diff --git a/docs/source/index.rst b/docs/source/index.rst index 27991d05..7298f830 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -13,7 +13,7 @@ scVelo - RNA velocity generalized through dynamical modeling enables the recovery of directed dynamic information by leveraging splicing kinetics :cite:p:`LaManno18`. scVelo collects different methods for inferring RNA velocity using an expectation-maximization framework -:cite:p:`Bergen20` or metabolically labeled transcripts :cite:p:`Weiler2024`. +:cite:p:`Bergen20` or metabolically labeled transcripts :cite:p:`Weiler24`. scVelo's key applications ^^^^^^^^^^^^^^^^^^^^^^^^^ diff --git a/docs/source/references.bib b/docs/source/references.bib index bbfd5783..8be9262c 100644 --- a/docs/source/references.bib +++ b/docs/source/references.bib @@ -1,3 +1,18 @@ +@article{BastidasPonce19, + title = {Comprehensive single cell mRNA profiling reveals a detailed roadmap for pancreatic endocrinogenesis}, + volume = {146}, + ISSN = {0950-1991}, + url = {http://dx.doi.org/10.1242/dev.173849}, + DOI = {10.1242/dev.173849}, + number = {12}, + journal = {Development}, + publisher = {The Company of Biologists}, + author = {Bastidas-Ponce, Aimée and Tritschler, Sophie and Dony, Leander and Scheibner, Katharina and Tarquis-Medina, Marta and Salinno, Ciro and Schirge, Silvia and Burtscher, Ingo and B\"{o}ttcher, Anika and Theis, Fabian J. and Lickert, Heiko and Bakhti, Mostafa}, + editor = {Klein, Allon and Treutlein, Barbara}, + year = {2019}, + month = jun +} + @article{Bergen20, doi = {10.1038/s41587-020-0591-3}, url = {https://doi.org/10.1038/s41587-020-0591-3}, @@ -12,6 +27,36 @@ @article{Bergen20 journal = {Nature Biotechnology} } +@article{Haghverdi16, + title = {Diffusion pseudotime robustly reconstructs lineage branching}, + volume = {13}, + ISSN = {1548-7105}, + url = {http://dx.doi.org/10.1038/nmeth.3971}, + DOI = {10.1038/nmeth.3971}, + number = {10}, + journal = {Nature Methods}, + publisher = {Springer Science and Business Media LLC}, + author = {Haghverdi, Laleh and B\"{u}ttner, Maren and Wolf, F Alexander and Buettner, Florian and Theis, Fabian J}, + year = {2016}, + month = aug, + pages = {845-848} +} + +@article{Hochgerner18, + title = {Conserved properties of dentate gyrus neurogenesis across postnatal development revealed by single-cell RNA sequencing}, + volume = {21}, + ISSN = {1546-1726}, + url = {http://dx.doi.org/10.1038/s41593-017-0056-2}, + DOI = {10.1038/s41593-017-0056-2}, + number = {2}, + journal = {Nature Neuroscience}, + publisher = {Springer Science and Business Media LLC}, + author = {Hochgerner, Hannah and Zeisel, Amit and L\"{o}nnerberg, Peter and Linnarsson, Sten}, + year = {2018}, + month = jan, + pages = {290-299} +} + @article{LaManno18, doi = {10.1038/s41586-018-0414-6}, url = {https://doi.org/10.1038/s41586-018-0414-6}, @@ -37,6 +82,66 @@ @article{McInnes18 copyright = {arXiv.org perpetual, non-exclusive license} } +@article{PijuanSala19, + title = {A single-cell molecular map of mouse gastrulation and early organogenesis}, + volume = {566}, + ISSN = {1476-4687}, + url = {http://dx.doi.org/10.1038/s41586-019-0933-9}, + DOI = {10.1038/s41586-019-0933-9}, + number = {7745}, + journal = {Nature}, + publisher = {Springer Science and Business Media LLC}, + author = {Pijuan-Sala, Blanca and Griffiths, Jonathan A. and Guibentif, Carolina and Hiscock, Tom W. and Jawaid, Wajid and Calero-Nieto, Fernando J. and Mulas, Carla and Ibarra-Soria, Ximena and Tyser, Richard C. V. and Ho, Debbie Lee Lian and Reik, Wolf and Srinivas, Shankar and Simons, Benjamin D. and Nichols, Jennifer and Marioni, John C. and G\"{o}ttgens, Berthold}, + year = {2019}, + month = feb, + pages = {490-495} +} + +@article{Setty19, + title = {Characterization of cell fate probabilities in single-cell