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Estimating intrinsic and extrinsic noise from single-cell gene expression measurements

Fu, Audrey Qiuyan and Pachter, Lior (2016) Estimating intrinsic and extrinsic noise from single-cell gene expression measurements. Statistical Applications in Genetics and Molecular Biology, 15 (6). pp. 447-471. ISSN 2194-6302. PMCID PMC5518956. http://resolver.caltech.edu/CaltechAUTHORS:20170306-150123048

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Abstract

Gene expression is stochastic and displays variation (“noise”) both within and between cells. Intracellular (intrinsic) variance can be distinguished from extracellular (extrinsic) variance by applying the law of total variance to data from two-reporter assays that probe expression of identically regulated gene pairs in single cells. We examine established formulas [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.] for the estimation of intrinsic and extrinsic noise and provide interpretations of them in terms of a hierarchical model. This allows us to derive alternative estimators that minimize bias or mean squared error. We provide a geometric interpretation of these results that clarifies the interpretation in [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.]. We also demonstrate through simulation and re-analysis of published data that the distribution assumptions underlying the hierarchical model have to be satisfied for the estimators to produce sensible results, which highlights the importance of normalization.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1515/sagmb-2016-0002DOIArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5518956PubMed CentralArticle
https://arxiv.org/abs/1601.03334arXivDiscussion Paper
ORCID:
AuthorORCID
Pachter, Lior0000-0002-9164-6231
Additional Information:© 2016 Walter de Gruyter GmbH, Berlin/Boston. Published Online: 2016-11-22; Published in Print: 2016-12-01. This project began as a result of discussion during a journal club meeting of Prof. Jonathan Pritchard’s group that A.F. was attending. We thank Michael Elowitz, Peter Swain, Nam Ki Lee and Sora Yang for sharing their data from Elowitz et al. (2002) and from Yang et al. (2014), respectively. We also thank helpful comments we have received since posting the manuscript online. In particular, we thank Arjun Raj for bringing up the 1- vs 2-copy experiment, and Erik van Nimwegen for helpful discussions. We also thank Editor in Chief Prof. Michael Stumpf and two anonymous reviewers for insightful comments that led to a significantly enriched version. A.F. was partially supported by K99 HG007368 and R00 HG007368 (NIH/NHGRI). L.P. was partially supported by NIH grants R01 HG006129 and R01 DK094699.
Funders:
Funding AgencyGrant Number
NIHK99 HG007368
NIHR00 HG007368
NIHR01 HG006129
NIHR01 DK094699
Subject Keywords:gene expression; noise; optimal estimators; single cell
PubMed Central ID:PMC5518956
Record Number:CaltechAUTHORS:20170306-150123048
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20170306-150123048
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74808
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:07 Mar 2017 00:15
Last Modified:03 May 2019 17:49

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