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PAGA - partition-based graph abstraction

Mapping out the coarse-grained connectivity structures of complex manifolds (Genome Biology, 2019).

PAGA for hematopoiesis.

PAGA is available within Scanpy through: tl.paga | pl.paga | pl.paga_path | pl.paga_compare.

Below you find links to all central example notebooks, which also allow reproducing all main figures of the paper. If you start working with PAGA, go through blood/paul15.

notebooksystemdetailsreferencefigure
blood/simulatedhematopoiesissimulatedKrumsiek et al., Plos One (2011)2a
blood/paul15murine hematopoiesis2,730 cells, MARS-seqPaul et al., Cell (2015)2b
blood/nestorowa16murine hematopoiesis1,654 cells, Smart-seq2Nestorowa et al., Blood (2016)2c
blood/dahlin18murine hematopoiesis44,802 cells, 10x GenomicsDahlin et al., Blood (2018)2d
planariaplanaria21,612 cellsPlass et al., Science (2018)3
zebrafishzebrafish embryo53,181 cellsWagner et al., Science (2018)4
1M_neuronsneurons1.3 million cells, 10x Genomics10x Genomics (2017)S12
deep_learningcycling Jurkat cells30,000 single-cell imagesEulenberg et al., Nat. Commun. (2017)S14

All supplemental figures of the paper can be reproduced based on the following table.

notebookdescriptionfigure
connectivity_measureconnectivity measureS1, S2, S3
robustnessrobustness and multi-resolution capacityS4, S5
comparisons/simulated_datacomparisons for simulated dataS6, S7
comparisons/paul15_monocle2comparison Monocle 2 for Paul et al. (2015)S8
comparisons/nestorowa16_monocle2comparison Monocle 2 for Nestorowa et al. (2016)S9
embedding_qualityquantifying embedding qualityS10
simulationsimulating hematopoiesisS11
1M_neuronsneurons, 1.3 million cells, 10x Genomics, 10x Genomics (2017)S12
blood/paul15annotation of louvain clusters using PAGAS13
deep_learningcycling Jurkat cells, 30,000 single-cell images, Eulenberg et al., Nat. Commun. (2017)S14