Best practices on the differential expression analysis of multi-species RNA-seq View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-04-29

AUTHORS

Matthew Chung, Vincent M. Bruno, David A. Rasko, Christina A. Cuomo, José F. Muñoz, Jonathan Livny, Amol C. Shetty, Anup Mahurkar, Julie C. Dunning Hotopp

ABSTRACT

Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression. More... »

PAGES

121

References to SciGraph publications

  • 2016-10-07. Efficient Enrichment of Bacterial mRNA from Host-Bacteria Total RNA Samples in SCIENTIFIC REPORTS
  • 2018-02-27. Host-Pathogen Transcriptomics by Dual RNA-Seq in BACTERIAL REGULATORY RNA
  • 2013-06-24. Laser microdissection coupled with RNA-seq analysis of porcine enterocytes infected with an obligate intracellular pathogen (Lawsonia intracellularis) in BMC GENOMICS
  • 2016-03-22. EPIG-Seq: extracting patterns and identifying co-expressed genes from RNA-Seq data in BMC GENOMICS
  • 2015-03-09. HISAT: a fast spliced aligner with low memory requirements in NATURE METHODS
  • 2016-09-23. Analysis RNA-seq and Noncoding RNA in POLYCOMB GROUP PROTEINS
  • 2014-08-24. Normalization of RNA-seq data using factor analysis of control genes or samples in NATURE BIOTECHNOLOGY
  • 2018-09-10. SMRT-Cappable-seq reveals complex operon variants in bacteria in NATURE COMMUNICATIONS
  • 2012-08-14. Dual RNA-seq of pathogen and host in NATURE REVIEWS MICROBIOLOGY
  • 2014-06-02. Comparison of RNA-Seq by poly (A) capture, ribosomal RNA depletion, and DNA microarray for expression profiling in BMC GENOMICS
  • 2008-05-30. Mapping and quantifying mammalian transcriptomes by RNA-Seq in NATURE METHODS
  • 2019-04-08. Coordinated host-pathogen transcriptional dynamics revealed using sorted subpopulations and single macrophages infected with Candida albicans in NATURE COMMUNICATIONS
  • 2020-05-25. Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing in NATURE MICROBIOLOGY
  • 2009-03-04. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome in GENOME BIOLOGY
  • 2016-07-21. A highly multiplexed and sensitive RNA-seq protocol for simultaneous analysis of host and pathogen transcriptomes in NATURE PROTOCOLS
  • 2013-10-24. Integrated transcriptomic and proteomic analysis of the global response of Wolbachia to doxycycline-induced stress in THE ISME JOURNAL: MULTIDISCIPLINARY JOURNAL OF MICROBIAL ECOLOGY
  • 2016-01-20. Dual RNA-seq unveils noncoding RNA functions in host–pathogen interactions in NATURE
  • 2015-02-05. Comprehensive insights into transcriptional adaptation of intracellular mycobacteria by microbe-enriched dual RNA sequencing in BMC GENOMICS
  • 2016-01-26. A survey of best practices for RNA-seq data analysis in GENOME BIOLOGY
  • 2014-11-18. RNA-sequencing reveals early, dynamic transcriptome changes in the corollas of pollinated petunias in BMC PLANT BIOLOGY
  • 2008-12-18. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources in NATURE PROTOCOLS
  • 2017-03-06. Salmon provides fast and bias-aware quantification of transcript expression in NATURE METHODS
  • 2009-05-29. PANTHER Pathway: An Ontology-Based Pathway Database Coupled with Data Analysis Tools in PROTEIN NETWORKS AND PATHWAY ANALYSIS
  • 2019-11-28. Improved metagenomic analysis with Kraken 2 in GENOME BIOLOGY
  • 2014-12-05. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 in GENOME BIOLOGY
  • 2000-05. Gene Ontology: tool for the unification of biology in NATURE GENETICS
  • 2018-09-06. Targeted enrichment outperforms other enrichment techniques and enables more multi-species RNA-Seq analyses in SCIENTIFIC REPORTS
  • 2017-06-16. Single-cell multi-omics sequencing of mouse early embryos and embryonic stem cells in CELL RESEARCH
  • 2015-07-27. Efficient and quantitative high-throughput tRNA sequencing in NATURE METHODS
  • 2010-10-10. De novo assembly and analysis of RNA-seq data in NATURE METHODS
  • 2013-01-01. Streaming fragment assignment for real-time analysis of sequencing experiments in NATURE METHODS
  • 2008-12-29. WGCNA: an R package for weighted correlation network analysis in BMC BIOINFORMATICS
  • 2014-07-28. Pervasive transcription: illuminating the dark matter of bacterial transcriptomes in NATURE REVIEWS MICROBIOLOGY
  • 2011-08-04. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome in BMC BIOINFORMATICS
  • 2020-05-11. ORF Capture-Seq as a versatile method for targeted identification of full-length isoforms in NATURE COMMUNICATIONS
  • 2009-04-06. mRNA-Seq whole-transcriptome analysis of a single cell in NATURE METHODS
  • 2016-10-10. FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies in BMC BIOINFORMATICS
  • 2010-03-02. A scaling normalization method for differential expression analysis of RNA-seq data in GENOME BIOLOGY
  • 2012-08-08. Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples in THEORY IN BIOSCIENCES
  • 2017-06-05. Differential analysis of RNA-seq incorporating quantification uncertainty in NATURE METHODS
  • 2016-11-14. Single-cell RNA-seq ties macrophage polarization to growth rate of intracellular Salmonella in NATURE MICROBIOLOGY
  • 2020-09-07. Alignment and mapping methodology influence transcript abundance estimation in GENOME BIOLOGY
  • 2012-03-01. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks in NATURE PROTOCOLS
  • 2017-07-26. Comparative analysis of targeted long read sequencing approaches for characterization of a plant’s immune receptor repertoire in BMC GENOMICS
  • 2011-06-24. Metagenomic biomarker discovery and explanation in GENOME BIOLOGY
  • 2010-10-27. Differential expression analysis for sequence count data in GENOME BIOLOGY
  • 2018-10-30. Species-level functional profiling of metagenomes and metatranscriptomes in NATURE METHODS
  • 2014-04-20. Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms in NATURE BIOTECHNOLOGY
  • 2005-12. How does gene expression clustering work? in NATURE BIOTECHNOLOGY
  • 2011-05-15. Full-length transcriptome assembly from RNA-Seq data without a reference genome in NATURE BIOTECHNOLOGY
  • 2016-03-10. Integrated analysis of mRNA-seq and miRNA-seq in the liver of Pelteobagrus vachelli in response to hypoxia in SCIENTIFIC REPORTS
  • 2016-06-24. Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing in NATURE COMMUNICATIONS
  • 2016-05-23. MetaTrans: an open-source pipeline for metatranscriptomics in SCIENTIFIC REPORTS
  • 2019-12-17. Hybridization-based capture of pathogen mRNA enables paired host-pathogen transcriptional analysis in SCIENTIFIC REPORTS
  • 2018-08-07. Single-cell RNA sequencing technologies and bioinformatics pipelines in EXPERIMENTAL & MOLECULAR MEDICINE
  • 2016-08-26. Erratum to: A survey of best practices for RNA-seq data analysis in GENOME BIOLOGY
  • 2013-11-01. Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories in NATURE BIOTECHNOLOGY
  • 2016-04-04. Near-optimal probabilistic RNA-seq quantification in NATURE BIOTECHNOLOGY
  • 2017-10-27. scDual-Seq: mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing in GENOME BIOLOGY
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13059-021-02337-8

