{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T23:14:35Z","timestamp":1787008475080,"version":"build-2736575974"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2016,10,2]],"date-time":"2016-10-02T00:00:00Z","timestamp":1475366400000},"content-version":"vor","delay-in-days":1378,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,2,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Motivation: Cell populations are never truly homogeneous; individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantitative polymerase chain reactions now enables high-throughput single-cell gene expression measurement, allowing assessment of cellular heterogeneity. However, few analytic tools have been developed specifically for the statistical and analytical challenges of single-cell quantitative polymerase chain reactions data.<\/jats:p>\n                  <jats:p>Results: We present a statistical framework for the exploration, quality control and analysis of single-cell gene expression data from microfluidic arrays. We assess accuracy and within-sample heterogeneity of single-cell expression and develop quality control criteria to filter unreliable cell measurements. We propose a statistical model accounting for the fact that genes at the single-cell level can be on (and a continuous expression measure is recorded) or dichotomously off (and the recorded expression is zero). Based on this model, we derive a combined likelihood ratio test for differential expression that incorporates both the discrete and continuous components. Using an experiment that examines treatment-specific changes in expression, we show that this combined test is more powerful than either the continuous or dichotomous component in isolation, or a t-test on the zero-inflated data. Although developed for measurements from a specific platform (Fluidigm), these tools are generalizable to other multi-parametric measures over large numbers of events.<\/jats:p>\n                  <jats:p>Availability: All results presented here were obtained using the SingleCellAssay R package available on GitHub (http:\/\/github.com\/RGLab\/SingleCellAssay).<\/jats:p>\n                  <jats:p>Contact: \u00a0rgottard@fhcrc.org<\/jats:p>\n                  <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/bts714","type":"journal-article","created":{"date-parts":[[2012,12,24]],"date-time":"2012-12-24T22:12:57Z","timestamp":1356387177000},"page":"461-467","source":"Crossref","is-referenced-by-count":380,"title":["Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments"],"prefix":"10.1093","volume":"29","author":[{"given":"Andrew","family":"McDavid","sequence":"first","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"},{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Greg","family":"Finak","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pratip K.","family":"Chattopadyay","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Dominguez","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurie","family":"Lamoreaux","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steven S.","family":"Ma","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Roederer","sequence":"additional","affiliation":[{"name":"1 Department of Statistics, University of Washington, Seattle, WA 98195, USA, 2Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA, 3ImmunoTechnology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA and 4Immunology Laboratory, Vaccine Research Center, NIAID, NIH, 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