data with Palantir}, + volume = {37}, + ISSN = {1546-1696}, + url = {http://dx.doi.org/10.1038/s41587-019-0068-4}, + DOI = {10.1038/s41587-019-0068-4}, + number = {4}, + journal = {Nature Biotechnology}, + publisher = {Springer Science and Business Media LLC}, + author = {Setty, Manu and Kiseliovas, Vaidotas and Levine, Jacob and Gayoso, Adam and Mazutis, Linas and Pe’er, Dana}, + year = {2019}, + month = mar, + pages = {451-460} +} + +@article{Tirosh16, + title = {Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq}, + volume = {352}, + ISSN = {1095-9203}, + url = {http://dx.doi.org/10.1126/science.aad0501}, + DOI = {10.1126/science.aad0501}, + number = {6282}, + journal = {Science}, + publisher = {American Association for the Advancement of Science (AAAS)}, + author = {Tirosh, Itay and Izar, Benjamin and Prakadan, Sanjay M. and Wadsworth, Marc H. and Treacy, Daniel and Trombetta, John J. and Rotem, Asaf and Rodman, Christopher and Lian, Christine and Murphy, George and Fallahi-Sichani, Mohammad and Dutton-Regester, Ken and Lin, Jia-Ren and Cohen, Ofir and Shah, Parin and Lu, Diana and Genshaft, Alex S. and Hughes, Travis K. and Ziegler, Carly G. K. and Kazer, Samuel W. and Gaillard, Aleth and Kolb, Kellie E. and Villani, Alexandra-Chloé and Johannessen, Cory M. and Andreev, Aleksandr Y. and Van Allen, Eliezer M. and Bertagnolli, Monica and Sorger, Peter K. and Sullivan, Ryan J. and Flaherty, Keith T. and Frederick, Dennie T. and Jané-Valbuena, Judit and Yoon, Charles H. and Rozenblatt-Rosen, Orit and Shalek, Alex K. and Regev, Aviv and Garraway, Levi A.}, + year = {2016}, + month = apr, + pages = {189-196} +} + +@article{Weiler24, + author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe'er, Dana and Theis, Fabian}, + publisher = {Springer Science and Business Media LLC}, + url = {http://dx.doi.org/10.1038/s41592-024-02303-9}, + doi = {10.1038/s41592-024-02303-9}, + issn = {1548-7105}, + journal = {Nature Methods}, + month = jun, + number = {7}, + pages = {1196-1205}, + title = {CellRank 2: unified fate mapping in multiview single-cell data}, + volume = {21}, + year = {2024}, +} + @article{Wolf18, doi = {10.1186/s13059-017-1382-0}, url = {https://doi.org/10.1186/s13059-017-1382-0}, @@ -63,28 +168,16 @@ @article{Wolf19 journal = {Genome Biology} } -@article{Gayoso2023, - title = {Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells}, - url = {http://dx.doi.org/10.1038/s41592-023-01994-w}, - doi = {10.1038/s41592-023-01994-w}, - journal = {Nature Methods}, - publisher = {Springer Science and Business Media LLC}, - author = {Adam Gayoso and Philipp Weiler and Mohammad Lotfollahi and Dominik Klein and Justin Hong and Aaron Streets and Fabian J. Theis and Nir Yosef}, - year = {2023}, - month = sep -} - -@article{Weiler2024, - author = {Weiler, Philipp and Lange, Marius and Klein, Michal and Pe'er, Dana and Theis, Fabian}, +@article{Zheng17, + title = {Massively parallel digital transcriptional profiling of single cells}, + volume = {8}, + ISSN = {2041-1723}, + url = {http://dx.doi.org/10.1038/ncomms14049}, + DOI = {10.1038/ncomms14049}, + number = {1}, + journal = {Nature Communications}, publisher = {Springer Science and Business Media LLC}, - url = {http://dx.doi.org/10.1038/s41592-024-02303-9}, - doi = {10.1038/s41592-024-02303-9}, - issn = {1548-7105}, - journal = {Nature Methods}, - month = jun, - number = {7}, - pages = {1196--1205}, - title = {CellRank 2: unified fate mapping in multiview single-cell data}, - volume = {21}, - year = {2024}, + author = {Zheng, Grace X. Y. and Terry, Jessica M. and Belgrader, Phillip and Ryvkin, Paul and Bent, Zachary W. and Wilson, Ryan and Ziraldo, Solongo B. and Wheeler, Tobias D. and McDermott, Geoff P. and Zhu, Junjie and Gregory, Mark T. and Shuga, Joe and Montesclaros, Luz and Underwood, Jason G. and Masquelier, Donald A. and Nishimura, Stefanie Y. and Schnall-Levin, Michael and Wyatt, Paul W. and Hindson, Christopher M. and Bharadwaj, Rajiv and Wong, Alexander and Ness, Kevin D. and Beppu, Lan W. and Deeg, H. Joachim and McFarland, Christopher and Loeb, Keith R. and Valente, William J. and Ericson, Nolan G. and Stevens, Emily A. and Radich, Jerald P. and Mikkelsen, Tarjei S. and Hindson, Benjamin J. and Bielas, Jason H.