    DOI

    http://dx.doi.org/10.1186/s13059-021-02337-8

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1137601313

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/33926528


    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/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Animals", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Eukaryota", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Regulation", 
            "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": "Organ Specificity", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Prokaryotic Cells", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "RNA-Seq", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "ROC Curve", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Sequence Alignment", 
            "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": "Transcriptome", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Workflow", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
                "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chung", 
            "givenName": "Matthew", 
            "id": "sg:person.012050420627.26", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012050420627.26"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
                "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Bruno", 
            "givenName": "Vincent M.", 
            "id": "sg:person.01312736150.36", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01312736150.36"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
                "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Rasko", 
            "givenName": "David A.", 
            "id": "sg:person.01223251575.74", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223251575.74"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA", 
              "id": "http://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cuomo", 
            "givenName": "Christina A.", 
            "id": "sg:person.01350413270.48", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350413270.48"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA", 
              "id": "http://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Mu\u00f1oz", 
            "givenName": "Jos\u00e9 F.", 
            "id": "sg:person.0624221250.40", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624221250.40"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA", 
              "id": "http://www.grid.ac/institutes/grid.66859.34", 
              "name": [
                "Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Livny", 
            "givenName": "Jonathan", 
            "id": "sg:person.01213752162.55", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213752162.55"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Shetty", 
            "givenName": "Amol C.", 
            "id": "sg:person.0705703554.98", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705703554.98"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Mahurkar", 
            "givenName": "Anup", 
            "id": "sg:person.01051370761.80", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051370761.80"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Greenebaum Cancer Center, University of Maryland, 21201, Baltimore, MD, USA", 
              "id": "http://www.grid.ac/institutes/grid.411024.2", 
              "name": [
                "Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
                "Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA", 
                "Greenebaum Cancer Center, University of Maryland, 21201, Baltimore, MD, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Dunning Hotopp", 
            "givenName": "Julie C.", 
            "id": "sg:person.01322263734.83", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322263734.83"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1007/s12064-012-0162-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036112334", 
              "https://doi.org/10.1007/s12064-012-0162-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-019-1891-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1122989517", 
              "https://doi.org/10.1186/s13059-019-1891-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2010-11-3-r25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050509557", 
              "https://doi.org/10.1186/gb-2010-11-3-r25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1226", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045381177", 
              "https://doi.org/10.1038/nmeth.1226"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-019-09599-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1113300670", 
              "https://doi.org/10.1038/s41467-019-09599-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep22907", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042013127", 
              "https://doi.org/10.1038/srep22907"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4939-6380-5_11", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037644206", 
              "https://doi.org/10.1007/978-1-4939-6380-5_11"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12870-014-0307-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032145961", 
              "https://doi.org/10.1186/s12870-014-0307-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ismej.2013.192", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1013190382", 
              "https://doi.org/10.1038/ismej.2013.192"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-60761-175-2_7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021693998", 
              "https://doi.org/10.1007/978-1-60761-175-2_7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2702", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010194085", 
              "https://doi.org/10.1038/nbt.2702"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2862", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011219673", 
              "https://doi.org/10.1038/nbt.2862"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.4197", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084129290", 
              "https://doi.org/10.1038/nmeth.4197"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2009-10-3-r25", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049583368", 
              "https://doi.org/10.1186/gb-2009-10-3-r25"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1205-1499", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030341885", 
              "https://doi.org/10.1038/nbt1205-1499"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-15-419", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1025871035", 
              "https://doi.org/10.1186/1471-2164-15-419"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-1047-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004627047", 
              "https://doi.org/10.1186/s13059-016-1047-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-020-16174-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1127502992", 
              "https://doi.org/10.1038/s41467-020-16174-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep26447", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020336652", 
              "https://doi.org/10.1038/srep26447"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-016-2584-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048648223", 
              "https://doi.org/10.1186/s12864-016-2584-7"
            ], 
            "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": "sg:pub.10.1038/s41598-018-31420-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106476094", 
              "https://doi.org/10.1038/s41598-018-31420-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrmicro3316", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1029996988", 
              "https://doi.org/10.1038/nrmicro3316"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41592-018-0176-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1107804224", 
              "https://doi.org/10.1038/s41592-018-0176-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41564-020-0729-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1127865871", 
              "https://doi.org/10.1038/s41564-020-0729-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.3519", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024493480", 
              "https://doi.org/10.1038/nbt.3519"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1517", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1032102367", 
