dc.contributor.author | Zhang, Cheng-Zhong | |
dc.contributor.author | Francis, Joshua | |
dc.contributor.author | Cornils, Hauke | |
dc.contributor.author | Jung, Joonil | |
dc.contributor.author | Maire, Cecile | |
dc.contributor.author | Ligon, Keith L. | |
dc.contributor.author | Meyerson, Matthew | |
dc.contributor.author | Adalsteinsson, Viktor A. | |
dc.contributor.author | Love, John C | |
dc.date.accessioned | 2017-10-02T14:11:45Z | |
dc.date.available | 2017-10-02T14:11:45Z | |
dc.date.issued | 2015-04 | |
dc.date.submitted | 2014-08 | |
dc.identifier.issn | 2041-1723 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/111665 | |
dc.description.abstract | Artifacts introduced in whole-genome amplification (WGA) make it difficult to derive accurate genomic information from single-cell genomes and require different analytical strategies from bulk genome analysis. Here, we describe statistical methods to quantitatively assess the amplification bias resulting from whole-genome amplification of single-cell genomic DNA. Analysis of single-cell DNA libraries generated by different technologies revealed universal features of the genome coverage bias predominantly generated at the amplicon level (1–10 kb). The magnitude of coverage bias can be accurately calibrated from low-pass sequencing (∼0.1 × ) to predict the depth-of-coverage yield of single-cell DNA libraries sequenced at arbitrary depths. We further provide a benchmark comparison of single-cell libraries generated by multi-strand displacement amplification (MDA) and multiple annealing and looping-based amplification cycles (MALBAC). Finally, we develop statistical models to calibrate allelic bias in single-cell whole-genome amplification and demonstrate a census-based strategy for efficient and accurate variant detection from low-input biopsy samples. | en_US |
dc.description.sponsorship | National Cancer Institute (U.S.) (Grant P30-CA14051) | en_US |
dc.language.iso | en_US | |
dc.publisher | Nature Publishing Group | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1038/ncomms7822 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | Prof. Love via Erja Kajosalo | en_US |
dc.title | Calibrating genomic and allelic coverage bias in single-cell sequencing | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Zhang, Cheng-Zhong et al. “Calibrating Genomic and Allelic Coverage Bias in Single-Cell Sequencing.” Nature Communications 6 (April 2015): 6822 ©
2015 Macmillan Publishers Limited | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Chemical Engineering | en_US |
dc.contributor.department | Koch Institute for Integrative Cancer Research at MIT | en_US |
dc.contributor.approver | Love, John C | en_US |
dc.contributor.mitauthor | Adalsteinsson, Viktor A. | |
dc.contributor.mitauthor | Love, John C | |
dc.relation.journal | Nature Communications | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Zhang, Cheng-Zhong; Adalsteinsson, Viktor A.; Francis, Joshua; Cornils, Hauke; Jung, Joonil; Maire, Cecile; Ligon, Keith L.; Meyerson, Matthew; Love, J. Christopher | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0003-4555-2485 | |
dc.identifier.orcid | https://orcid.org/0000-0003-0921-3144 | |
mit.license | PUBLISHER_POLICY | en_US |
mit.metadata.status | Complete | |