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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.

notebook system details reference figure
blood/simulated hematopoiesis simulated Krumsiek et al., Plos One (2011) 2a
blood/paul15 murine hematopoiesis 2,730 cells, MARS-seq Paul et al., Cell (2015) 2b
blood/nestorowa16 murine hematopoiesis 1,654 cells, Smart-seq2 Nestorowa et al., Blood (2016) 2c
blood/dahlin18 murine hematopoiesis 44,802 cells, 10x Genomics Dahlin et al., Blood (2018) 2d
planaria planaria 21,612 cells Plass et al., Science (2018) 3
zebrafish zebrafish embryo 53,181 cells Wagner et al., Science (2018) 4
1M_neurons neurons 1.3 million cells, 10x Genomics 10x Genomics (2017) S12
deep_learning cycling Jurkat cells 30,000 single-cell images Eulenberg et al., Nat. Commun. (2017) S14

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

notebook description figure
connectivity_measure connectivity measure S1, S2, S3
robustness robustness and multi-resolution capacity S4, S5
comparisons/simulated_data comparisons for simulated data S6, S7
comparisons/paul15_monocle2 comparison Monocle 2 for Paul et al. (2015) S8
comparisons/nestorowa16_monocle2 comparison Monocle 2 for Nestorowa et al. (2016) S9
embedding_quality quantifying embedding quality S10
simulation simulating hematopoiesis S11
1M_neurons neurons, 1.3 million cells, 10x Genomics, 10x Genomics (2017) S12
blood/paul15 annotation of louvain clusters using PAGA S13
deep_learning cycling Jurkat cells, 30,000 single-cell images, Eulenberg et al., Nat. Commun. (2017) S14


Mapping out the coarse-grained connectivity structures of complex manifolds.




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