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Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells

The stochastic nature of generating eukaryotic transcripts challenges conventional methods for obtaining and analyzing single-cell gene expression data. In order to address the inherent noise, detailed methods are described on how to collect data on multiple genes in a large number of single cells u...

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Detalles Bibliográficos
Autores principales: Livak, Kenneth J., Wills, Quin F., Tipping, Alex J., Datta, Krishnalekha, Mittal, Rowena, Goldson, Andrew J., Sexton, Darren W., Holmes, Chris C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562442/
https://www.ncbi.nlm.nih.gov/pubmed/23079396
http://dx.doi.org/10.1016/j.ymeth.2012.10.004
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author Livak, Kenneth J.
Wills, Quin F.
Tipping, Alex J.
Datta, Krishnalekha
Mittal, Rowena
Goldson, Andrew J.
Sexton, Darren W.
Holmes, Chris C.
author_facet Livak, Kenneth J.
Wills, Quin F.
Tipping, Alex J.
Datta, Krishnalekha
Mittal, Rowena
Goldson, Andrew J.
Sexton, Darren W.
Holmes, Chris C.
author_sort Livak, Kenneth J.
collection PubMed
description The stochastic nature of generating eukaryotic transcripts challenges conventional methods for obtaining and analyzing single-cell gene expression data. In order to address the inherent noise, detailed methods are described on how to collect data on multiple genes in a large number of single cells using microfluidic arrays. As part of a study exploring the effect of genotype on Wnt pathway activation, data were collected for 96 qPCR assays on 1440 lymphoblastoid cells. The description of methods includes preliminary data processing steps. The methods used in the collection and analysis of single-cell qPCR data are contrasted with those used in conventional qPCR.
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spelling pubmed-35624422013-02-04 Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells Livak, Kenneth J. Wills, Quin F. Tipping, Alex J. Datta, Krishnalekha Mittal, Rowena Goldson, Andrew J. Sexton, Darren W. Holmes, Chris C. Methods Article The stochastic nature of generating eukaryotic transcripts challenges conventional methods for obtaining and analyzing single-cell gene expression data. In order to address the inherent noise, detailed methods are described on how to collect data on multiple genes in a large number of single cells using microfluidic arrays. As part of a study exploring the effect of genotype on Wnt pathway activation, data were collected for 96 qPCR assays on 1440 lymphoblastoid cells. The description of methods includes preliminary data processing steps. The methods used in the collection and analysis of single-cell qPCR data are contrasted with those used in conventional qPCR. Academic Press 2013-01 /pmc/articles/PMC3562442/ /pubmed/23079396 http://dx.doi.org/10.1016/j.ymeth.2012.10.004 Text en © 2013 Elsevier Inc. https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Article
Livak, Kenneth J.
Wills, Quin F.
Tipping, Alex J.
Datta, Krishnalekha
Mittal, Rowena
Goldson, Andrew J.
Sexton, Darren W.
Holmes, Chris C.
Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title_full Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title_fullStr Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title_full_unstemmed Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title_short Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells
title_sort methods for qpcr gene expression profiling applied to 1440 lymphoblastoid single cells
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562442/
https://www.ncbi.nlm.nih.gov/pubmed/23079396
http://dx.doi.org/10.1016/j.ymeth.2012.10.004
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