A statistical approach for identifying differential distributions in single-cell RNA-seq experiments View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Keegan D. Korthauer, Li-Fang Chu, Michael A. Newton, Yuan Li, James Thomson, Ron Stewart, Christina Kendziorski

ABSTRACT

The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach. More... »

PAGES

222

References to SciGraph publications

  • 2015-12. Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells in GENOME BIOLOGY
  • 2010-02. The pea aphid genome sequence brings theories of insect defense into question in GENOME BIOLOGY
  • 2005-06. Cell cycle control of embryonic stem cells in STEM CELL REVIEWS AND REPORTS
  • 2016-12. Ancient DNA and the rewriting of human history: be sparing with Occam’s razor in GENOME BIOLOGY
  • 2013-09. Transcriptome and genome sequencing uncovers functional variation in humans in NATURE
  • 2013-09. Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data in GENOME BIOLOGY
  • 2002-05. Regulation of noise in the expression of a single gene in NATURE GENETICS
  • 2014-12-03. Deconstructing transcriptional heterogeneity in pluripotent stem cells in NATURE
  • 2012-08. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells in NATURE BIOTECHNOLOGY
  • 2014-07. Bayesian approach to single-cell differential expression analysis in NATURE METHODS
  • 2013-06. Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells in NATURE
  • 2016-12. Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm in GENOME BIOLOGY
  • 2010-07. Single-cell NF-κB dynamics reveal digital activation and analogue information processing in NATURE
  • 2014-04. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells in NATURE BIOTECHNOLOGY
  • 2012. Bimodal Protein Distributions in Heterogeneous Oscillating Systems in COMPUTATIONAL METHODS IN SYSTEMS BIOLOGY
  • 2005-06. Stochasticity in gene expression: from theories to phenotypes in NATURE REVIEWS GENETICS
  • 2011-05. Chemically defined conditions for human iPSC derivation and culture in NATURE METHODS
  • 2013-09. Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells in NATURE STRUCTURAL & MOLECULAR BIOLOGY
  • 2011-12. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome in BMC BIOINFORMATICS
  • 2012-12. Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise in BMC SYSTEMS BIOLOGY
  • 2016-12. Beyond comparisons of means: understanding changes in gene expression at the single-cell level in GENOME BIOLOGY
  • 2010-10. Differential expression analysis for sequence count data in GENOME BIOLOGY
  • 2014-02. voom: precision weights unlock linear model analysis tools for RNA-seq read counts in GENOME BIOLOGY
  • 2015-12. MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing data in GENOME BIOLOGY
  • 2015-12. De novo assembly of bacterial transcriptomes from RNA-seq data in GENOME BIOLOGY
  • 2014-05. Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq in NATURE
  • 2016-12. Discrete distributional differential expression (D3E) - a tool for gene expression analysis of single-cell RNA-seq data in BMC BIOINFORMATICS
  • 2015-03. Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells in NATURE BIOTECHNOLOGY
  • 2013-08. Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing in NATURE
  • 2015-10. Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments in NATURE METHODS
  • 2013-01. Inferring the kinetics of stochastic gene expression from single-cell RNA-sequencing data in GENOME BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13059-016-1077-y

    DOI

    http://dx.doi.org/10.1186/s13059-016-1077-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1001810254

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/27782827


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0104", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Statistics", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Mathematical Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Algorithms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Computational Biology", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "High-Throughput Nucleotide Sequencing", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Analysis, RNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Single-Cell Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Software", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Harvard University", 
              "id": "https://www.grid.ac/institutes/grid.38142.3c", 
              "name": [
                "Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 02215, Boston, MA, USA", 
                "Department of Biostatistics, Harvard T. H. Chan School of Public Health, 02115, Boston, MA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Korthauer", 
            "givenName": "Keegan D.", 
            "id": "sg:person.01160161455.34", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160161455.34"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Wisconsin\u2013Madison", 
              "id": "https://www.grid.ac/institutes/grid.14003.36", 
              "name": [
                "Morgridge Institute for Research, University of Wisconsin, 53706, Madison, WI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chu", 
            "givenName": "Li-Fang", 
            "id": "sg:person.01155005721.95", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155005721.95"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Wisconsin\u2013Madison", 
              "id": "https://www.grid.ac/institutes/grid.14003.36", 
              "name": [
                "Department of Biostatistics, University of Wisconsin, 53706, Madison, WI, USA", 
                "Department of Statistics, University of Wisconsin, 53706, Madison, WI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Newton", 
            "givenName": "Michael A.", 
            "id": "sg:person.01242322154.17", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242322154.17"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Wisconsin\u2013Madison", 
              "id": "https://www.grid.ac/institutes/grid.14003.36", 
              "name": [
                "Department of Statistics, University of Wisconsin, 53706, Madison, WI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Li", 
            "givenName": "Yuan", 
            "id": "sg:person.01062741047.69", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01062741047.69"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Morgridge Institute for Research, University of Wisconsin, 53706, Madison, WI, USA", 
                "Department of Cell and Regenerative Biology, University of Wisconsin, 53706, Madison, WI, USA", 
                "Department of Molecular, Cellular, and Developmental Biology, University of California, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Thomson", 
            "givenName": "James", 
            "id": "sg:person.012266000337.10", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012266000337.10"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Wisconsin\u2013Madison", 
              "id": "https://www.grid.ac/institutes/grid.14003.36", 
              "name": [
                "Morgridge Institute for Research, University of Wisconsin, 53706, Madison, WI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Stewart", 
            "givenName": "Ron", 
            "id": "sg:person.015153676747.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015153676747.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Wisconsin\u2013Madison", 
