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+ + + - +
+
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@@ -108,6 +122,7 @@
+ - + + GitHub
  • @@ -146,8 +162,8 @@ - - + + Docker
  • @@ -158,8 +174,8 @@ - - + + Manuscript
  • @@ -173,11 +189,23 @@ Docs Build
    • -
    diff --git a/docs/_build/html/objects.inv b/docs/_build/html/objects.inv index a2be95e..172cfba 100644 Binary files a/docs/_build/html/objects.inv and b/docs/_build/html/objects.inv differ diff --git a/docs/_build/html/preprocessing.html b/docs/_build/html/preprocessing.html index b371264..e9ea2bb 100644 --- a/docs/_build/html/preprocessing.html +++ b/docs/_build/html/preprocessing.html @@ -7,7 +7,7 @@ - + preprocessing package — GRouNdGAN 1.0 documentation @@ -453,10 +453,7 @@

    Contents

    @@ -447,20 +445,6 @@

    sc_dataset module

    @@ -470,77 +454,8 @@

    Contents

    -
    -

    sc_dataset module#

    -
    -
    -class sc_dataset.SCDataset(path: str | bytes | PathLike)[source]#
    -

    Bases: Dataset

    -
    -
    -__init__(path: str | bytes | PathLike) → None[source]#
    -

    Create a dataset from the h5ad processed data. Use the -preprocessing/preprocess.py script to create the h5ad train, -test, and validation files.

    -
    -
    Parameters:
    -

    path (Union[str, bytes, os.PathLike]) – Path to the h5ad file.

    -
    -
    -
    - -
    -
    -__getitem__(index: int) → Tuple[Tensor, Tensor][source]#
    -
    -
    Parameters:
    -

    index (int) –

    -
    -
    Returns:
    -

    Gene expression, Cluster label Tensor tuple.

    -
    -
    Return type:
    -

    Tuple[torch.Tensor, torch.Tensor]

    -
    -
    -
    - -
    -
    -__len__() → int[source]#
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    Returns:
    -

    Number of samples (cells).

    -
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    Return type:
    -

    int

    -
    -
    -
    - -
    - -
    -
    -sc_dataset.get_loader(file_path: str | bytes | PathLike, batch_size: int | None = None) → DataLoader[source]#
    -

    Provides an IterableLoader over a scRNA-seq Dataset read from given h5ad file.

    -
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    Parameters:
    -
      -

    • file_path (Union[str, bytes, os.PathLike]) – Path to the h5ad file.

      • -

    • batch_size (Optional[int]) – Training batch size. If not specified, the entire dataset -is returned at each load.

      • -
    -
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    Returns:
    -

    Iterable data loader over the dataset.

    -
    -
    Return type:
    -

    DataLoader

    -
    -
    -
    - +
    +

    sc_dataset module#

    @@ -579,26 +494,7 @@

    Contents

    -
    - - -
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    - Contents -
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    +
    diff --git a/docs/_build/html/searchindex.js b/docs/_build/html/searchindex.js index b1aee43..588a847 100644 --- a/docs/_build/html/searchindex.js +++ b/docs/_build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["benchmarking", "causal_gan_cfg", "citation", "custom_parser", "docker", "factory", "gans", "index", "installation", "layers", "license", "local_installation", "main", "modules", "networks", "preprocessing", "sc_dataset", "singularity", "tfrecord_loader", "tree", "tutorial"], "filenames": ["benchmarking.rst", "causal_gan_cfg.rst", "citation.rst", "custom_parser.rst", "docker.rst", "factory.rst", "gans.rst", "index.rst", "installation.rst", "layers.rst", "license.rst", "local_installation.rst", "main.rst", "modules.rst", "networks.rst", "preprocessing.rst", "sc_dataset.rst", "singularity.rst", "tfrecord_loader.rst", "tree.rst", "tutorial.rst"], "titles": ["Benchmarking", "<no title>", "Citation", "custom_parser module", "Docker Setup", "factory module", "gans 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"tfrecord-loader-module"]]}, "indexentries": {"gans": [[6, "module-gans"]], "module": [[6, "module-gans"], [9, "module-layers"], [14, "module-networks"], [15, "module-preprocessing"], [15, "module-preprocessing.preprocess"]], "layers": [[9, "module-layers"]], "networks": [[14, "module-networks"]], "preprocess() (in module preprocessing.preprocess)": [[15, "preprocessing.preprocess.preprocess"]], "preprocessing": [[15, "module-preprocessing"]], "preprocessing.preprocess": [[15, "module-preprocessing.preprocess"]]}}) \ No newline at end of file diff --git a/docs/_build/html/singularity.html b/docs/_build/html/singularity.html index 7baaf45..4629e3c 100644 --- a/docs/_build/html/singularity.html +++ b/docs/_build/html/singularity.html @@ -7,7 +7,7 @@ - + Singularity Setup — GRouNdGAN 1.0 documentation diff --git a/docs/_build/html/tfrecord_loader.html b/docs/_build/html/tfrecord_loader.html index 0035481..b33eaef 100644 --- a/docs/_build/html/tfrecord_loader.html +++ b/docs/_build/html/tfrecord_loader.html @@ -7,7 +7,7 @@ - + tfrecord_loader module — GRouNdGAN 1.0 documentation @@ -428,9 +428,7 @@ `); - + @@ -446,14 +444,6 @@