              "https://doi.org/10.1038/nmeth.1517"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-14-421", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021521343", 
              "https://doi.org/10.1186/1471-2164-14-421"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncomms11708", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028468515", 
              "https://doi.org/10.1038/ncomms11708"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-014-0550-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015222646", 
              "https://doi.org/10.1186/s13059-014-0550-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/cr.2017.82", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086046809", 
              "https://doi.org/10.1038/cr.2017.82"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-017-3936-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1090895465", 
              "https://doi.org/10.1186/s12864-017-3936-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-020-02151-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1130649820", 
              "https://doi.org/10.1186/s13059-020-02151-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/75556", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044135237", 
              "https://doi.org/10.1038/75556"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.1883", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015803168", 
              "https://doi.org/10.1038/nbt.1883"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4939-7634-8_4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101222807", 
              "https://doi.org/10.1007/978-1-4939-7634-8_4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s12276-018-0071-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106053598", 
              "https://doi.org/10.1038/s12276-018-0071-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmicrobiol.2016.206", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008457589", 
              "https://doi.org/10.1038/nmicrobiol.2016.206"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2008.211", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1039987283", 
              "https://doi.org/10.1038/nprot.2008.211"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41598-019-55633-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1123464538", 
              "https://doi.org/10.1038/s41598-019-55633-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt.2931", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008162673", 
              "https://doi.org/10.1038/nbt.2931"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrmicro2852", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1026729568", 
              "https://doi.org/10.1038/nrmicro2852"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature16547", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043653044", 
              "https://doi.org/10.1038/nature16547"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.1315", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022155307", 
              "https://doi.org/10.1038/nmeth.1315"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2012.016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030124536", 
              "https://doi.org/10.1038/nprot.2012.016"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.4324", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1085864685", 
              "https://doi.org/10.1038/nmeth.4324"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep34850", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044909774", 
              "https://doi.org/10.1038/srep34850"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-017-1340-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1092409644", 
              "https://doi.org/10.1186/s13059-017-1340-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.2251", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016190409", 
              "https://doi.org/10.1038/nmeth.2251"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12864-014-1197-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1040804903", 
              "https://doi.org/10.1186/s12864-014-1197-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12859-016-1278-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037408767", 
              "https://doi.org/10.1186/s12859-016-1278-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2105-9-559", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020312314", 
              "https://doi.org/10.1186/1471-2105-9-559"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nprot.2016.090", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038936999", 
              "https://doi.org/10.1038/nprot.2016.090"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-018-05997-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1106681124", 
              "https://doi.org/10.1038/s41467-018-05997-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s13059-016-0881-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041902478", 
              "https://doi.org/10.1186/s13059-016-0881-8"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2011-12-6-r60", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000243423", 
              "https://doi.org/10.1186/gb-2011-12-6-r60"
            ], 
            "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": "sg:pub.10.1038/nmeth.3478", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045590675", 
              "https://doi.org/10.1038/nmeth.3478"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nmeth.3317", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005140994", 
              "https://doi.org/10.1038/nmeth.3317"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2021-04-29", 
        "datePublishedReg": "2021-04-29", 
        "description": "Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.", 
        "genre": "article", 
        "id": "sg:pub.10.1186/s13059-021-02337-8", 
        "inLanguage": "en", 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.3535018", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3535398", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1023439", 
            "issn": [
              "1474-760X", 
              "1465-6906"
            ], 
            "name": "Genome Biology", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "22"
          }
        ], 
        "keywords": [
          "differential expression analysis", 
          "expression analysis", 
          "differential gene expression", 
          "total read counts", 
          "downstream analysis steps", 
          "organism of interest", 
          "differential expression experiments", 
          "transcriptome sequencing", 
          "RNA-seq", 
          "transcriptomic datasets", 
          "single RNA sample", 
          "expression experiments", 
          "gene expression", 
          "multiple species", 
          "read counts", 
          "relative abundance", 
          "RNA samples", 
          "transcriptomics", 
          "analysis pipeline", 
          "enrichment method", 
          "simultaneous interrogation", 
          "genes", 
          "organisms", 
          "sequencing", 
          "species", 
          "abundance", 
          "expression", 
          "analysis", 
          "modification", 
          "interrogation", 
          "analysis steps", 
          "advances", 
          "alignment", 
          "pipeline", 
          "quantification", 
          "step", 
          "samples", 
          "experiments", 
          "dataset", 
          "differences", 
          "interest", 
          "count", 
          "method", 
          "design", 
          "practice", 
          "best practices"
        ], 
        "name": "Best practices on the differential expression analysis of multi-species RNA-seq", 
        "pagination": "121", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1137601313"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/s13059-021-02337-8"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "33926528"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/s13059-021-02337-8", 
          "https://app.dimensions.ai/details/publication/pub.1137601313"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-06-01T22:25", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_917.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1186/s13059-021-02337-8"
      }
    ]
     