              "id": "https://www.grid.ac/institutes/grid.14003.36", 
              "name": [
                "Department of Biostatistics, University of Wisconsin, 53706, Madison, WI, USA", 
                "Department of Statistics, University of Wisconsin, 53706, Madison, WI, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kendziorski", 
            "givenName": "Christina", 
            "id": "sg:person.01200027211.18", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200027211.18"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/s0955-0674(00)00154-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002497920"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.tibs.2005.09.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004505010"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.tibs.2005.09.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004505010"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12859-016-0944-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004557618", 
              "https://doi.org/10.1186/s12859-016-0944-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.3549", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005273990", 
              "https://doi.org/10.1038/nmeth.3549"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/30.1.207", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005297170"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2011.08.023", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008248361"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btt511", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008560102"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkt145", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009099949"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.stem.2010.03.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012499272"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13920", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1012885463", 
              "https://doi.org/10.1038/nature13920"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-0930-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014175016", 
              "https://doi.org/10.1186/s13059-016-0930-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1242/dev.110601", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014196464"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg1615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014958319", 
              "https://doi.org/10.1038/nrg1615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg1615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014958319", 
              "https://doi.org/10.1038/nrg1615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrg1615", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014958319", 
              "https://doi.org/10.1038/nrg1615"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2967", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015866289", 
              "https://doi.org/10.1038/nmeth.2967"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.3102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016103324", 
              "https://doi.org/10.1038/nbt.3102"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-3-642-33636-2_3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017227019", 
              "https://doi.org/10.1007/978-3-642-33636-2_3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-015-0692-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017242507", 
              "https://doi.org/10.1186/s13059-015-0692-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-015-0692-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017242507", 
              "https://doi.org/10.1186/s13059-015-0692-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-015-0692-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017242507", 
              "https://doi.org/10.1186/s13059-015-0692-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2010-11-2-106", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017440825", 
              "https://doi.org/10.1186/gb-2010-11-2-106"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.145144.112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017622007"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.151588598", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017925340"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/gr.161034.113", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018538260"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2859", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1018546171", 
              "https://doi.org/10.1038/nbt.2859"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.molcel.2014.06.029", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019447028"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.celrep.2012.08.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019883673"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-014-0572-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020717956", 
              "https://doi.org/10.1186/s13059-014-0572-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-014-0572-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020717956", 
              "https://doi.org/10.1186/s13059-014-0572-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-12-323", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021902674", 
              "https://doi.org/10.1186/1471-2105-12-323"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/stem.1113", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022000732"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cell.2013.04.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024131885"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-015-0844-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025156179", 
              "https://doi.org/10.1186/s13059-015-0844-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.1516645112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025374500"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1593", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028183020", 
              "https://doi.org/10.1038/nmeth.1593"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.stem.2015.09.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029349367"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng869", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030126259", 
              "https://doi.org/10.1038/ng869"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng869", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030126259", 
              "https://doi.org/10.1038/ng869"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2010-11-10-r106", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031289083", 
              "https://doi.org/10.1186/gb-2010-11-10-r106"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/hmg/ddl112", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031534989"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pbio.0040309", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031857499"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pone.0033788", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032135069"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature12172", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035006736", 
