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

Νικόλαος Παπαδόπουλος | Zendy; Parra R Gonzalo | Zendy; Johannes Söding | Zendy

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

Author(s) -

Νικόλαος Παπαδόπουλος,

Parra R Gonzalo,

Johannes Söding

Publication year - 2019

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz078

Subject(s) - lineage (genetic) , computer science , tree (set theory) , network topology , scripting language , probabilistic logic , data mining , computational biology , noise (video) , simple (philosophy) , biology , artificial intelligence , mathematics , gene , genetics , computer network , mathematical analysis , philosophy , epistemology , image (mathematics) , operating system

Cellular lineage trees can be derived from single-cell RNA sequencing snapshots of differentiating cells. Currently, only datasets with simple topologies are available. To test and further develop tools for lineage tree reconstruction, we need test datasets with known complex topologies. PROSSTT 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.

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