    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/s13059-021-02337-8'

    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/s13059-021-02337-8'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13059-021-02337-8'

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

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13059-021-02337-8'


     

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

    475 TRIPLES      22 PREDICATES      147 URIs      80 LITERALS      23 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/s13059-021-02337-8 schema:about N2e2a7190a90b489faea3daa184c8a6ae
    2 N2f6f070e1d6b48ba889f262f05c6c731
    3 N3fb2b3a614a44352bcefaf34973c27d4
    4 N4479755edd2343c1a763ab3b4a0b5998
    5 N4e660786667e4ddc8f805c1f28d32623
    6 N51b39c338fa94dd2901cc3d0680ec158
    7 N52df6074ffb241709e678608a7a64a67
    8 N75ac57fd98c240b5b6cc4ff7af306770
    9 N89bd3bcd9a724a9bb0a093ca71dc9711
    10 N8be77de5d10841faaeb78709d98c7b8a
    11 Nb78e090ee4224f7cb19275a53c5572e7
    12 Nba33386e7d46441f84459349e56a0bc5
    13 Nc8ee5613363b45a19da95e98c042a936
    14 Nd3dd71b8d4fc4b26994d8148a7dd7c85
    15 Nd8ee5b33cdf14c479a04b48c6b59f3cc
    16 Nd980a7aaa8e7440d9296cb6cca9b57bf
    17 anzsrc-for:06
    18 anzsrc-for:0604
    19 schema:author N2a70ab17c2a941b786c36ba3885997a8
    20 schema:citation sg:pub.10.1007/978-1-4939-6380-5_11
    21 sg:pub.10.1007/978-1-4939-7634-8_4
    22 sg:pub.10.1007/978-1-60761-175-2_7
    23 sg:pub.10.1007/s12064-012-0162-3
    24 sg:pub.10.1038/75556
    25 sg:pub.10.1038/cr.2017.82
    26 sg:pub.10.1038/ismej.2013.192
    27 sg:pub.10.1038/nature16547
    28 sg:pub.10.1038/nbt.1883
    29 sg:pub.10.1038/nbt.2702
    30 sg:pub.10.1038/nbt.2862
    31 sg:pub.10.1038/nbt.2931
    32 sg:pub.10.1038/nbt.3519
    33 sg:pub.10.1038/nbt1205-1499
    34 sg:pub.10.1038/ncomms11708
    35 sg:pub.10.1038/nmeth.1226
    36 sg:pub.10.1038/nmeth.1315
    37 sg:pub.10.1038/nmeth.1517
    38 sg:pub.10.1038/nmeth.2251
    39 sg:pub.10.1038/nmeth.3317
    40 sg:pub.10.1038/nmeth.3478
    41 sg:pub.10.1038/nmeth.4197
    42 sg:pub.10.1038/nmeth.4324
    43 sg:pub.10.1038/nmicrobiol.2016.206
    44 sg:pub.10.1038/nprot.2008.211
    45 sg:pub.10.1038/nprot.2012.016
    46 sg:pub.10.1038/nprot.2016.090
    47 sg:pub.10.1038/nrmicro2852
    48 sg:pub.10.1038/nrmicro3316
    49 sg:pub.10.1038/s12276-018-0071-8
    50 sg:pub.10.1038/s41467-018-05997-6
    51 sg:pub.10.1038/s41467-019-09599-8
    52 sg:pub.10.1038/s41467-020-16174-z
    53 sg:pub.10.1038/s41564-020-0729-6
    54 sg:pub.10.1038/s41592-018-0176-y
    55 sg:pub.10.1038/s41598-018-31420-7
    56 sg:pub.10.1038/s41598-019-55633-6
    57 sg:pub.10.1038/srep22907
    58 sg:pub.10.1038/srep26447
    59 sg:pub.10.1038/srep34850
    60 sg:pub.10.1186/1471-2105-12-323
    61 sg:pub.10.1186/1471-2105-9-559
    62 sg:pub.10.1186/1471-2164-14-421
    63 sg:pub.10.1186/1471-2164-15-419
    64 sg:pub.10.1186/gb-2009-10-3-r25
    65 sg:pub.10.1186/gb-2010-11-10-r106
    66 sg:pub.10.1186/gb-2010-11-3-r25
    67 sg:pub.10.1186/gb-2011-12-6-r60
    68 sg:pub.10.1186/s12859-016-1278-0
    69 sg:pub.10.1186/s12864-014-1197-2
    70 sg:pub.10.1186/s12864-016-2584-7
    71 sg:pub.10.1186/s12864-017-3936-7
    72 sg:pub.10.1186/s12870-014-0307-2
    73 sg:pub.10.1186/s13059-014-0550-8
    74 sg:pub.10.1186/s13059-016-0881-8
    75 sg:pub.10.1186/s13059-016-1047-4
    76 sg:pub.10.1186/s13059-017-1340-x
    77 sg:pub.10.1186/s13059-019-1891-0
    78 sg:pub.10.1186/s13059-020-02151-8
    79 schema:datePublished 2021-04-29
    80 schema:datePublishedReg 2021-04-29
    81 schema:description Advances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.
    82 schema:genre article
    83 schema:inLanguage en
    84 schema:isAccessibleForFree true
    85 schema:isPartOf N6233dc7f35bc4f27b2ab2b8faf25c82d
    86 Na314c27ab4034c929fb389d3816bbd39
    87 sg:journal.1023439
    88 schema:keywords RNA samples
    89 RNA-seq
    90 abundance
    91 advances
    92 alignment
    93 analysis
    94 analysis pipeline
    95 analysis steps
    96 best practices
    97 count
    98 dataset
    99 design
    100 differences
    101 differential expression analysis
    102 differential expression experiments
    103 differential gene expression
    104 downstream analysis steps
    105 enrichment method
    106 experiments
    107 expression
    108 expression analysis
    109 expression experiments
    110 gene expression
    111 genes
    112 interest
    113 interrogation
    114 method
    115 modification
    116 multiple species
    117 organism of interest
    118 organisms
    119 pipeline
    120 practice
    121 quantification
    122 read counts
    123 relative abundance
    124 samples
    125 sequencing
    126 simultaneous interrogation
    127 single RNA sample
    128 species
    129 step
    130 total read counts
    131 transcriptome sequencing
    132 transcriptomic datasets
    133 transcriptomics
    134 schema:name Best practices on the differential expression analysis of multi-species RNA-seq