              "https://doi.org/10.1038/nature12172"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2013-14-9-r95", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036803445", 
              "https://doi.org/10.1186/gb-2013-14-9-r95"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-1033-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037189037", 
              "https://doi.org/10.1186/s13059-016-1033-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-1033-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037189037", 
              "https://doi.org/10.1186/s13059-016-1033-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/0471142727.mb0422s107", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039084047"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/gepi.20255", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039265406"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09145", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040793604", 
              "https://doi.org/10.1038/nature09145"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature09145", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040793604", 
              "https://doi.org/10.1038/nature09145"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1098/rsif.2014.0383", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041234555"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13173", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042638061", 
              "https://doi.org/10.1038/nature13173"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-015-0866-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042902494", 
              "https://doi.org/10.1186/s13059-015-0866-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2013-14-1-r7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043158487", 
              "https://doi.org/10.1186/gb-2013-14-1-r7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature12364", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043470764", 
              "https://doi.org/10.1038/nature12364"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1385/scr:1:2:131", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043519746", 
              "https://doi.org/10.1385/scr:1:2:131"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/03610919408813196", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044271055"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2014-15-2-r29", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045312009", 
              "https://doi.org/10.1186/gb-2014-15-2-r29"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1752-0509-6-109", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046687594", 
              "https://doi.org/10.1186/1752-0509-6-109"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1126/science.1254257", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046815039"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/hmg/ddu167", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047707020"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.1404656111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048361174"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nsmb.2660", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050140072", 
              "https://doi.org/10.1038/nsmb.2660"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2282", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051167758", 
              "https://doi.org/10.1038/nbt.2282"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1214/11-ba625", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051946695"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature12531", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052616209", 
              "https://doi.org/10.1038/nature12531"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btt087", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052940103"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/01621459.1963.10500845", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058299788"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1080/03610929008830345", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1058334809"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1089/scd.2004.13.694", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059309432"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/biomet/83.2.275", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059420652"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1471082x0800800204", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064025714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1177/1471082x0800800204", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064025714"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1198/jcgs.2010.07081", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064201030"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.18637/jss.v053.i08", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1068672796"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.4137/cin.s2846", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1077950823"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/020735", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085110275"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/020735", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085110275"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1101/020735", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085110275"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2016-12", 
        "datePublishedReg": "2016-12-01", 
        "description": "The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/s13059-016-1077-y", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.3805478", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2521815", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3860225", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.2691985", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1023439", 
            "issn": [
              "1474-760X", 
              "1465-6906"
            ], 
            "name": "Genome Biology", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "17"
          }
        ], 
        "name": "A statistical approach for identifying differential distributions in single-cell RNA-seq experiments", 
        "pagination": "222", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "089f7614a018e4cf375507a30f0075a70a3b0de96bea2e660833f29bb6ff83ef"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "27782827"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "100960660"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s13059-016-1077-y"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1001810254"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s13059-016-1077-y", 
          "https://app.dimensions.ai/details/publication/pub.1001810254"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T12:25", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87106_00000000.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1186%2Fs13059-016-1077-y"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s13059-016-1077-y'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13059-016-1077-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13059-016-1077-y'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13059-016-1077-y'


     

    This table displays all metadata directly associated to this object as RDF triples.

