| Genome-wide copy number analysis of single cells. | |
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MedLine Citation:
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PMID: 22555242 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells in which information regarding genetic heterogeneity is lost. Here we present a protocol that allows for the genome-wide copy number analysis of single nuclei isolated from mixed populations of cells. Single-nucleus sequencing (SNS), combines flow sorting of single nuclei on the basis of DNA content and whole-genome amplification (WGA); this is followed by next-generation sequencing to quantize genomic intervals in a genome-wide manner. Multiplexing of single cells is discussed. In addition, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ∼3 d from flow cytometry to sequence-ready DNA libraries. |
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Authors:
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Timour Baslan; Jude Kendall; Linda Rodgers; Hilary Cox; Mike Riggs; Asya Stepansky; Jennifer Troge; Kandasamy Ravi; Diane Esposito; B Lakshmi; Michael Wigler; Nicholas Navin; James Hicks |
Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S. Date: 2012-05-03 |
Journal Detail:
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Title: Nature protocols Volume: 7 ISSN: 1750-2799 ISO Abbreviation: Nat Protoc Publication Date: 2012 Jun |
Date Detail:
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Created Date: 2012-05-04 Completed Date: 2012-09-07 Revised Date: 2012-09-24 |
Medline Journal Info:
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Nlm Unique ID: 101284307 Medline TA: Nat Protoc Country: England |
Other Details:
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Languages: eng Pagination: 1024-41 Citation Subset: IM |
Affiliation:
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Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, USA. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Cell Nucleus / genetics DNA Copy Number Variations* Flow Cytometry Genetic Heterogeneity Genetic Techniques* Humans Single-Cell Analysis / methods* |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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