Merge branch 'maintenance/v0.1.x' into dev

kevin931 · Nov 17, 2023 · 1d0e2bb · 1d0e2bb
2 parents 9027524 + e8eef37
commit 1d0e2bb
Show file tree

Hide file tree

Showing 4 changed files with 38 additions and 29 deletions.
diff --git a/PyCytoData/data.py b/PyCytoData/data.py
@@ -190,6 +190,7 @@ def preprocess(self,
         3. Gate for intact cells.
         4. Gate for live cells.
         5. Gate for anomalies using center, offset, and residual channels. 
+        6. Bead normalization.
 
         :param gate_debris_removal: Whether to gate to remove debris, defaults to True.
         :type gate_debris_removal: bool
@@ -520,11 +521,11 @@ def __getitem__(self, items: Union[slice, List[int], np.ndarray, Tuple[Union[sli
         
         A few deviations from the numpy notations:
         
-        1. Integer indices are currently not supported. This is because indexing by integer
-            returns a 1-d array instead of a 2-d array, which can possibly cause confusion.
-        2. Indexing by two lists or arrays with different lengths are supported. They are
-            treated to index rows and columns, such as ``exprs[[0,1,2], [3,4]]`` is perfectly
-            valid to index the first 3 cells with the fourth and fifth channel.
+        1. Integer indices are currently not supported. This is because indexing by
+           integer returns a 1-d array instead of a 2-d array, which can possibly cause confusion.
+        2. Indexing by two lists or arrays with different lengths are supported.
+           They are treated to index rows and columns, such as ``exprs[[0,1,2], [3,4]]`` is
+           perfectly valid to index the first 3 cells with the fourth and fifth channel.
         
         .. tip::
         

diff --git a/README.md b/README.md
@@ -3,7 +3,7 @@
 # PyCytoData
 > An elegant data analysis tool for CyTOF.
 
-This package is an all-in-one CyTOF data analysis package for your experiments. From loading datasets to DR and evaluation, you have a consistent interface and readable code every step along the way. There is also support for some of ``HDCytoData``'s benchmark datasets as originally implemented in R by Weber & Soneson (2019) in [this repository](https://github.com/lmweber/HDCytoData). Why wait? Start your PyCytoData journal right here, right now! 
+This package is an all-in-one CyTOF data analysis package for your experiments. From loading datasets to DR and evaluation, you have a consistent interface and readable code every step along the way. There is also support for some of ``HDCytoData``'s benchmark datasets as originally implemented in R by Weber & Soneson (2019) in [this repository](https://github.com/lmweber/HDCytoData). Why wait? Start your PyCytoData journey right here, right now! 
 
 ## Installation
 
@@ -180,19 +180,23 @@ Update is strongly recommended.
 
 ## References
 
-If you used ``PyCytoData`` in your research or with ``Cytomulate`` as part of the pipeline, please cite [our paper](https://doi.org/10.1101/2022.06.14.496200) here:
+If you used ``PyCytoData`` in your research or with ``Cytomulate`` as part of the pipeline, please cite [our paper](https://doi.org/10.1186/s13059-023-03099-1) here:
 
 ```
-@article {Yang2022.06.14.496200,
+Yang, Y., Wang, K., Lu, Z. et al. Cytomulate: accurate and efficient simulation of CyTOF data. Genome Biol 24, 262 (2023). https://doi.org/10.1186/s13059-023-03099-1
+```
+
+or with our BibTex:
+
+```
+@article {Yang2023,
 	author = {Yang, Yuqiu and Wang, Kaiwen and Lu, Zeyu and Wang, Tao and Wang, Xinlei},
-	title = {Cytomulate: Accurate and Efficient Simulation of CyTOF data},
-	elocation-id = {2022.06.14.496200},
-	year = {2022},
-	doi = {10.1101/2022.06.14.496200},
-	publisher = {Cold Spring Harbor Laboratory},
-	URL = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200},
-	eprint = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200.full.pdf},
-	journal = {bioRxiv}
+	title = {Cytomulate: accurate and efficient simulation of CyTOF data},
+  journal={Genome biology},
+  volume={24},
+  number={262},
+  year={2023},
+  publisher={Springer}
 }
 ```
 