    404 TRIPLES      21 PREDICATES      107 URIs      30 LITERALS      18 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s13059-016-1077-y schema:about N023e23f515e3420e9bc68b94f3f3c7b0
    2 N0a3c93d54aca4af286e4c1815cbfb4ab
    3 N0cb2d359967a481f818ff6e532f30f91
    4 N21abf92434904472ade7a6fe67ec2e03
    5 N329d7bd17bd34f8e844d8fee61a462ec
    6 N77b4bb0d6fe64228a56bd1a6d079bb2f
    7 N8459f9a094ec44f48f12ad0f04206dcd
    8 Nc50e1374b76c4654a01647cbda77424f
    9 Nd6641c7d87ab4691b0299fdc3dbef349
    10 anzsrc-for:01
    11 anzsrc-for:0104
    12 schema:author N773c5b802e214a079580ab52fe29c363
    13 schema:citation sg:pub.10.1007/978-3-642-33636-2_3
    14 sg:pub.10.1038/nature09145
    15 sg:pub.10.1038/nature12172
    16 sg:pub.10.1038/nature12364
    17 sg:pub.10.1038/nature12531
    18 sg:pub.10.1038/nature13173
    19 sg:pub.10.1038/nature13920
    20 sg:pub.10.1038/nbt.2282
    21 sg:pub.10.1038/nbt.2859
    22 sg:pub.10.1038/nbt.3102
    23 sg:pub.10.1038/ng869
    24 sg:pub.10.1038/nmeth.1593
    25 sg:pub.10.1038/nmeth.2967
    26 sg:pub.10.1038/nmeth.3549
    27 sg:pub.10.1038/nrg1615
    28 sg:pub.10.1038/nsmb.2660
    29 sg:pub.10.1186/1471-2105-12-323
    30 sg:pub.10.1186/1752-0509-6-109
    31 sg:pub.10.1186/gb-2010-11-10-r106
    32 sg:pub.10.1186/gb-2010-11-2-106
    33 sg:pub.10.1186/gb-2013-14-1-r7
    34 sg:pub.10.1186/gb-2013-14-9-r95
    35 sg:pub.10.1186/gb-2014-15-2-r29
    36 sg:pub.10.1186/s12859-016-0944-6
    37 sg:pub.10.1186/s13059-014-0572-2
    38 sg:pub.10.1186/s13059-015-0692-3
    39 sg:pub.10.1186/s13059-015-0844-5
    40 sg:pub.10.1186/s13059-015-0866-z
    41 sg:pub.10.1186/s13059-016-0930-3
    42 sg:pub.10.1186/s13059-016-1033-x
    43 sg:pub.10.1385/scr:1:2:131
    44 https://doi.org/10.1002/0471142727.mb0422s107
    45 https://doi.org/10.1002/gepi.20255
    46 https://doi.org/10.1002/stem.1113
    47 https://doi.org/10.1016/j.cell.2011.08.023
    48 https://doi.org/10.1016/j.cell.2013.04.022
    49 https://doi.org/10.1016/j.celrep.2012.08.003
    50 https://doi.org/10.1016/j.molcel.2014.06.029
    51 https://doi.org/10.1016/j.stem.2010.03.015
    52 https://doi.org/10.1016/j.stem.2015.09.011
    53 https://doi.org/10.1016/j.tibs.2005.09.005
    54 https://doi.org/10.1016/s0955-0674(00)00154-x
    55 https://doi.org/10.1073/pnas.1404656111
    56 https://doi.org/10.1073/pnas.151588598
    57 https://doi.org/10.1073/pnas.1516645112
    58 https://doi.org/10.1080/01621459.1963.10500845
    59 https://doi.org/10.1080/03610919408813196
    60 https://doi.org/10.1080/03610929008830345
    61 https://doi.org/10.1089/scd.2004.13.694
    62 https://doi.org/10.1093/bioinformatics/btt087
    63 https://doi.org/10.1093/bioinformatics/btt511
    64 https://doi.org/10.1093/biomet/83.2.275
    65 https://doi.org/10.1093/hmg/ddl112
    66 https://doi.org/10.1093/hmg/ddu167
    67 https://doi.org/10.1093/nar/30.1.207
    68 https://doi.org/10.1093/nar/gkt145
    69 https://doi.org/10.1098/rsif.2014.0383
    70 https://doi.org/10.1101/020735
    71 https://doi.org/10.1101/gr.145144.112
    72 https://doi.org/10.1101/gr.161034.113
    73 https://doi.org/10.1126/science.1254257
    74 https://doi.org/10.1177/1471082x0800800204
    75 https://doi.org/10.1198/jcgs.2010.07081
    76 https://doi.org/10.1214/11-ba625
    77 https://doi.org/10.1242/dev.110601
    78 https://doi.org/10.1371/journal.pbio.0040309
    79 https://doi.org/10.1371/journal.pone.0033788
    80 https://doi.org/10.18637/jss.v053.i08
    81 https://doi.org/10.4137/cin.s2846
    82 schema:datePublished 2016-12
    83 schema:datePublishedReg 2016-12-01
    84 schema:description The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach.