    135 schema:pagination 121
    136 schema:productId N4c41d2e6963a4f279b612b4671d1673d
    137 Na8aac68295c245efa9409591f979ab7f
    138 Nbf25150db21d4ae8baeb7f449a97e9a0
    139 schema:sameAs https://app.dimensions.ai/details/publication/pub.1137601313
    140 https://doi.org/10.1186/s13059-021-02337-8
    141 schema:sdDatePublished 2022-06-01T22:25
    142 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    143 schema:sdPublisher N292830f5f0334791b568beae38b9b517
    144 schema:url https://doi.org/10.1186/s13059-021-02337-8
    145 sgo:license sg:explorer/license/
    146 sgo:sdDataset articles
    147 rdf:type schema:ScholarlyArticle
    148 N292830f5f0334791b568beae38b9b517 schema:name Springer Nature - SN SciGraph project
    149 rdf:type schema:Organization
    150 N2a70ab17c2a941b786c36ba3885997a8 rdf:first sg:person.012050420627.26
    151 rdf:rest N5a6604e8d764453b8f31f40d6ef4a1ab
    152 N2e2a7190a90b489faea3daa184c8a6ae schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    153 schema:name Sequence Analysis, RNA
    154 rdf:type schema:DefinedTerm
    155 N2f6f070e1d6b48ba889f262f05c6c731 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    156 schema:name Transcriptome
    157 rdf:type schema:DefinedTerm
    158 N30022103398a4f7ead2ef8be662c8d4b rdf:first sg:person.0624221250.40
    159 rdf:rest Ndd33e58d55b54134abd0ef7750236ce3
    160 N3735d51049c04a4084c1226a2d7bc40f rdf:first sg:person.01350413270.48
    161 rdf:rest N30022103398a4f7ead2ef8be662c8d4b
    162 N3fb2b3a614a44352bcefaf34973c27d4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    163 schema:name ROC Curve
    164 rdf:type schema:DefinedTerm
    165 N4479755edd2343c1a763ab3b4a0b5998 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    166 schema:name Organ Specificity
    167 rdf:type schema:DefinedTerm
    168 N4b1d0e2bb9c348f18696c485e110415c rdf:first sg:person.01223251575.74
    169 rdf:rest N3735d51049c04a4084c1226a2d7bc40f
    170 N4c41d2e6963a4f279b612b4671d1673d schema:name pubmed_id
    171 schema:value 33926528
    172 rdf:type schema:PropertyValue
    173 N4e660786667e4ddc8f805c1f28d32623 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    174 schema:name Sequence Alignment
    175 rdf:type schema:DefinedTerm
    176 N51b39c338fa94dd2901cc3d0680ec158 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    177 schema:name Animals
    178 rdf:type schema:DefinedTerm
    179 N51f53555a58846958ef7fb426fc75433 rdf:first sg:person.01051370761.80
    180 rdf:rest N713d1700b1744b6e82522f5ec6f65c8e
    181 N52df6074ffb241709e678608a7a64a67 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    182 schema:name Workflow
    183 rdf:type schema:DefinedTerm
    184 N5a6604e8d764453b8f31f40d6ef4a1ab rdf:first sg:person.01312736150.36
    185 rdf:rest N4b1d0e2bb9c348f18696c485e110415c
    186 N6233dc7f35bc4f27b2ab2b8faf25c82d schema:issueNumber 1
    187 rdf:type schema:PublicationIssue
    188 N713d1700b1744b6e82522f5ec6f65c8e rdf:first sg:person.01322263734.83
    189 rdf:rest rdf:nil
    190 N75ac57fd98c240b5b6cc4ff7af306770 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    191 schema:name Gene Expression Regulation
    192 rdf:type schema:DefinedTerm
    193 N89bd3bcd9a724a9bb0a093ca71dc9711 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    194 schema:name Single-Cell Analysis
    195 rdf:type schema:DefinedTerm
    196 N8be77de5d10841faaeb78709d98c7b8a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    197 schema:name Gene Expression Profiling
    198 rdf:type schema:DefinedTerm
    199 Na314c27ab4034c929fb389d3816bbd39 schema:volumeNumber 22
    200 rdf:type schema:PublicationVolume
    201 Na8aac68295c245efa9409591f979ab7f schema:name dimensions_id
    202 schema:value pub.1137601313
    203 rdf:type schema:PropertyValue
    204 Nb78e090ee4224f7cb19275a53c5572e7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    205 schema:name RNA
    206 rdf:type schema:DefinedTerm
    207 Nba33386e7d46441f84459349e56a0bc5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    208 schema:name High-Throughput Nucleotide Sequencing
    209 rdf:type schema:DefinedTerm
    210 Nbf25150db21d4ae8baeb7f449a97e9a0 schema:name doi
    211 schema:value 10.1186/s13059-021-02337-8
    212 rdf:type schema:PropertyValue
    213 Nc8ee5613363b45a19da95e98c042a936 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    214 schema:name Humans
    215 rdf:type schema:DefinedTerm
    216 Nd3dd71b8d4fc4b26994d8148a7dd7c85 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    217 schema:name RNA-Seq
    218 rdf:type schema:DefinedTerm
    219 Nd8ee5b33cdf14c479a04b48c6b59f3cc schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    220 schema:name Prokaryotic Cells
    221 rdf:type schema:DefinedTerm
    222 Nd980a7aaa8e7440d9296cb6cca9b57bf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    223 schema:name Eukaryota
    224 rdf:type schema:DefinedTerm
