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  Reconstructing complex lineage trees from scRNA-seq data using MERLoT

Parra, R. G., Papadopoulos, N., Ahumada-Arranz, L., El Kholtei, J., Mottelson, N., Horokhovsky, Y., et al. (2019). Reconstructing complex lineage trees from scRNA-seq data using MERLoT. Nucleic Acids Research, 47(17), 8961-8974. doi:10.1093/nar/gkz706.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0004-F53E-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000B-AD9F-0
Genre: Journal Article

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© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
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 Creators:
Parra, R. Gonzalo, Author
Papadopoulos, Nikolaos, Author
Ahumada-Arranz, Laura, Author
El Kholtei, Jakob , Author
Mottelson, Noah, Author
Horokhovsky, Yehor, Author
Treutlein, Barbara1, Author                 
Soeding, Johannes, Author
Affiliations:
1Single Cell Genomics, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society, ou_2173644              

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 Abstract: Advances in single-cell transcriptomics techniques are revolutionizing studies of cellular differentiation and heterogeneity. It has become possible to track the trajectory of thousands of genes across the cellular lineage trees that represent the temporal emergence of cell types during dynamic processes. However, reconstruction of cellular lineage trees with more than a few cell fates has proved challenging. We present MERLoT (https://github.com/soedinglab/merlot), a flexible and user-friendly tool to reconstruct complex lineage trees from single-cell transcriptomics data. It can impute temporal gene expression profiles along the reconstructed tree. We show MERLoT’s capabilities on various real cases and hundreds of simulated datasets.

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Language(s): eng - English
 Dates: 2019-09-26
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1093/nar/gkz706
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Title: Nucleic Acids Research
Source Genre: Journal
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Pages: - Volume / Issue: 47 (17) Sequence Number: - Start / End Page: 8961 - 8974 Identifier: ISSN: 0305-1048