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change name in tests and vignette
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‎README.Rmd‎

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@@ -169,7 +169,7 @@ get_metadata() |>
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# Filter and subset
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filter(cell_type_harmonised=="nk") |>
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select(.cell, file_id_db, disease, file_id, tissue_harmonised) |>
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select(cell_, file_id_db, disease, file_id, tissue_harmonised) |>
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# Get counts per million for NCAM1 gene
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get_SingleCellExperiment(assays = "cpm", features = "NCAM1") |>
@@ -201,11 +201,11 @@ Dataset-specific columns (definitions available at cellxgene.cziscience.com)
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Sample-specific columns (definitions available at cellxgene.cziscience.com)
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`.sample`, `.sample_name`, `age_days`, `assay`, `assay_ontology_term_id`, `development_stage`, `development_stage_ontology_term_id`, `ethnicity`, `ethnicity_ontology_term_id`, `experiment___`, `organism`, `organism_ontology_term_id`, `sample_placeholder`, `sex`, `sex_ontology_term_id`, `tissue`, `tissue_harmonised`, `tissue_ontology_term_id`, `disease`, `disease_ontology_term_id`, `is_primary_data.x`
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`sample_`, `sample_name`, `age_days`, `assay`, `assay_ontology_term_id`, `development_stage`, `development_stage_ontology_term_id`, `ethnicity`, `ethnicity_ontology_term_id`, `experiment___`, `organism`, `organism_ontology_term_id`, `sample_placeholder`, `sex`, `sex_ontology_term_id`, `tissue`, `tissue_harmonised`, `tissue_ontology_term_id`, `disease`, `disease_ontology_term_id`, `is_primary_data.x`
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Cell-specific columns (definitions available at cellxgene.cziscience.com)
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`.cell`, `cell_type`, `cell_type_ontology_term_idm`, `cell_type_harmonised`, `confidence_class`, `cell_annotation_azimuth_l2`, `cell_annotation_blueprint_singler`
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`cell_`, `cell_type`, `cell_type_ontology_term_idm`, `cell_type_harmonised`, `confidence_class`, `cell_annotation_azimuth_l2`, `cell_annotation_blueprint_singler`
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Through harmonisation and curation we introduced custom column, not present in the original CELLxGENE metadata
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@@ -218,8 +218,8 @@ Through harmonisation and curation we introduced custom column, not present in t
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- `cell_annotation_blueprint_monaco`: SingleR cell annotation using Monaco reference
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- `sample_id_db`: Sample subdivision for internal use
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- `file_id_db`: File subdivision for internal use
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- `.sample`: Sample ID
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- `.sample_name`: How samples were defined
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- `sample_`: Sample ID
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- `sample_name`: How samples were defined
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# RNA abundance
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‎README.md‎

