Introduction

The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an 'integrate by intersection' (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance.

Publications

  1. Gene integrated set profile analysis: a context-based approach for inferring biological endpoints.
    Cite this
    Kowalski J, Dwivedi B, Newman S, Switchenko JM, Pauly R, Gutman DA, Arora J, Gandhi K, Ainslie K, Doho G, Qin Z, Moreno CS, Rossi MR, Vertino PM, Lonial S, Bernal-Mizrachi L, Boise LH, 2016-04-01 - Nucleic acids research

Credits

  1. Jeanne Kowalski
    Developer

    Winship Cancer Institute, Emory University, United States of America

  2. Bhakti Dwivedi
    Developer

    Department of Biostatistics and Bioinformatics, Rollins School of Public Health, United States of America

  3. Scott Newman
    Developer

    Department of Biostatistics and Bioinformatics, Rollins School of Public Health, United States of America

  4. Jeffery M Switchenko
    Developer

    Winship Cancer Institute, Emory University, United States of America

  5. Rini Pauly
    Developer

    Winship Cancer Institute, Emory University, United States of America

  6. David A Gutman
    Developer

    Department of Biomedical Informatics and Neurology, School of Medicine, United States of America

  7. Jyoti Arora
    Developer

    Winship Cancer Institute, Emory University, United States of America

  8. Khanjan Gandhi
    Developer

    Department of Human Genetics, School of Medicine, United States of America

  9. Kylie Ainslie
    Developer

    Department of Biostatistics and Bioinformatics, Rollins School of Public Health, United States of America

  10. Gregory Doho
    Developer

    Centers for Disease Control, Atlanta, United States of America

  11. Zhaohui Qin
    Developer

    Department of Biostatistics and Bioinformatics, Rollins School of Public Health, United States of America

  12. Carlos S Moreno
    Developer

    Winship Cancer Institute, Emory University, United States of America

  13. Michael R Rossi
    Developer

    Winship Cancer Institute, Emory University, United States of America

  14. Paula M Vertino
    Developer

    Winship Cancer Institute, Emory University, United States of America

  15. Sagar Lonial
    Developer

    Winship Cancer Institute, Emory University, United States of America

  16. Leon Bernal-Mizrachi
    Developer

    Winship Cancer Institute, Emory University, United States of America

  17. Lawrence H Boise
    Investigator

    Winship Cancer Institute, Emory University, United States of America

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Summary
AccessionBT006435
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByLawrence H Boise