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Robust lineage reconstruction from high-dimensional single-cell data
Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not b...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001598/ https://www.ncbi.nlm.nih.gov/pubmed/27207878 http://dx.doi.org/10.1093/nar/gkw452 |
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author | Giecold, Gregory Marco, Eugenio Garcia, Sara P. Trippa, Lorenzo Yuan, Guo-Cheng |
author_facet | Giecold, Gregory Marco, Eugenio Garcia, Sara P. Trippa, Lorenzo Yuan, Guo-Cheng |
author_sort | Giecold, Gregory |
collection | PubMed |
description | Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy. |
format | Online Article Text |
id | pubmed-5001598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-50015982016-12-07 Robust lineage reconstruction from high-dimensional single-cell data Giecold, Gregory Marco, Eugenio Garcia, Sara P. Trippa, Lorenzo Yuan, Guo-Cheng Nucleic Acids Res Methods Online Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy. Oxford University Press 2016-08-19 2016-05-20 /pmc/articles/PMC5001598/ /pubmed/27207878 http://dx.doi.org/10.1093/nar/gkw452 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Online Giecold, Gregory Marco, Eugenio Garcia, Sara P. Trippa, Lorenzo Yuan, Guo-Cheng Robust lineage reconstruction from high-dimensional single-cell data |
title | Robust lineage reconstruction from high-dimensional single-cell data |
title_full | Robust lineage reconstruction from high-dimensional single-cell data |
title_fullStr | Robust lineage reconstruction from high-dimensional single-cell data |
title_full_unstemmed | Robust lineage reconstruction from high-dimensional single-cell data |
title_short | Robust lineage reconstruction from high-dimensional single-cell data |
title_sort | robust lineage reconstruction from high-dimensional single-cell data |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001598/ https://www.ncbi.nlm.nih.gov/pubmed/27207878 http://dx.doi.org/10.1093/nar/gkw452 |
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