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  FateID infers fate bias in multipotent progenitors from single-cell RNA-seq data

Herman, J. S., Sagar, S., & Grün, D. (2018). FateID infers fate bias in multipotent progenitors from single-cell RNA-seq data. Nature methods, 15, 379-386. doi:10.1038/nmeth.4662.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-F636-D Version Permalink: http://hdl.handle.net/21.11116/0000-0004-EB07-C
Genre: Journal Article

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 Creators:
Herman, Josip S.1, Author
Sagar, S.1, Author
Grün, Dominic1, Author              
Affiliations:
1Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, 79108 Freiburg, DE, ou_2243640              

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 Abstract: To understand stem cell differentiation along multiple lineages, it is necessary to resolve heterogeneous cellular states and the ancestral relationships between them. We developed a robotic miniaturized CEL-Seq2 implementation to carry out deep single-cell RNA-seq of ∼2,000 mouse hematopoietic progenitors enriched for lymphoid lineages, and used an improved clustering algorithm, RaceID3, to identify cell types. To resolve subtle transcriptome differences indicative of lineage biases, we developed FateID, an iterative supervised learning algorithm for the probabilistic quantification of cell fate bias in progenitor populations. Here we used FateID to delineate domains of fate bias and enable the derivation of high-resolution differentiation trajectories, thereby revealing a common progenitor population of B cells and plasmacytoid dendritic cells, which we validated by in vitro differentiation assays. We expect that FateID will improve understanding of the process of cell fate choice in complex multi-lineage differentiation systems.

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Language(s): eng - English
 Dates: 2018-05
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/nmeth.4662
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Title: Nature methods
  Other : Nature methods
Source Genre: Journal
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Publ. Info: New York, NY : Nature Pub. Group
Pages: - Volume / Issue: 15 Sequence Number: - Start / End Page: 379 - 386 Identifier: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556