Tools: tl
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Any transformation of the data matrix that is not preprocessing. In contrast to a preprocessing function, a tool usually adds an easily interpretable annotation to the data matrix, which can then be visualized with a corresponding plotting function.
Embeddings#
Principal component analysis [Pedregosa et al., 2011]. |
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t-SNE [Amir et al., 2013, Pedregosa et al., 2011, van der Maaten and Hinton, 2008]. |
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Embed the neighborhood graph using UMAP [McInnes et al., 2018]. |
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Force-directed graph drawing [Chippada, 2018, Islam et al., 2011, Jacomy et al., 2014]. |
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Diffusion Maps [Coifman et al., 2005, Haghverdi et al., 2015, Wolf et al., 2018]. |
Compute densities on embeddings.
Calculate the density of cells in an embedding (per condition). |
Clustering and trajectory inference#
Cluster cells into subgroups [Traag et al., 2019]. |
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Cluster cells into subgroups [Blondel et al., 2008, Levine et al., 2015, Traag, 2015]. |
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Computes a hierarchical clustering for the given |
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Infer progression of cells through geodesic distance along the graph [Haghverdi et al., 2016, Wolf et al., 2019]. |
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Mapping out the coarse-grained connectivity structures of complex manifolds [Wolf et al., 2019]. |
Data integration#
Map labels and embeddings from reference data to new data. |
Marker genes#
Rank genes for characterizing groups. |
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Filters out genes based on log fold change and fraction of genes expressing the gene within and outside the |
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Calculate an overlap score between data-deriven marker genes and provided markers |
Gene scores, Cell cycle#
Score a set of genes [Satija et al., 2015]. |
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Score cell cycle genes [Satija et al., 2015]. |
Simulations#
Simulate dynamic gene expression data [Wittmann et al., 2009] [Wolf et al., 2018]. |