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Consensus comparative analysis of human embryonic stem cell-derived cardiomyocytes

  • Shaohong Zhang
  • , Ellen Poon
  • , Dongqing Xie
  • , Kenneth R. Boheler
  • , Ronald A. Li
  • , Hau-San Wong*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

48 Downloads (CityUHK Scholars)

Abstract

Global transcriptional analyses have been performed with human embryonic stem cells (hESC) derived cardiomyocytes (CMs) to identify molecules and pathways important for human CM differentiation, but variations in culture and profiling conditions have led to greatly divergent results among different studies. Consensus investigation to identify genes and gene sets enriched in multiple studies is important for revealing differential gene expression intrinsic to human CM differentiation independent of the above variables, but reliable methods of conducting such comparison are lacking. We examined differential gene expression between hESC and hESC-CMs from multiple microarray studies. For single gene analysis, we identified genes that were expressed at increased levels in hESC-CMs in seven datasets and which have not been previously highlighted. For gene set analysis, we developed a new algorithm, consensus comparative analysis (CSSCMP), capable of evaluating enrichment of gene sets from heterogeneous data sources. Based on both theoretical analysis and experimental validation, CSSCMP is more efficient and less susceptible to experimental variations than traditional methods. We applied CSSCMP to hESC-CM microarray data and revealed novel gene set enrichment (e.g., glucocorticoid stimulus), and also identified genes that might mediate this response. Our results provide important molecular information intrinsic to hESC-CM differentiation. Data and Matlab codes can be downloaded from S1 Data.
Original languageEnglish
Article numbere0125442
JournalPLOS ONE
Volume10
Issue number5
DOIs
Publication statusPublished - 4 May 2015

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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