    85 schema:genre research_article
    86 schema:inLanguage en
    87 schema:isAccessibleForFree true
    88 schema:isPartOf N317f3ab8caed4b0c8e15b3fdfcefd6d5
    89 Na8c72a99b00e42a2bb3982efd629172f
    90 sg:journal.1023439
    91 schema:name A statistical approach for identifying differential distributions in single-cell RNA-seq experiments
    92 schema:pagination 222
    93 schema:productId N35cf785ef51d4cb0a67d4d33e1947713
    94 N52a1f23433714d2e8d2fa9cd6e6cd9e2
    95 N61661f43007f4f32b41e37a337955d98
    96 Nb91e5756c764458891f3cc23fe2fc919
    97 Nd8a2ad36d3524d13933009ba7d8fb57b
    98 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001810254
    99 https://doi.org/10.1186/s13059-016-1077-y
    100 schema:sdDatePublished 2019-04-11T12:25
    101 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    102 schema:sdPublisher Nc69e35a98fa54ce280ab49b37bb17af1
    103 schema:url https://link.springer.com/10.1186%2Fs13059-016-1077-y
    104 sgo:license sg:explorer/license/
    105 sgo:sdDataset articles
    106 rdf:type schema:ScholarlyArticle
    107 N023e23f515e3420e9bc68b94f3f3c7b0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    108 schema:name Computational Biology
    109 rdf:type schema:DefinedTerm
    110 N0a3c93d54aca4af286e4c1815cbfb4ab schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    111 schema:name Single-Cell Analysis
    112 rdf:type schema:DefinedTerm
    113 N0cb2d359967a481f818ff6e532f30f91 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    114 schema:name RNA
    115 rdf:type schema:DefinedTerm
    116 N21abf92434904472ade7a6fe67ec2e03 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    117 schema:name Humans
    118 rdf:type schema:DefinedTerm
    119 N26546bdee6c1421ea1280d35213aa307 rdf:first sg:person.01242322154.17
    120 rdf:rest N6b2e4a8561094035b05298a34c64218c
    121 N27e230a7b373472a9d42de674945eb6a rdf:first sg:person.01200027211.18
    122 rdf:rest rdf:nil
    123 N317f3ab8caed4b0c8e15b3fdfcefd6d5 schema:volumeNumber 17
    124 rdf:type schema:PublicationVolume
    125 N329d7bd17bd34f8e844d8fee61a462ec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    126 schema:name Gene Expression Profiling
    127 rdf:type schema:DefinedTerm
    128 N35cf785ef51d4cb0a67d4d33e1947713 schema:name doi
    129 schema:value 10.1186/s13059-016-1077-y
    130 rdf:type schema:PropertyValue
    131 N4fb84b6a2bdc4bc3b61489266f433c22 rdf:first sg:person.015153676747.04
    132 rdf:rest N27e230a7b373472a9d42de674945eb6a
    133 N52a1f23433714d2e8d2fa9cd6e6cd9e2 schema:name nlm_unique_id
    134 schema:value 100960660
    135 rdf:type schema:PropertyValue
    136 N54440d843c814a189b30b554ac849926 rdf:first sg:person.012266000337.10
    137 rdf:rest N4fb84b6a2bdc4bc3b61489266f433c22
    138 N61661f43007f4f32b41e37a337955d98 schema:name pubmed_id
    139 schema:value 27782827
    140 rdf:type schema:PropertyValue
    141 N6b2e4a8561094035b05298a34c64218c rdf:first sg:person.01062741047.69
    142 rdf:rest N54440d843c814a189b30b554ac849926
    143 N773c5b802e214a079580ab52fe29c363 rdf:first sg:person.01160161455.34
    144 rdf:rest N77cc2ee553c243199a622e8af09ae228
    145 N77b4bb0d6fe64228a56bd1a6d079bb2f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    146 schema:name Algorithms
    147 rdf:type schema:DefinedTerm
    148 N77cc2ee553c243199a622e8af09ae228 rdf:first sg:person.01155005721.95
    149 rdf:rest N26546bdee6c1421ea1280d35213aa307
    150 N8459f9a094ec44f48f12ad0f04206dcd schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    151 schema:name High-Throughput Nucleotide Sequencing
    152 rdf:type schema:DefinedTerm
    153 Na8c72a99b00e42a2bb3982efd629172f schema:issueNumber 1
    154 rdf:type schema:PublicationIssue
    155 Nb91e5756c764458891f3cc23fe2fc919 schema:name readcube_id
    156 schema:value 089f7614a018e4cf375507a30f0075a70a3b0de96bea2e660833f29bb6ff83ef
    157 rdf:type schema:PropertyValue
    158 Nc50e1374b76c4654a01647cbda77424f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    159 schema:name Software
    160 rdf:type schema:DefinedTerm
    161 Nc69e35a98fa54ce280ab49b37bb17af1 schema:name Springer Nature - SN SciGraph project
    162 rdf:type schema:Organization
    163 Nd6641c7d87ab4691b0299fdc3dbef349 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    164 schema:name Sequence Analysis, RNA
    165 rdf:type schema:DefinedTerm
    166 Nd8a2ad36d3524d13933009ba7d8fb57b schema:name dimensions_id
    167 schema:value pub.1001810254
    168 rdf:type schema:PropertyValue
    169 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
    170 schema:name Mathematical Sciences
    171 rdf:type schema:DefinedTerm
    172 anzsrc-for:0104 schema:inDefinedTermSet anzsrc-for:
    173 schema:name Statistics
    174 rdf:type schema:DefinedTerm
    175 sg:grant.2521815 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-016-1077-y
    176 rdf:type schema:MonetaryGrant