    225 Ndd33e58d55b54134abd0ef7750236ce3 rdf:first sg:person.01213752162.55
    226 rdf:rest Ndfd6cb0961cd4ef2a4ff7d96bf57cc49
    227 Ndfd6cb0961cd4ef2a4ff7d96bf57cc49 rdf:first sg:person.0705703554.98
    228 rdf:rest N51f53555a58846958ef7fb426fc75433
    229 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    230 schema:name Biological Sciences
    231 rdf:type schema:DefinedTerm
    232 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    233 schema:name Genetics
    234 rdf:type schema:DefinedTerm
    235 sg:grant.3535018 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-021-02337-8
    236 rdf:type schema:MonetaryGrant
    237 sg:grant.3535398 http://pending.schema.org/fundedItem sg:pub.10.1186/s13059-021-02337-8
    238 rdf:type schema:MonetaryGrant
    239 sg:journal.1023439 schema:issn 1465-6906
    240 1474-760X
    241 schema:name Genome Biology
    242 schema:publisher Springer Nature
    243 rdf:type schema:Periodical
    244 sg:person.01051370761.80 schema:affiliation grid-institutes:grid.411024.2
    245 schema:familyName Mahurkar
    246 schema:givenName Anup
    247 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01051370761.80
    248 rdf:type schema:Person
    249 sg:person.012050420627.26 schema:affiliation grid-institutes:grid.411024.2
    250 schema:familyName Chung
    251 schema:givenName Matthew
    252 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012050420627.26
    253 rdf:type schema:Person
    254 sg:person.01213752162.55 schema:affiliation grid-institutes:grid.66859.34
    255 schema:familyName Livny
    256 schema:givenName Jonathan
    257 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01213752162.55
    258 rdf:type schema:Person
    259 sg:person.01223251575.74 schema:affiliation grid-institutes:grid.411024.2
    260 schema:familyName Rasko
    261 schema:givenName David A.
    262 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01223251575.74
    263 rdf:type schema:Person
    264 sg:person.01312736150.36 schema:affiliation grid-institutes:grid.411024.2
    265 schema:familyName Bruno
    266 schema:givenName Vincent M.
    267 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01312736150.36
    268 rdf:type schema:Person
    269 sg:person.01322263734.83 schema:affiliation grid-institutes:grid.411024.2
    270 schema:familyName Dunning Hotopp
    271 schema:givenName Julie C.
    272 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01322263734.83
    273 rdf:type schema:Person
    274 sg:person.01350413270.48 schema:affiliation grid-institutes:grid.66859.34
    275 schema:familyName Cuomo
    276 schema:givenName Christina A.
    277 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01350413270.48
    278 rdf:type schema:Person
    279 sg:person.0624221250.40 schema:affiliation grid-institutes:grid.66859.34
    280 schema:familyName Muñoz
    281 schema:givenName José F.
    282 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0624221250.40
    283 rdf:type schema:Person
    284 sg:person.0705703554.98 schema:affiliation grid-institutes:grid.411024.2
    285 schema:familyName Shetty
    286 schema:givenName Amol C.
    287 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0705703554.98
    288 rdf:type schema:Person
    289 sg:pub.10.1007/978-1-4939-6380-5_11 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037644206
    290 https://doi.org/10.1007/978-1-4939-6380-5_11
    291 rdf:type schema:CreativeWork
    292 sg:pub.10.1007/978-1-4939-7634-8_4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101222807
    293 https://doi.org/10.1007/978-1-4939-7634-8_4
    294 rdf:type schema:CreativeWork
    295 sg:pub.10.1007/978-1-60761-175-2_7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021693998
    296 https://doi.org/10.1007/978-1-60761-175-2_7
    297 rdf:type schema:CreativeWork
    298 sg:pub.10.1007/s12064-012-0162-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036112334
    299 https://doi.org/10.1007/s12064-012-0162-3
    300 rdf:type schema:CreativeWork
    301 sg:pub.10.1038/75556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044135237
    302 https://doi.org/10.1038/75556
    303 rdf:type schema:CreativeWork
    304 sg:pub.10.1038/cr.2017.82 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086046809
    305 https://doi.org/10.1038/cr.2017.82
    306 rdf:type schema:CreativeWork
    307 sg:pub.10.1038/ismej.2013.192 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013190382
    308 https://doi.org/10.1038/ismej.2013.192
    309 rdf:type schema:CreativeWork
    310 sg:pub.10.1038/nature16547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043653044
    311 https://doi.org/10.1038/nature16547
    312 rdf:type schema:CreativeWork
    313 sg:pub.10.1038/nbt.1883 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015803168
    314 https://doi.org/10.1038/nbt.1883
    315 rdf:type schema:CreativeWork
    316 sg:pub.10.1038/nbt.2702 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010194085
    317 https://doi.org/10.1038/nbt.2702
