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BioinformaticsBioinformatics
Peer-reviewed journal article

PROSSTT: probabilistic simulation of single-cell RNA-seq data for complex differentiation processes

Νικόλαος ΠαπαδόπουλοςiD, R. Gonzalo ParraiD, Johannes SödingiD

Abstract

BackgroundSingle-cell RNA sequencing (scRNA-seq) is an enabling technology for the study of cellular differentiation and heterogeneity. From snapshots of the transcriptomic profiles of differentiating single cells, the cellular lineage tree that leads from a progenitor population to multiple types of differentiated cells can be derived. The underlying lineage trees of most published datasets are linear or have a single branchpoint, but many studies with more complex lineage trees will soon become available. To test and further develop tools for lineage tree reconstruction, we need test datasets with known trees.\n\nResultsPROSSTT can simulate scRNA-seq datasets for differentiation processes with lineage trees of any desired complexity, noise level, noise model, and size. PROSSTT also provides scripts to quantify the quality of predicted lineage trees.\n\nAvailabilityhttps://github.com/soedinglab/prosstt\n\nContactsoeding@mpibpc.mpg.de

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