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Original file line numberDiff line numberDiff line change
@@ -39,27 +39,27 @@ library(stringr)
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``` r
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get_metadata()
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#> # Source: table</stornext/Home/data/allstaff/m/mangiola.s/.cache/R/CuratedAtlasQueryR/metadata.parquet> [?? x 56]
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#> # Database: DuckDB 0.6.2-dev1166 [unknown@Linux 3.10.0-1160.81.1.el7.x86_64:R 4.2.0/:memory:]
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#> .cell sampl…¹ .sample .samp…² assay assay…³ file_…⁴ cell_…⁵ cell_…⁶ devel…⁷
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#> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
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#> 1 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 2 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 3 AAACCT… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
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#> 4 AAACCT… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
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#> 5 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 6 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 7 AAACCT… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 8 AAACGG… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> 9 AAACGG… 02eb2e… 5f20d7… D17PrP… 10x … EFO:00… 30f754… lumina… CL:000… 31-yea…
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#> 10 AAACGG… 8a0fe0… 5f20d7… D17PrP… 10x … EFO:00… 1e334b… basal … CL:000… 31-yea…
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#> # … with more rows, 46 more variables:
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#> # Source: table</stornext/Home/data/allstaff/m/mangiola.s/.cache/R/CuratedAtlasQueryR/metadata.0.2.2.parquet> [?? x 56]
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#> # Database: DuckDB 0.7.0 [unknown@Linux 3.10.0-1160.81.1.el7.x86_64:R 4.2.0/:memory:]
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#> `_cell` _samp…¹ cell_…² cell_…³ confi…⁴ cell_…⁵ cell_…⁶ cell_…⁷ sampl…⁸
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#> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr>
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#> 1 AAACCTGAGAGA… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
47+
#> 2 AAACCTGAGTTG… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> 3 AAACCTGCAGTC… 689e2f… lumina… lumina… 1 <NA> <NA> <NA> 930938…
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#> 4 AAACCTGCAGTT… 689e2f… lumina… lumina… 1 <NA> <NA> <NA> 930938…
50+
#> 5 AAACCTGGTCTA… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> 6 AAACCTGTCGTA… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> 7 AAACCTGTCTTG… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> 8 AAACGGGAGTAC… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> 9 AAACGGGAGTAG… 689e2f… lumina… lumina… 1 <NA> <NA> <NA> 930938…
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#> 10 AAACGGGAGTGG… 689e2f… basal … basal_… 1 <NA> <NA> <NA> f297c7…
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#> # … with more rows, 47 more variables: `_sample_name` <chr>, assay <chr>,
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#> # assay_ontology_term_id <chr>, file_id_db <chr>,
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#> # cell_type_ontology_term_id <chr>, development_stage <chr>,
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#> # development_stage_ontology_term_id <chr>, disease <chr>,
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#> # disease_ontology_term_id <chr>, ethnicity <chr>,
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#> # ethnicity_ontology_term_id <chr>, file_id <chr>, is_primary_data.x <chr>,
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#> # organism <chr>, organism_ontology_term_id <chr>, sample_placeholder <chr>,
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#> # sex <chr>, sex_ontology_term_id <chr>, tissue <chr>,
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#> # tissue_ontology_term_id <chr>, tissue_harmonised <chr>, age_days <dbl>, …
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#> # ethnicity_ontology_term_id <chr>, experiment___ <chr>, file_id <chr>,
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#> # is_primary_data_x <chr>, organism <chr>, organism_ontology_term_id <chr>, …
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```
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### Explore the tissue
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get_metadata() |>
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dplyr::distinct(tissue, file_id)
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#> # Source: SQL [?? x 2]
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#> # Database: DuckDB 0.6.2-dev1166 [unknown@Linux 3.10.0-1160.81.1.el7.x86_64:R 4.2.0/:memory:]
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#> tissue file_id
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#> <chr> <chr>
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#> 1 cortex of kidney 2977b3fa-e4d6-4929-8540-ae12d33a3c53
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#> 2 entorhinal cortex 29d5d028-6f90-4943-91f7-fa3f93731de8
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#> 3 middle temporal gyrus 2a689fda-d335-4ac0-81b1-a356fdf939db
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#> 4 respiratory airway 2c2d5bea-8be7-4227-8a56-f2a85d57fa56
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#> 5 thymus 2ec94470-8171-4825-8346-34d77383438b
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#> 6 ileum 2f893c30-c91b-487b-b1f8-b386a4ef91a3
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#> 7 cortex of kidney 2fe625b6-8c85-4818-a9c5-1189303f6e2b
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#> 8 fimbria of uterine tube 3044b5dd-a499-456e-86d9-94769bc3b63e
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#> 9 ampulla of uterine tube 3044b5dd-a499-456e-86d9-94769bc3b63e
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#> 10 temporal cortex 4e4bbb2d-f341-4523-a5a0-5407d8b03e0e
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#> # Database: DuckDB 0.7.0 [unknown@Linux 3.10.0-1160.81.1.el7.x86_64:R 4.2.0/:memory:]
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#> tissue file_id