    318 rdf:type schema:CreativeWork
    319 sg:pub.10.1038/nbt.2862 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011219673
    320 https://doi.org/10.1038/nbt.2862
    321 rdf:type schema:CreativeWork
    322 sg:pub.10.1038/nbt.2931 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008162673
    323 https://doi.org/10.1038/nbt.2931
    324 rdf:type schema:CreativeWork
    325 sg:pub.10.1038/nbt.3519 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024493480
    326 https://doi.org/10.1038/nbt.3519
    327 rdf:type schema:CreativeWork
    328 sg:pub.10.1038/nbt1205-1499 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030341885
    329 https://doi.org/10.1038/nbt1205-1499
    330 rdf:type schema:CreativeWork
    331 sg:pub.10.1038/ncomms11708 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028468515
    332 https://doi.org/10.1038/ncomms11708
    333 rdf:type schema:CreativeWork
    334 sg:pub.10.1038/nmeth.1226 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045381177
    335 https://doi.org/10.1038/nmeth.1226
    336 rdf:type schema:CreativeWork
    337 sg:pub.10.1038/nmeth.1315 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022155307
    338 https://doi.org/10.1038/nmeth.1315
    339 rdf:type schema:CreativeWork
    340 sg:pub.10.1038/nmeth.1517 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032102367
    341 https://doi.org/10.1038/nmeth.1517
    342 rdf:type schema:CreativeWork
    343 sg:pub.10.1038/nmeth.2251 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016190409
    344 https://doi.org/10.1038/nmeth.2251
    345 rdf:type schema:CreativeWork
    346 sg:pub.10.1038/nmeth.3317 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005140994
    347 https://doi.org/10.1038/nmeth.3317
    348 rdf:type schema:CreativeWork
    349 sg:pub.10.1038/nmeth.3478 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045590675
    350 https://doi.org/10.1038/nmeth.3478
    351 rdf:type schema:CreativeWork
    352 sg:pub.10.1038/nmeth.4197 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084129290
    353 https://doi.org/10.1038/nmeth.4197
    354 rdf:type schema:CreativeWork
    355 sg:pub.10.1038/nmeth.4324 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085864685
    356 https://doi.org/10.1038/nmeth.4324
    357 rdf:type schema:CreativeWork
    358 sg:pub.10.1038/nmicrobiol.2016.206 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008457589
    359 https://doi.org/10.1038/nmicrobiol.2016.206
    360 rdf:type schema:CreativeWork
    361 sg:pub.10.1038/nprot.2008.211 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039987283
    362 https://doi.org/10.1038/nprot.2008.211
    363 rdf:type schema:CreativeWork
    364 sg:pub.10.1038/nprot.2012.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030124536
    365 https://doi.org/10.1038/nprot.2012.016
    366 rdf:type schema:CreativeWork
    367 sg:pub.10.1038/nprot.2016.090 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038936999
    368 https://doi.org/10.1038/nprot.2016.090
    369 rdf:type schema:CreativeWork
    370 sg:pub.10.1038/nrmicro2852 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026729568
    371 https://doi.org/10.1038/nrmicro2852
    372 rdf:type schema:CreativeWork
    373 sg:pub.10.1038/nrmicro3316 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029996988
    374 https://doi.org/10.1038/nrmicro3316
    375 rdf:type schema:CreativeWork
    376 sg:pub.10.1038/s12276-018-0071-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106053598
    377 https://doi.org/10.1038/s12276-018-0071-8
    378 rdf:type schema:CreativeWork
    379 sg:pub.10.1038/s41467-018-05997-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106681124
    380 https://doi.org/10.1038/s41467-018-05997-6
    381 rdf:type schema:CreativeWork
    382 sg:pub.10.1038/s41467-019-09599-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1113300670
    383 https://doi.org/10.1038/s41467-019-09599-8
    384 rdf:type schema:CreativeWork
    385 sg:pub.10.1038/s41467-020-16174-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1127502992
    386 https://doi.org/10.1038/s41467-020-16174-z
    387 rdf:type schema:CreativeWork
    388 sg:pub.10.1038/s41564-020-0729-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127865871
    389 https://doi.org/10.1038/s41564-020-0729-6
    390 rdf:type schema:CreativeWork
    391 sg:pub.10.1038/s41592-018-0176-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1107804224
    392 https://doi.org/10.1038/s41592-018-0176-y
    393 rdf:type schema:CreativeWork
    394 sg:pub.10.1038/s41598-018-31420-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1106476094
    395 https://doi.org/10.1038/s41598-018-31420-7
    396 rdf:type schema:CreativeWork
    397 sg:pub.10.1038/s41598-019-55633-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1123464538
    398 https://doi.org/10.1038/s41598-019-55633-6
    399 rdf:type schema:CreativeWork