}, + year = {2017}, + month = jan } diff --git a/scvelo/datasets/_datasets.py b/scvelo/datasets/_datasets.py index 1bcbd6c9..fdf32e53 100644 --- a/scvelo/datasets/_datasets.py +++ b/scvelo/datasets/_datasets.py @@ -19,7 +19,7 @@ def bonemarrow( ): """Human bone marrow. - Data from `Setty et al. (2019) `__. + Data from :cite:p:`Setty19`. The bone marrow is the primary site of new blood cell production or haematopoiesis. It is composed of hematopoietic cells, marrow adipose tissue, and supportive stromal @@ -45,7 +45,7 @@ def bonemarrow( def dentategyrus(file_path: Optional[Union[str, Path]] = None, adjusted=True): """Dentate Gyrus neurogenesis. - Data from `Hochgerner et al. (2018) `__. + Data from :cite:p:`Hochgerner18`. Dentate gyrus (DG) is part of the hippocampus involved in learning, episodic memory formation and spatial coding. The experiment from the developing DG comprises two @@ -102,7 +102,7 @@ def dentategyrus_lamanno( ): """Dentate Gyrus neurogenesis. - From `La Manno et al. (2018) `__. + From :cite:p:`LaManno18`. The experiment from the developing mouse hippocampus comprises two time points (P0 and P5) and reveals the complex manifold with multiple branching lineages @@ -145,7 +145,7 @@ def dentategyrus_lamanno( def forebrain(file_path: Union[str, Path] = "data/ForebrainGlut/hgForebrainGlut.loom"): """Developing human forebrain. - From `La Manno et al. (2018) `__. + From :cite:p:`LaManno18`. Forebrain tissue of a human week 10 embryo, focusing on glutamatergic neuronal lineage, obtained from elective routine abortions (10 weeks post-conception). @@ -170,7 +170,7 @@ def gastrulation( ): """Mouse gastrulation. - Data from `Pijuan-Sala et al. (2019) `__. + Data from :cite:p:`PijuanSala19`. Gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult @@ -201,7 +201,7 @@ def gastrulation_e75( ): """Mouse gastrulation subset to E7.5. - Data from `Pijuan-Sala et al. (2019) `__. + Data from :cite:p:`PijuanSala19`. Gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult @@ -225,7 +225,7 @@ def gastrulation_erythroid( ): """Mouse gastrulation subset to erythroid lineage. - Data from `Pijuan-Sala et al. (2019) `__. + Data from :cite:p:`PijuanSala19`. Gastrulation represents a key developmental event during which embryonic pluripotent cells diversify into lineage-specific precursors that will generate the adult @@ -247,7 +247,7 @@ def gastrulation_erythroid( def pancreas(file_path: Union[str, Path] = "data/Pancreas/endocrinogenesis_day15.h5ad"): """Pancreatic endocrinogenesis. - Data from `Bastidas-Ponce et al. (2019) `__. + Data from :cite:p:`BastidasPonce19`. Pancreatic epithelial and Ngn3-Venus fusion (NVF) cells during secondary transition with transcriptome profiles sampled from embryonic day 15.5. @@ -278,7 +278,7 @@ def pancreas(file_path: Union[str, Path] = "data/Pancreas/endocrinogenesis_day15 def pbmc68k(file_path: Optional[Union[str, Path]] = "data/PBMC/pbmc68k.h5ad"): """Peripheral blood mononuclear cells. - Data from `Zheng et al. (2017) `__. + Data from :cite:p:`Zheng17`. This experiment contains 68k peripheral blood mononuclear cells (PBMC) measured using 10X. diff --git a/scvelo/inference/_metabolic_labeling.py b/scvelo/inference/_metabolic_labeling.py index c7405335..3ba2b075 100644 --- a/scvelo/inference/_metabolic_labeling.py +++ b/scvelo/inference/_metabolic_labeling.py @@ -143,7 +143,7 @@ def _get_n_neighbors( def get_labeling_times(adata, time_key) -> List: """Get labeling times in dataset. - See :cite:p:`Weiler2024`. + See :cite:p:`Weiler24`. Parameters ---------- @@ -164,7 +164,7 @@ def get_labeling_time_mask( ) -> Dict[float, np.ndarray]: """Get number of neighbors required to include ``n_nontrivial_counts`` counts per labeling time. - See :cite:p:`Weiler2024`. + See :cite:p:`Weiler24`. Parameters ---------- @@ -191,7 +191,7 @@ def get_obs_dist_argsort( ) -> Dict[float, np.ndarray]: """Calculate argsorted pairwise distances per labeling_time_point. - See :cite:p:`Weiler2024`. + See :cite:p:`Weiler24`. Parameters ---------- @@ -232,7 +232,7 @@ def get_n_neighbors( ) -> Dict[str, pd.DataFrame]: """Get number of neighbors required to include ``n_nontrivial_counts`` counts per labeling time. - See :cite:p:`Weiler2024`. + See :cite:p:`Weiler24`. Parameters ---------- @@ -389,7 +389,7 @@ def get_parameters( ): """Estimates parameters of splicing kinetics from metabolic labeling data. - See :cite:p:`Weiler2024`. + See :cite:p:`Weiler24`. Parameters ---------- diff --git a/scvelo/preprocessing/moments.py b/scvelo/preprocessing/moments.py index f1a8017e..5cf5c168 100644 --- a/scvelo/preprocessing/moments.py +++ b/scvelo/preprocessing/moments.py @@ -39,7 +39,7 @@ def moments( method : {{'umap', 'hnsw', 'sklearn', `None`}} (default: `'umap'`) Method to compute neighbors, only differs in runtime. Connectivities are computed with adaptive kernel width as proposed in - Haghverdi et al. 2016 (https://doi.org/10.1038/nmeth.3971). + :cite:p:`Haghverdi16`. use_rep : `None`, `'X'` or any key for `.obsm` (default: None) Use the indicated representation. If `None`, the representation is chosen automatically: for .n_vars < 50, .X is used, otherwise ‘X_pca’ is used. diff --git a/scvelo/preprocessing/neighbors.py b/scvelo/preprocessing/neighbors.py index da427fc7..ac316449 100644 --- a/scvelo/preprocessing/neighbors.py +++ b/scvelo/preprocessing/neighbors.py @@ -168,7 +168,7 @@ def neighbors( The neighbor graph methods (umap, hnsw, sklearn) only differ in runtime and yield the same result as Scanpy :cite:p:`Wolf18`. Connectivities are computed with - adaptive kernel width as proposed in Haghverdi et al. 2016 (doi:10.1038/nmeth.3971). + adaptive kernel width as proposed in :cite:p:`Haghverdi16`. Parameters ---------- @@ -188,7 +188,7 @@ def neighbors( or 30 components are used when PCA is computed internally. use_rep : `None`, `'X'` or any key for `.obsm` (default: None) Use the indicated representation. If `None`, the representation is chosen - automatically: for .n_vars < 50, .X is used, otherwise ‘X_pca’ is used. + automatically: for .n_vars < 50, .X is used, otherwise 'X_pca' is used. use_highly_variable: `bool` (default: True) Whether to use highly variable genes only, stored in .var['highly_variable']. knn @@ -203,7 +203,7 @@ def neighbors( The 'hnsw' method is most efficient and requires to `pip install hnswlib`. Connectivities are computed with adaptive kernel. metric - A known metric’s name or a callable that returns a distance. + A known metric's name or a callable that returns a distance. metric_kwds Options for the metric. num_threads diff --git a/scvelo/tools/score_genes_cell_cycle.py b/scvelo/tools/score_genes_cell_cycle.py index 44cf24a2..58e73057 100644 --- a/scvelo/tools/score_genes_cell_cycle.py +++ b/scvelo/tools/score_genes_cell_cycle.py @@ -54,7 +54,7 @@ def score_genes_cell_cycle(adata, s_genes=None, g2m_genes=None, copy=False, **kw """Score cell cycle genes. Calculates scores and assigns a cell cycle phase (G1, S, G2M) using the list of cell - cycle genes defined in Tirosh et al, 2015 (https://doi.org/10.1126/science.aad0501). + cycle genes defined in :cite:p:`Tirosh16`. Parameters ----------