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#> <chr> <chr>
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#> 1 renal medulla 52cb5191-2976-4077-ba88-47c76692bef0
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#> 2 pancreas 53329245-06f3-45a4-bf15-ed61f628ff83
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#> 3 blood 5500774a-6ebe-4ddf-adce-90302b7cd007
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#> 4 blood 550760cb-ede9-4e6b-b6ab-7152f2ce29e1
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#> 5 intestine 556bb449-bbef-43d3-9487-87031fc0decb
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#> 6 lung 56e0359f-ee8d-4ba5-a51d-159a183643e5
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#> 7 adrenal gland 56e0359f-ee8d-4ba5-a51d-159a183643e5
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#> 8 pleural effusion 56e0359f-ee8d-4ba5-a51d-159a183643e5
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#> 9 liver 56e0359f-ee8d-4ba5-a51d-159a183643e5
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#> 10 lymph node 56e0359f-ee8d-4ba5-a51d-159a183643e5
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#> # … with more rows
8585
```
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@@ -125,15 +125,14 @@ single_cell_counts =
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single_cell_counts
127127
#> class: SingleCellExperiment
128-
#> dim: 60661 1571
128+
#> dim: 35615 1571
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#> metadata(0):
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#> assays(2): counts cpm
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#> rownames(60661): TSPAN6 TNMD ... RP11-175I6.6 PRSS43P
131+
#> rownames(35615): TSPAN6 TNMD ... LNCDAT HRURF
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#> rowData names(0):
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#> colnames(1571): ACAGCCGGTCCGTTAA_F02526_1 GGGAATGAGCCCAGCT_F02526_1 ...
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#> TACAACGTCAGCATTG_SC84_1 CATTCGCTCAATACCG_F02526_1
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#> colData names(56): sample_id_db .sample ... n_tissue_in_cell_type
136-
#> original_cell_id
135+
#> colData names(56): _sample cell_type ... updated_at_y original_cell_id
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#> reducedDimNames(0):
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#> mainExpName: NULL
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#> altExpNames(0):
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single_cell_counts
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#> class: SingleCellExperiment
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#> dim: 60661 1571
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#> dim: 35615 1571
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#> metadata(0):
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#> assays(1): cpm
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#> rownames(60661): TSPAN6 TNMD ... RP11-175I6.6 PRSS43P
166+
#> rownames(35615): TSPAN6 TNMD ... LNCDAT HRURF
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#> rowData names(0):
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#> colnames(1571): ACAGCCGGTCCGTTAA_F02526_1 GGGAATGAGCCCAGCT_F02526_1 ...
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#> TACAACGTCAGCATTG_SC84_1 CATTCGCTCAATACCG_F02526_1
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#> colData names(56): sample_id_db .sample ... n_tissue_in_cell_type
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#> original_cell_id
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#> colData names(56): _sample cell_type ... updated_at_y original_cell_id
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#> reducedDimNames(0):
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#> mainExpName: NULL
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#> altExpNames(0):
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201199
#> rowData names(0):
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#> colnames(1571): ACAGCCGGTCCGTTAA_F02526_1 GGGAATGAGCCCAGCT_F02526_1 ...
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#> TACAACGTCAGCATTG_SC84_1 CATTCGCTCAATACCG_F02526_1
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#> colData names(56): sample_id_db .sample ... n_tissue_in_cell_type
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#> original_cell_id
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#> colData names(56): _sample cell_type ... updated_at_y original_cell_id
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#> reducedDimNames(0):
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#> mainExpName: NULL
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#> altExpNames(0):
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#> ℹ Synchronising files
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#> ℹ Reading files.
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#> ℹ Compiling Single Cell Experiment.
231-
#> Warning: Feature names cannot have underscores ('_'), replacing with dashes
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#> ('-')
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#> Warning: Non-unique features (rownames) present in the input matrix, making
229+
#> unique
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single_cell_counts
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#> An object of class Seurat
236-
#> 60661 features across 1571 samples within 1 assay
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#> Active assay: originalexp (60661 features, 0 variable features)
233+
#> 35615 features across 1571 samples within 1 assay
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#> Active assay: originalexp (35615 features, 0 variable features)
238235
```
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240237
## Visualise gene transcription
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251248
# Filter and subset
252249
filter(cell_type_harmonised=="nk") |>
253-
select(.cell, file_id_db, disease, file_id, tissue_harmonised) |>
250+
select(cell_, file_id_db, disease, file_id, tissue_harmonised) |>
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255252
# Get counts per million for NCAM1 gene
256253
get_SingleCellExperiment(assays = "cpm", features = "NCAM1") |>
@@ -286,9 +283,8 @@ cellxgene.cziscience.com)
286283
Sample-specific columns (definitions available at
287284
cellxgene.cziscience.com)
288285

