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Dense transcript profiling in single cells by image correlation decoding

Coskun, Ahmet F. and Cai, Long (2016) Dense transcript profiling in single cells by image correlation decoding. Nature Methods, 13 (8). pp. 657-660. ISSN 1548-7091. PMCID PMC4965285. http://resolver.caltech.edu/CaltechAUTHORS:20160509-170833016

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Abstract

Sequential barcoded fluorescent in situ hybridization (seqFISH) allows large numbers of molecular species to be accurately detected in single cells, but multiplexing is limited by the density of barcoded objects. We present correlation FISH (corrFISH), a method to resolve dense temporal barcodes in sequential hybridization experiments. Using corrFISH, we quantified highly expressed ribosomal protein genes in single cultured cells and mouse thymus sections, revealing cell-type-specific gene expression.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1038/nmeth.3895DOIArticle
http://www.nature.com/nmeth/journal/v13/n8/full/nmeth.3895.htmlPublisherArticle
https://github.com/singlecelllab/correlationFISHOrganizationSoftware
http://rdcu.be/iIJQPublisherFree ReadCube access
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4965285/PubMed CentralArticle
ORCID:
AuthorORCID
Coskun, Ahmet F.0000-0002-5797-1524
Cai, Long0000-0002-7154-5361
Additional Information:© 2016 Macmillan Publishers Limited. Received 22 February 2016. Accepted 11 May 2016. Published online 06 June 2016. We thank J. Linton from the Elowitz laboratory (Caltech) for providing cell lines and M. Yui from the Rothenberg Laboratory (Caltech) for the intact thymus organ. We appreciate the help of the City of Hope Pathology Core to slice thymus into sections. This work is funded by US National Institute of Health single-cell analysis program award R01HD075605. A.F.C. is supported by a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. Code availability: Custom MATLAB source codes (Supplementary Software) with test images are available and updated at https://github.com/singlecelllab/correlationFISH. Author Contributions: A.F.C. and L.C. designed the project and wrote the manuscript. L.C. supervised the project. Competing financial interests: L.C. and A.F.C. declare conflict of interests and have filed a patent application.
Funders:
Funding AgencyGrant Number
NIHR01HD075605
Burroughs Wellcome FundUNSPECIFIED
PubMed Central ID:PMC4965285
Record Number:CaltechAUTHORS:20160509-170833016
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160509-170833016
Official Citation:Dense transcript profiling in single cells by image correlation decoding Ahmet F Coskun & Long Cai Nature Methods 13, 657–660 (2016) doi:10.1038/nmeth.3895
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:66792
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:06 Jun 2016 21:04
Last Modified:03 Nov 2016 17:56

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