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -65,7 +65,7 @@ tutorials below! Enjoy your journey working with CyTOF datasets!
    :hidden:
 
    references
-   Our Paper (Cytomulate) <https://doi.org/10.1101/2022.06.14.496200>
+   Our Paper (Cytomulate) <https://doi.org/10.1186/s13059-023-03099-1>
    CyTOF DR Review (CytofDR) <https://doi.org/10.1038/s41467-023-37478-w>
    Dr. Xinlei (Shery) Wang <https://www.uta.edu/academics/faculty/profile?username=wangx9>
    Dr. Tao Wang <https://qbrc.swmed.edu/labs/wanglab/aboutpi.php>
@@ -80,7 +80,7 @@ Resources
 
 For more resources on our labs, collaborators, and related projects, please visit the following:
 
-   * `Our Paper (Cytomulate) <https://doi.org/10.1101/2022.06.14.496200>`_
+   * `Our Paper (Cytomulate) <https://doi.org/10.1186/s13059-023-03099-1>`_
    * `CyTOF DR Review Paper (CytofDR) <https://doi.org/10.1038/s41467-023-37478-w>`_
    * `Dr. Xinlei (Shery) Wang faculty page <https://www.uta.edu/academics/faculty/profile?username=wangx9>`_
    * `Dr. Tao Wang Lab <https://qbrc.swmed.edu/labs/wanglab/aboutpi.php>`_

diff --git a/docs/source/references.rst b/docs/source/references.rst
@@ -2,21 +2,25 @@
 References
 ################
 
-If you used ``PyCytoData`` as part of your research or used ``Cytomulate`` with this package, `our paper <https://doi.org/10.1101/2022.06.14.496200>`_
+If you used ``PyCytoData`` as part of your research or used ``Cytomulate`` with this package, `our paper <https://doi.org/10.1186/s13059-023-03099-1>`_
 can be cited here:
 
+.. code-block::
+
+	Yang, Y., Wang, K., Lu, Z. et al. Cytomulate: accurate and efficient simulation of CyTOF data. Genome Biol 24, 262 (2023). https://doi.org/10.1186/s13059-023-03099-1
+
+or
+
 .. code-block:: 
 
-	@article {Yang2022.06.14.496200,
+	@article {Yang2023,
 		author = {Yang, Yuqiu and Wang, Kaiwen and Lu, Zeyu and Wang, Tao and Wang, Xinlei},
-		title = {Cytomulate: Accurate and Efficient Simulation of CyTOF data},
-		elocation-id = {2022.06.14.496200},
-		year = {2022},
-		doi = {10.1101/2022.06.14.496200},
-		publisher = {Cold Spring Harbor Laboratory},
-		URL = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200},
-		eprint = {https://www.biorxiv.org/content/early/2022/06/16/2022.06.14.496200.full.pdf},
-		journal = {bioRxiv}
+		title = {Cytomulate: accurate and efficient simulation of CyTOF data},
+		journal={Genome biology},
+		volume={24},
+		number={262},
+		year={2023},
+		publisher={Springer}
 	}
 
 
@@ -55,7 +59,7 @@ Benchmark Datasets
 ********************
 
 If you use the builtin datasets (``levine13``, ``levine32``, ``samusik``), you can cite the following papers
-along with ``HDCytoData``, which hosts these datasets.
+along with ``HDCytoData``, which serves as the inspiration for this package.
 
 - Weber, L. M., & Soneson, C. (2019). HDCytoData: collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats. F1000Research, 8.
 - Levine et al. (2015). Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis. Cell, 162, pp. 184-197.