289-
`.sample`, `.sample_name`, `age_days`, `assay`,
290-
`assay_ontology_term_id`, `development_stage`,
291-
`development_stage_ontology_term_id`, `ethnicity`,
286+
`sample_`, `sample_name`, `age_days`, `assay`, `assay_ontology_term_id`,
287+
`development_stage`, `development_stage_ontology_term_id`, `ethnicity`,
292288
`ethnicity_ontology_term_id`, `experiment___`, `organism`,
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`organism_ontology_term_id`, `sample_placeholder`, `sex`,
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`sex_ontology_term_id`, `tissue`, `tissue_harmonised`,
@@ -298,7 +294,7 @@ cellxgene.cziscience.com)
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Cell-specific columns (definitions available at
299295
cellxgene.cziscience.com)
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301-
`.cell`, `cell_type`, `cell_type_ontology_term_idm`,
297+
`cell_`, `cell_type`, `cell_type_ontology_term_idm`,
302298
`cell_type_harmonised`, `confidence_class`,
303299
`cell_annotation_azimuth_l2`, `cell_annotation_blueprint_singler`
304300

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320316
Monaco reference
321317
- `sample_id_db`: Sample subdivision for internal use
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- `file_id_db`: File subdivision for internal use
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- `.sample`: Sample ID
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- `.sample_name`: How samples were defined
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- `sample_`: Sample ID
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- `sample_name`: How samples were defined
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# RNA abundance
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‎tests/testthat/test-query.R‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@ library(CuratedAtlasQueryR)
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test_that("get_SingleCellExperiment() correctly handles duplicate cell IDs", {
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meta <- get_metadata() |>
5-
dplyr::filter(`_cell` == "868417_1") |>
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dplyr::filter(cell_ == "868417_1") |>
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dplyr::collect()
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sce <- get_SingleCellExperiment(meta)
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# This query should return multiple cells, despite querying only 1 cell ID

‎vignettes/Introduction.Rmd‎

Lines changed: 4 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -172,7 +172,7 @@ meta |>
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# Filter and subset
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filter(cell_type_harmonised=="nk") |>
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select(.cell, file_id_db, disease, file_id, tissue_harmonised) |>
175+
select(cell_, file_id_db, disease, file_id, tissue_harmonised) |>
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# Get counts per million for NCAM1 gene
178178
get_SingleCellExperiment(assays = "cpm", features = "NCAM1") |>
@@ -204,11 +204,11 @@ Dataset-specific columns (definitions available at cellxgene.cziscience.com)
204204

205205
Sample-specific columns (definitions available at cellxgene.cziscience.com)
206206

207-
`.sample`, `.sample_name`, `age_days`, `assay`, `assay_ontology_term_id`, `development_stage`, `development_stage_ontology_term_id`, `ethnicity`, `ethnicity_ontology_term_id`, `experiment___`, `organism`, `organism_ontology_term_id`, `sample_placeholder`, `sex`, `sex_ontology_term_id`, `tissue`, `tissue_harmonised`, `tissue_ontology_term_id`, `disease`, `disease_ontology_term_id`, `is_primary_data.x`
207+
`sample_`, `sample_name`, `age_days`, `assay`, `assay_ontology_term_id`, `development_stage`, `development_stage_ontology_term_id`, `ethnicity`, `ethnicity_ontology_term_id`, `experiment___`, `organism`, `organism_ontology_term_id`, `sample_placeholder`, `sex`, `sex_ontology_term_id`, `tissue`, `tissue_harmonised`, `tissue_ontology_term_id`, `disease`, `disease_ontology_term_id`, `is_primary_data.x`
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209209
Cell-specific columns (definitions available at cellxgene.cziscience.com)
210210

211-
`.cell`, `cell_type`, `cell_type_ontology_term_idm`, `cell_type_harmonised`, `confidence_class`, `cell_annotation_azimuth_l2`, `cell_annotation_blueprint_singler`
211+
`cell_`, `cell_type`, `cell_type_ontology_term_idm`, `cell_type_harmonised`, `confidence_class`, `cell_annotation_azimuth_l2`, `cell_annotation_blueprint_singler`
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213213
Through harmonisation and curation we introduced custom column, not present in the original CELLxGENE metadata
214214

@@ -221,7 +221,7 @@ Through harmonisation and curation we introduced custom column, not present in t
221221
- `cell_annotation_blueprint_monaco`: SingleR cell annotation using Monaco reference
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- `sample_id_db`: Sample subdivision for internal use
223223
- `file_id_db`: File subdivision for internal use
224-
- `.sample`: Sample ID
224+
- `sample_`: Sample ID
225225
- `.sample_name`: How samples were defined
226226

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# RNA abundance

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