    177 sg:grant.2691985 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-016-1077-y
    178 rdf:type schema:MonetaryGrant
    179 sg:grant.3805478 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-016-1077-y
    180 rdf:type schema:MonetaryGrant
    181 sg:grant.3860225 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-016-1077-y
    182 rdf:type schema:MonetaryGrant
    183 sg:journal.1023439 schema:issn 1465-6906
    184 1474-760X
    185 schema:name Genome Biology
    186 rdf:type schema:Periodical
    187 sg:person.01062741047.69 schema:affiliation https://www.grid.ac/institutes/grid.14003.36
    188 schema:familyName Li
    189 schema:givenName Yuan
    190 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01062741047.69
    191 rdf:type schema:Person
    192 sg:person.01155005721.95 schema:affiliation https://www.grid.ac/institutes/grid.14003.36
    193 schema:familyName Chu
    194 schema:givenName Li-Fang
    195 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01155005721.95
    196 rdf:type schema:Person
    197 sg:person.01160161455.34 schema:affiliation https://www.grid.ac/institutes/grid.38142.3c
    198 schema:familyName Korthauer
    199 schema:givenName Keegan D.
    200 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01160161455.34
    201 rdf:type schema:Person
    202 sg:person.01200027211.18 schema:affiliation https://www.grid.ac/institutes/grid.14003.36
    203 schema:familyName Kendziorski
    204 schema:givenName Christina
    205 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200027211.18
    206 rdf:type schema:Person
    207 sg:person.012266000337.10 schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    208 schema:familyName Thomson
    209 schema:givenName James
    210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012266000337.10
    211 rdf:type schema:Person
    212 sg:person.01242322154.17 schema:affiliation https://www.grid.ac/institutes/grid.14003.36
    213 schema:familyName Newton
    214 schema:givenName Michael A.
    215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01242322154.17
    216 rdf:type schema:Person
    217 sg:person.015153676747.04 schema:affiliation https://www.grid.ac/institutes/grid.14003.36
    218 schema:familyName Stewart
    219 schema:givenName Ron
    220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015153676747.04
    221 rdf:type schema:Person
    222 sg:pub.10.1007/978-3-642-33636-2_3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017227019
    223 https://doi.org/10.1007/978-3-642-33636-2_3
    224 rdf:type schema:CreativeWork
    225 sg:pub.10.1038/nature09145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040793604
    226 https://doi.org/10.1038/nature09145
    227 rdf:type schema:CreativeWork
    228 sg:pub.10.1038/nature12172 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035006736
    229 https://doi.org/10.1038/nature12172
    230 rdf:type schema:CreativeWork
    231 sg:pub.10.1038/nature12364 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043470764
    232 https://doi.org/10.1038/nature12364
    233 rdf:type schema:CreativeWork
    234 sg:pub.10.1038/nature12531 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052616209
    235 https://doi.org/10.1038/nature12531
    236 rdf:type schema:CreativeWork
    237 sg:pub.10.1038/nature13173 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042638061
    238 https://doi.org/10.1038/nature13173
    239 rdf:type schema:CreativeWork
    240 sg:pub.10.1038/nature13920 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012885463
    241 https://doi.org/10.1038/nature13920
    242 rdf:type schema:CreativeWork
    243 sg:pub.10.1038/nbt.2282 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051167758
    244 https://doi.org/10.1038/nbt.2282
    245 rdf:type schema:CreativeWork
    246 sg:pub.10.1038/nbt.2859 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018546171
    247 https://doi.org/10.1038/nbt.2859
    248 rdf:type schema:CreativeWork
    249 sg:pub.10.1038/nbt.3102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016103324
    250 https://doi.org/10.1038/nbt.3102
    251 rdf:type schema:CreativeWork
    252 sg:pub.10.1038/ng869 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030126259
    253 https://doi.org/10.1038/ng869
    254 rdf:type schema:CreativeWork
    255 sg:pub.10.1038/nmeth.1593 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028183020
    256 https://doi.org/10.1038/nmeth.1593
    257 rdf:type schema:CreativeWork
    258 sg:pub.10.1038/nmeth.2967 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015866289
    259 https://doi.org/10.1038/nmeth.2967
    260 rdf:type schema:CreativeWork
    261 sg:pub.10.1038/nmeth.3549 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005273990
    262 https://doi.org/10.1038/nmeth.3549
    263 rdf:type schema:CreativeWork
