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update docs
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@rcannood
rcannood committed Sep 19, 2023
1 parent 1f54ebe commit d0e633c
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52 changes: 23 additions & 29 deletions doc/design.md
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Original file line number Diff line number Diff line change
Expand Up @@ -6,10 +6,8 @@
library(anndataR)

# read from h5ad/h5mu file
adata <- read_h5ad("dataset.h5ad")
adata <- read_h5ad("dataset.h5ad", backed = TRUE)
mdata <- read_h5mu("dataset.h5mu")
mdata <- read_h5mu("dataset.h5mu", backed = TRUE)
adata <- read_h5ad("dataset.h5ad", backend = "HDF5AnnData")
adata <- read_h5ad("dataset.h5ad", backend = "InMemoryAnnData")

# anndata-like interface (the Python package)
adata$X
Expand All @@ -30,15 +28,15 @@ colData(adata)
reducedDimNames(adata)

# converters from/to sce
sce <- adata$to_sce()
sce <- adata$to_SingleCellExperiment()
from_sce(sce)

# optional feature 3: converters from/to Seurat
seu <- adata$to_seurat()
seu <- adata$to_Seurat()
from_seurat(seu)

# optional feature 4: converters from/to SOMA
som <- adata$to_soma()
som <- adata$to_SOMA()
from_soma(som)
```

Expand All @@ -63,17 +61,17 @@ classDiagram
*subset(...): AbstractAnnData
*write_h5ad(): Unit
to_sce(): SingleCellExperiment
to_seurat(): Seurat
to_SingleCellExperiment(): SingleCellExperiment
to_Seurat(): Seurat
to_h5anndata(): H5AnnData
to_zarranndata(): ZarrAnnData
to_inmemory(): InMemoryAnnData
to_HDF5AnnData(): HDF5AnnData
to_ZarrAnnData(): ZarrAnnData
to_InMemoryAnnData(): InMemoryAnnData
}
AbstractAnnData <|-- H5AnnData
class H5AnnData {
init(h5file): H5AnnData
AbstractAnnData <|-- HDF5AnnData
class HDF5AnnData {
init(h5file): HDF5AnnData
}
AbstractAnnData <|-- ZarrAnnData
Expand All @@ -92,8 +90,7 @@ classDiagram
}
class anndataR {
read_h5ad(path, backend): AbstractAnnData
read_h5mu(path, backend): AbstractMuData
read_h5ad(path, backend): Either[AbstractAnnData, SingleCellExperiment, Seurat]
}
anndataR --> AbstractAnnData
```
Expand All @@ -102,9 +99,11 @@ Notation:

- `X: Matrix` - variable `X` is of type `Matrix`
- `*X: Matrix` - variable `X` is abstract
- `to_sce(): SingleCellExperiment` - function `to_sce` returns object of
type `SingleCellExperiment`
- `*to_sce()` - function `to_sce` is abstract
- `to_SingleCellExperiment(): SingleCellExperiment` - function
`to_SingleCellExperiment` returns object of type
`SingleCellExperiment`
- `*to_SingleCellExperiment()` - function `to_SingleCellExperiment` is
abstract

## OO-framework

Expand All @@ -125,24 +124,19 @@ ease of use.

## Approach

- Implement inheritance objects for `AbstractAnnData`, `H5AnnData`,
- Implement inheritance objects for `AbstractAnnData`, `HDF5AnnData`,
`InMemoryAnnData`
- Only containing `X`, `obs`, `var` for now
- Only containing `X`, `layers`, `obs`, `var` for now
- Implement base R S3 generics
- Implement `read_h5ad()`, `$write_h5ad()`
- Implement `$to_sce()`
- Implement `$to_SingleCellExperiment()`
- Add simple unit tests

Optional:

- Add more fields (obsp, obsm, varp, varm, …) –\> see class diagram
- Start implementing MuData
- Implement `$to_seurat()`
- Implement `$to_Seurat()`
- Implement `ZarrAnnData`
- Implement `ReticulateAnnData`
- Implement Bioconductor S3 generics

## Conclusion

- Scope and therefore the name
- What we do after this
49 changes: 21 additions & 28 deletions doc/design.qmd
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ format: gfm
:::{.content-hidden}
Rendered using:
```
quarto render doc/design.qmd; sed -i 's#&lt;#<#g;s#&gt;#>#g' doc/design.md
quarto render doc/design.qmd
```
:::

