Experimental validation of methods for differential gene expression analysis and sample pooling in RNA-seq View Full Text


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Article Info

DATE

2015-12

AUTHORS

Anto P. Rajkumar, Per Qvist, Ross Lazarus, Francesco Lescai, Jia Ju, Mette Nyegaard, Ole Mors, Anders D. Børglum, Qibin Li, Jane H. Christensen

ABSTRACT

BACKGROUND: Massively parallel cDNA sequencing (RNA-seq) experiments are gradually superseding microarrays in quantitative gene expression profiling. However, many biologists are uncertain about the choice of differentially expressed gene (DEG) analysis methods and the validity of cost-saving sample pooling strategies for their RNA-seq experiments. Hence, we performed experimental validation of DEGs identified by Cuffdiff2, edgeR, DESeq2 and Two-stage Poisson Model (TSPM) in a RNA-seq experiment involving mice amygdalae micro-punches, using high-throughput qPCR on independent biological replicate samples. Moreover, we sequenced RNA-pools and compared their results with sequencing corresponding individual RNA samples. RESULTS: False-positivity rate of Cuffdiff2 and false-negativity rates of DESeq2 and TSPM were high. Among the four investigated DEG analysis methods, sensitivity and specificity of edgeR was relatively high. We documented the pooling bias and that the DEGs identified in pooled samples suffered low positive predictive values. CONCLUSIONS: Our results highlighted the need for combined use of more sensitive DEG analysis methods and high-throughput validation of identified DEGs in future RNA-seq experiments. They indicated limited utility of sample pooling strategies for RNA-seq in similar setups and supported increasing the number of biological replicate samples. More... »

PAGES

548

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s12864-015-1767-y

    DOI

    http://dx.doi.org/10.1186/s12864-015-1767-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1017454076

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/26208977


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    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/s12864-015-1767-y'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s12864-015-1767-y'

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

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    285 https://www.grid.ac/institutes/grid.21155.32 schema:alternateName Beijing Genomics Institute
    286 schema:name Beijing Genomics Institute, 518083, Shenzhen, China
    287 rdf:type schema:Organization
    288 https://www.grid.ac/institutes/grid.7048.b schema:alternateName Aarhus University
    289 schema:name Center for Integrative Sequencing, iSEQ, Aarhus University, 8000, Aarhus, Denmark
    290 Department of Biomedicine, Aarhus University, 6, Bartholins Allé, Aarhus C, 8000, Aarhus, Denmark
    291 Mental Health of Older Adults and Dementia Clinical Academic Group, South London and Maudsley NHS foundation trust, London, UK
    292 Research Department P, Aarhus University Hospital, Risskov, Denmark
    293 The Initiative for Integrative Psychiatric Research, iPSYCH, 8000, Aarhus, Denmark
    294 Translational Neuropsychiatry Unit, Aarhus University, 8240, Aarhus, Denmark
    295 Wolfson Centre for Age Related Diseases, Institute of Psychiatry, Psychology, & Neuroscience, King’s College, London, UK
    296 rdf:type schema:Organization
     




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