    264 sg:pub.10.1038/nrg1615 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014958319
    265 https://doi.org/10.1038/nrg1615
    266 rdf:type schema:CreativeWork
    267 sg:pub.10.1038/nsmb.2660 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050140072
    268 https://doi.org/10.1038/nsmb.2660
    269 rdf:type schema:CreativeWork
    270 sg:pub.10.1186/1471-2105-12-323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021902674
    271 https://doi.org/10.1186/1471-2105-12-323
    272 rdf:type schema:CreativeWork
    273 sg:pub.10.1186/1752-0509-6-109 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046687594
    274 https://doi.org/10.1186/1752-0509-6-109
    275 rdf:type schema:CreativeWork
    276 sg:pub.10.1186/gb-2010-11-10-r106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031289083
    277 https://doi.org/10.1186/gb-2010-11-10-r106
    278 rdf:type schema:CreativeWork
    279 sg:pub.10.1186/gb-2010-11-2-106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017440825
    280 https://doi.org/10.1186/gb-2010-11-2-106
    281 rdf:type schema:CreativeWork
    282 sg:pub.10.1186/gb-2013-14-1-r7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043158487
    283 https://doi.org/10.1186/gb-2013-14-1-r7
    284 rdf:type schema:CreativeWork
    285 sg:pub.10.1186/gb-2013-14-9-r95 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036803445
    286 https://doi.org/10.1186/gb-2013-14-9-r95
    287 rdf:type schema:CreativeWork
    288 sg:pub.10.1186/gb-2014-15-2-r29 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045312009
    289 https://doi.org/10.1186/gb-2014-15-2-r29
    290 rdf:type schema:CreativeWork
    291 sg:pub.10.1186/s12859-016-0944-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004557618
    292 https://doi.org/10.1186/s12859-016-0944-6
    293 rdf:type schema:CreativeWork
    294 sg:pub.10.1186/s13059-014-0572-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020717956
    295 https://doi.org/10.1186/s13059-014-0572-2
    296 rdf:type schema:CreativeWork
    297 sg:pub.10.1186/s13059-015-0692-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017242507
    298 https://doi.org/10.1186/s13059-015-0692-3
    299 rdf:type schema:CreativeWork
    300 sg:pub.10.1186/s13059-015-0844-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025156179
    301 https://doi.org/10.1186/s13059-015-0844-5
    302 rdf:type schema:CreativeWork
    303 sg:pub.10.1186/s13059-015-0866-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1042902494
    304 https://doi.org/10.1186/s13059-015-0866-z
    305 rdf:type schema:CreativeWork
    306 sg:pub.10.1186/s13059-016-0930-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014175016
    307 https://doi.org/10.1186/s13059-016-0930-3
    308 rdf:type schema:CreativeWork
    309 sg:pub.10.1186/s13059-016-1033-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1037189037
    310 https://doi.org/10.1186/s13059-016-1033-x
    311 rdf:type schema:CreativeWork
    312 sg:pub.10.1385/scr:1:2:131 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043519746
    313 https://doi.org/10.1385/scr:1:2:131
    314 rdf:type schema:CreativeWork
    315 https://doi.org/10.1002/0471142727.mb0422s107 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039084047
    316 rdf:type schema:CreativeWork
    317 https://doi.org/10.1002/gepi.20255 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039265406
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1002/stem.1113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022000732
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1016/j.cell.2011.08.023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008248361
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1016/j.cell.2013.04.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024131885
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1016/j.celrep.2012.08.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019883673
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1016/j.molcel.2014.06.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019447028
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1016/j.stem.2010.03.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012499272
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1016/j.stem.2015.09.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029349367
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1016/j.tibs.2005.09.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004505010
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1016/s0955-0674(00)00154-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1002497920
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1073/pnas.1404656111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048361174
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1073/pnas.151588598 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017925340