Expand All @@ -16,10 +16,8 @@ quarto render doc/design.qmd; sed -i 's#&lt;#<#g;s#&gt;#>#g' doc/design.md
library(anndataR)

# read from h5ad/h5mu file
adata <- read_h5ad("dataset.h5ad")
adata <- read_h5ad("dataset.h5ad", backed = TRUE)
mdata <- read_h5mu("dataset.h5mu")
mdata <- read_h5mu("dataset.h5mu", backed = TRUE)
adata <- read_h5ad("dataset.h5ad", backend = "HDF5AnnData")
adata <- read_h5ad("dataset.h5ad", backend = "InMemoryAnnData")

# anndata-like interface (the Python package)
adata$X
Expand All @@ -40,15 +38,15 @@ colData(adata)
reducedDimNames(adata)

# converters from/to sce
sce <- adata$to_sce()
sce <- adata$to_SingleCellExperiment()
from_sce(sce)

# optional feature 3: converters from/to Seurat
seu <- adata$to_seurat()
seu <- adata$to_Seurat()
from_seurat(seu)

# optional feature 4: converters from/to SOMA
som <- adata$to_soma()
som <- adata$to_SOMA()
from_soma(som)
```

Expand All @@ -73,17 +71,17 @@ classDiagram
*subset(...): AbstractAnnData
*write_h5ad(): Unit
to_sce(): SingleCellExperiment
to_seurat(): Seurat
to_SingleCellExperiment(): SingleCellExperiment
to_Seurat(): Seurat
to_h5anndata(): H5AnnData
to_zarranndata(): ZarrAnnData
to_inmemory(): InMemoryAnnData
to_HDF5AnnData(): HDF5AnnData
to_ZarrAnnData(): ZarrAnnData
to_InMemoryAnnData(): InMemoryAnnData
}
AbstractAnnData <|-- H5AnnData
class H5AnnData {
init(h5file): H5AnnData
AbstractAnnData <|-- HDF5AnnData
class HDF5AnnData {
init(h5file): HDF5AnnData
}
AbstractAnnData <|-- ZarrAnnData
Expand All @@ -102,8 +100,7 @@ classDiagram
}
class anndataR {
read_h5ad(path, backend): AbstractAnnData
read_h5mu(path, backend): AbstractMuData
read_h5ad(path, backend): Either[AbstractAnnData, SingleCellExperiment, Seurat]
}
anndataR --> AbstractAnnData
```
Expand All @@ -112,8 +109,8 @@ Notation:

- `X: Matrix` - variable `X` is of type `Matrix`
- `*X: Matrix` - variable `X` is abstract
- `to_sce(): SingleCellExperiment` - function `to_sce` returns object of type `SingleCellExperiment`
- `*to_sce()` - function `to_sce` is abstract
- `to_SingleCellExperiment(): SingleCellExperiment` - function `to_SingleCellExperiment` returns object of type `SingleCellExperiment`
- `*to_SingleCellExperiment()` - function `to_SingleCellExperiment` is abstract

## OO-framework

Expand All @@ -127,23 +124,19 @@ Choosing an OOP system depends on the project requirements, developer familiarit

## Approach

* Implement inheritance objects for `AbstractAnnData`, `H5AnnData`, `InMemoryAnnData`
* Only containing `X`, `obs`, `var` for now
* Implement inheritance objects for `AbstractAnnData`, `HDF5AnnData`, `InMemoryAnnData`
* Only containing `X`, `layers`, `obs`, `var` for now
* Implement base R S3 generics
* Implement `read_h5ad()`, `$write_h5ad()`
* Implement `$to_sce()`
* Implement `$to_SingleCellExperiment()`
* Add simple unit tests

Optional:

* Add more fields (obsp, obsm, varp, varm, ...) --> see class diagram
* Start implementing MuData
* Implement `$to_seurat()`
* Implement `$to_Seurat()`
* Implement `ZarrAnnData`
* Implement `ReticulateAnnData`
* Implement Bioconductor S3 generics

## Conclusion

* Scope and therefore the name
* What we do after this

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