    400 sg:pub.10.1038/srep22907 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042013127
    401 https://doi.org/10.1038/srep22907
    402 rdf:type schema:CreativeWork
    403 sg:pub.10.1038/srep26447 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020336652
    404 https://doi.org/10.1038/srep26447
    405 rdf:type schema:CreativeWork
    406 sg:pub.10.1038/srep34850 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044909774
    407 https://doi.org/10.1038/srep34850
    408 rdf:type schema:CreativeWork
    409 sg:pub.10.1186/1471-2105-12-323 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021902674
    410 https://doi.org/10.1186/1471-2105-12-323
    411 rdf:type schema:CreativeWork
    412 sg:pub.10.1186/1471-2105-9-559 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020312314
    413 https://doi.org/10.1186/1471-2105-9-559
    414 rdf:type schema:CreativeWork
    415 sg:pub.10.1186/1471-2164-14-421 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021521343
    416 https://doi.org/10.1186/1471-2164-14-421
    417 rdf:type schema:CreativeWork
    418 sg:pub.10.1186/1471-2164-15-419 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025871035
    419 https://doi.org/10.1186/1471-2164-15-419
    420 rdf:type schema:CreativeWork
    421 sg:pub.10.1186/gb-2009-10-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049583368
    422 https://doi.org/10.1186/gb-2009-10-3-r25
    423 rdf:type schema:CreativeWork
    424 sg:pub.10.1186/gb-2010-11-10-r106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031289083
    425 https://doi.org/10.1186/gb-2010-11-10-r106
    426 rdf:type schema:CreativeWork
    427 sg:pub.10.1186/gb-2010-11-3-r25 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050509557
    428 https://doi.org/10.1186/gb-2010-11-3-r25
    429 rdf:type schema:CreativeWork
    430 sg:pub.10.1186/gb-2011-12-6-r60 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000243423
    431 https://doi.org/10.1186/gb-2011-12-6-r60
    432 rdf:type schema:CreativeWork
    433 sg:pub.10.1186/s12859-016-1278-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037408767
    434 https://doi.org/10.1186/s12859-016-1278-0
    435 rdf:type schema:CreativeWork
    436 sg:pub.10.1186/s12864-014-1197-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040804903
    437 https://doi.org/10.1186/s12864-014-1197-2
    438 rdf:type schema:CreativeWork
    439 sg:pub.10.1186/s12864-016-2584-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048648223
    440 https://doi.org/10.1186/s12864-016-2584-7
    441 rdf:type schema:CreativeWork
    442 sg:pub.10.1186/s12864-017-3936-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1090895465
    443 https://doi.org/10.1186/s12864-017-3936-7
    444 rdf:type schema:CreativeWork
    445 sg:pub.10.1186/s12870-014-0307-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032145961
    446 https://doi.org/10.1186/s12870-014-0307-2
    447 rdf:type schema:CreativeWork
    448 sg:pub.10.1186/s13059-014-0550-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015222646
    449 https://doi.org/10.1186/s13059-014-0550-8
    450 rdf:type schema:CreativeWork
    451 sg:pub.10.1186/s13059-016-0881-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041902478
    452 https://doi.org/10.1186/s13059-016-0881-8
    453 rdf:type schema:CreativeWork
    454 sg:pub.10.1186/s13059-016-1047-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004627047
    455 https://doi.org/10.1186/s13059-016-1047-4
    456 rdf:type schema:CreativeWork
    457 sg:pub.10.1186/s13059-017-1340-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1092409644
    458 https://doi.org/10.1186/s13059-017-1340-x
    459 rdf:type schema:CreativeWork
    460 sg:pub.10.1186/s13059-019-1891-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1122989517
    461 https://doi.org/10.1186/s13059-019-1891-0
    462 rdf:type schema:CreativeWork
    463 sg:pub.10.1186/s13059-020-02151-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1130649820
    464 https://doi.org/10.1186/s13059-020-02151-8
    465 rdf:type schema:CreativeWork
    466 grid-institutes:grid.411024.2 schema:alternateName Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA
    467 Greenebaum Cancer Center, University of Maryland, 21201, Baltimore, MD, USA
    468 Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA
    469 schema:name Department of Microbiology and Immunology, University of Maryland School of Medicine, 21201, Baltimore, MD, USA
    470 Greenebaum Cancer Center, University of Maryland, 21201, Baltimore, MD, USA
    471 Institute for Genome Sciences, University of Maryland School of Medicine, 21201, Baltimore, MD, USA
    472 rdf:type schema:Organization
    473 grid-institutes:grid.66859.34 schema:alternateName Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA
    474 schema:name Infectious Disease and Microbiome Program, Broad Institute, 02142, Cambridge, MA, USA
    475 rdf:type schema:Organization
     




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


    ...