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1073/pnas.1516645112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025374500
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.1080/01621459.1963.10500845 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058299788
    344 rdf:type schema:CreativeWork
    345 https://doi.org/10.1080/03610919408813196 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044271055
    346 rdf:type schema:CreativeWork
    347 https://doi.org/10.1080/03610929008830345 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058334809
    348 rdf:type schema:CreativeWork
    349 https://doi.org/10.1089/scd.2004.13.694 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059309432
    350 rdf:type schema:CreativeWork
    351 https://doi.org/10.1093/bioinformatics/btt087 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052940103
    352 rdf:type schema:CreativeWork
    353 https://doi.org/10.1093/bioinformatics/btt511 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008560102
    354 rdf:type schema:CreativeWork
    355 https://doi.org/10.1093/biomet/83.2.275 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059420652
    356 rdf:type schema:CreativeWork
    357 https://doi.org/10.1093/hmg/ddl112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031534989
    358 rdf:type schema:CreativeWork
    359 https://doi.org/10.1093/hmg/ddu167 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047707020
    360 rdf:type schema:CreativeWork
    361 https://doi.org/10.1093/nar/30.1.207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005297170
    362 rdf:type schema:CreativeWork
    363 https://doi.org/10.1093/nar/gkt145 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009099949
    364 rdf:type schema:CreativeWork
    365 https://doi.org/10.1098/rsif.2014.0383 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041234555
    366 rdf:type schema:CreativeWork
    367 https://doi.org/10.1101/020735 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085110275
    368 rdf:type schema:CreativeWork
    369 https://doi.org/10.1101/gr.145144.112 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017622007
    370 rdf:type schema:CreativeWork
    371 https://doi.org/10.1101/gr.161034.113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018538260
    372 rdf:type schema:CreativeWork
    373 https://doi.org/10.1126/science.1254257 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046815039
    374 rdf:type schema:CreativeWork
    375 https://doi.org/10.1177/1471082x0800800204 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064025714
    376 rdf:type schema:CreativeWork
    377 https://doi.org/10.1198/jcgs.2010.07081 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064201030
    378 rdf:type schema:CreativeWork
    379 https://doi.org/10.1214/11-ba625 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051946695
    380 rdf:type schema:CreativeWork
    381 https://doi.org/10.1242/dev.110601 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014196464
    382 rdf:type schema:CreativeWork
    383 https://doi.org/10.1371/journal.pbio.0040309 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031857499
    384 rdf:type schema:CreativeWork
    385 https://doi.org/10.1371/journal.pone.0033788 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032135069
    386 rdf:type schema:CreativeWork
    387 https://doi.org/10.18637/jss.v053.i08 schema:sameAs https://app.dimensions.ai/details/publication/pub.1068672796
    388 rdf:type schema:CreativeWork
    389 https://doi.org/10.4137/cin.s2846 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077950823
    390 rdf:type schema:CreativeWork
    391 https://www.grid.ac/institutes/grid.133342.4 schema:alternateName University of California, Santa Barbara
    392 schema:name Department of Cell and Regenerative Biology, University of Wisconsin, 53706, Madison, WI, USA
    393 Department of Molecular, Cellular, and Developmental Biology, University of California, 93106, Santa Barbara, CA, USA
    394 Morgridge Institute for Research, University of Wisconsin, 53706, Madison, WI, USA
    395 rdf:type schema:Organization
    396 https://www.grid.ac/institutes/grid.14003.36 schema:alternateName University of Wisconsin–Madison
    397 schema:name Department of Biostatistics, University of Wisconsin, 53706, Madison, WI, USA
    398 Department of Statistics, University of Wisconsin, 53706, Madison, WI, USA
    399 Morgridge Institute for Research, University of Wisconsin, 53706, Madison, WI, USA
    400 rdf:type schema:Organization
    401 https://www.grid.ac/institutes/grid.38142.3c schema:alternateName Harvard University
    402 schema:name Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, 02215, Boston, MA, USA
    403 Department of Biostatistics, Harvard T. H. Chan School of Public Health, 02115, Boston, MA, USA
    404 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...