    tfrecord_loader module

    -
    -

    Contents

    -
    -
    @@ -463,45 +453,8 @@

    Contents

    -
    -

    tfrecord_loader module#

    -
    -
    -tfrecord_loader.get_loader(genes_no: int, file_path: str | List[str], batch_size: int, splits: Dict[str, float] | None = None, description: List[str] | Dict[str, str] | None = None, compression_type: str | None = 'gzip', multi_read: bool | None = False, get_clusters: bool | None = False) → DataLoader[source]#
    -

    Provides an IterableLoader over a Dataset read from given tfrecord files for PyTorch.

    -

    Currently used to create data loaders from the PBMC preprocessed dataset in tfrecord -from scGAN (Marouf et al.,2020). description parameter and post_process function -can be modified to accommodate more tfrecord datasets.

    -
    -
    Parameters:
    -
      -

    • genes_no (int) – Number of genes in the expression matrix.

      • -

    • file_path (Union[str, List[str]]) – Tfrecord file path for reading a single tfrecord (multi_read=False) -or file pattern for reading multiple tfrecords (ex: /path/{}.tfrecord).

      • -

    • batch_size (int) – Training batch size.

      • -

    • splits (Optional[Dict[str, float]], optional) – Dictionary of (key, value) pairs, where the key is used to construct -the data and index path(s) and the value determines the contribution -of each split to the batch. Provide when reading from multiple tfrecords -(multi_read=True), by default None.

      • -

    • description (Union[List[str], Dict[str, str], None], optional) – List of keys or dict of (key, value) pairs to extract from each record. -The keys represent the name of the features and the values (“byte”, “float”, or “int”), -by default { “indices”: None, “values”: None, }.

      • -

    • compression_type (Optional[str], optional) – The type of compression used for the tfrecord. Either ‘gzip’ or None, by default “gzip”.

      • -

    • multi_read (Optional[bool], optional) – Specifies whether to construct the dataset from multiple tfrecords. -If True, a file pattern should be passed to file_path, by default False.

      • -

    • get_clusters (Optional[bool], optional) – If True, the returned data loader will contain the cluster label of cells in -addition to their gene expression values, by default False.

      • -
    -
    -
    Returns:
    -

    Iterable data loader over the dataset.

    -
    -
    Return type:
    -

    DataLoader

    -
    -
    -
    - +
    +

    tfrecord_loader module#

    @@ -531,20 +484,7 @@

    Contents

    -
    - - -
    -
    - Contents -
    -
    - -
    +
    diff --git a/docs/_build/html/tree.html b/docs/_build/html/tree.html index 669c82c..9b630fe 100644 --- a/docs/_build/html/tree.html +++ b/docs/_build/html/tree.html @@ -7,7 +7,7 @@ - + <no title> — GRouNdGAN 1.0 documentation diff --git a/docs/_build/html/tutorial.html b/docs/_build/html/tutorial.html index 182e67f..0230681 100644 --- a/docs/_build/html/tutorial.html +++ b/docs/_build/html/tutorial.html @@ -7,7 +7,7 @@ - + Tutorial — GRouNdGAN 1.0 documentation diff --git a/docs/citation.rst b/docs/citation.rst index 6c7ea1c..51afce1 100644 --- a/docs/citation.rst +++ b/docs/citation.rst @@ -1,7 +1,7 @@ Citation ================ - Zinati, Y., Takiddeen, A. & Emad, A. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks. *Nat Commun* **15**, 4055 (2024). `https://doi.org/10.1038/s41467-024-48516-6`_. + Zinati, Y., Takiddeen, A. & Emad, A. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks. *Nat Commun* **15**, 4055 (2024). https://doi.org/10.1038/s41467-024-48516-6. Bibtex Citation diff --git a/docs/index.rst b/docs/index.rst index 0a210f6..21527bd 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -14,7 +14,7 @@ This site documents the code released under **GRouNdGAN (GRN-guided simulation o To find out more details about GRouNdGAN, check out our paper: - Zinati, Y., Takiddeen, A. & Emad, A. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks. *Nat Commun* **15**, 4055 (2024). `https://doi.org/10.1038/s41467-024-48516-6`_. + Zinati, Y., Takiddeen, A. & Emad, A. GRouNdGAN: GRN-guided simulation of single-cell RNA-seq data using causal generative adversarial networks. *Nat Commun* **15**, 4055 (2024). https://doi.org/10.1038/s41467-024-48516-6. .. sidebar:: GRN inference benchmarking workflow