Data integration and reproducibility for high-throughput transcriptomics

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

The rapid advances in high-throughput transcriptomics allow individual investigators to rapidly and comprehensively interrogate the transcriptome. This phenomenon has placed large volumes of gene expression data in public repositories presenting opportunities for secondary analysis, discovery, and in silico modeling. We focus here on guidelines for best practices for transcriptomics data integration and considerations for reproducibility. In addition, we discuss some considerations for multi-omic and cross-species comparisons.

Original languageEnglish (US)
Title of host publicationInternational Review of Neurobiology
PublisherAcademic Press Inc.
Pages55-71
Number of pages17
DOIs
StatePublished - Jan 1 2014

Publication series

NameInternational Review of Neurobiology
Volume116
ISSN (Print)0074-7742

Keywords

  • Cross-platform
  • Data integration
  • High-throughput
  • Microarrays
  • Next-generation sequencing
  • Reproducibility
  • Transcriptomics

ASJC Scopus subject areas

  • Clinical Neurology
  • Cellular and Molecular Neuroscience

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  • Cite this

    Mooney, M., & McWeeney, S. (2014). Data integration and reproducibility for high-throughput transcriptomics. In International Review of Neurobiology (pp. 55-71). (International Review of Neurobiology; Vol. 116). Academic Press Inc.. https://doi.org/10.1016/B978-0-12-801105-8.00003-5