_azimuth_l2
## cell_annotation_blueprint_singler
## colData names(55): sample_id_db .sample ... n_cell_type_in_tissue
## n_tissue_in_cell_type
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):

Extract only a subset of genes:

``` r
get_metadata() |>
filter(
ethnicity == "African" &
assay %LIKE% "%10x%" &
tissue == "lung parenchyma" &
cell_type %LIKE% "%CD4%"
) |>
get_SingleCellExperiment(genes = "PUM1")
```

## Reading 1 files.

## .

## class: SingleCellExperiment
## dim: 1 1571
## metadata(0):
## assays(1): counts
## rownames(1): PUM1
## rowData names(0):
## colnames(1571): ACAGCCGGTCCGTTAA_F02526 GGGAATGAGCCCAGCT_F02526 ...
## TACAACGTCAGCATTG_SC84 CATTCGCTCAATACCG_F02526
## colData names(55): sample_id_db .sample ... n_cell_type_in_tissue
## n_tissue_in_cell_type
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):

Extract the counts as a Seurat object:

``` r
get_metadata() |>
filter(
ethnicity == "African" &
assay %LIKE% "%10x%" &
tissue == "lung parenchyma" &
cell_type %LIKE% "%CD4%"
) |>
get_seurat()
```

## Reading 1 files.

## .

## Warning: Feature names cannot have underscores ('_'), replacing with dashes
## ('-')

## An object of class Seurat
## 60661 features across 1571 samples within 1 assay
## Active assay: originalexp (60661 features, 0 variable features)

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