Introduction

Clustering is carried out to identify patterns in transcriptomics profiles to determine clinically relevant subgroups of patients. Feature (gene) selection is a critical and an integral part of the process. Currently, there are many feature selection and clustering methods to identify the relevant genes and perform clustering of samples. However, choosing an appropriate methodology is difficult. In addition, extensive feature selection methods have not been supported by the available packages. Hence, we developed an integrative R-package called multiClust that allows researchers to experiment with the choice of combination of methods for gene selection and clustering with ease. Using multiClust, we identified the best performing clustering methodology in the context of clinical outcome. Our observations demonstrate that simple methods such as variance-based ranking perform well on the majority of data sets, provided that the appropriate number of genes is selected. However, different gene ranking and selection methods remain relevant as no methodology works for all studies.

Publications

  1. multiClust: An R-package for Identifying Biologically Relevant Clusters in Cancer Transcriptome Profiles.
    Cite this
    Lawlor N, Fabbri A, Guan P, George J, Karuturi RK, 2016-01-01 - Cancer informatics

Credits

  1. Nathan Lawlor
    Developer

    Department of Molecular and Cell Biology, University of Connecticut, United States of America

  2. Alec Fabbri
    Developer

    Department of Biomedical Engineering, University of Connecticut, United States of America

  3. Peiyong Guan
    Developer

    Genome Institute of Singapore, ASTAR (Agency for Science, Singapore

  4. Joshy George
    Developer

    The Jackson Laboratory for Genomic Medicine, Farmington, United States of America

  5. R Krishna Murthy Karuturi
    Investigator

    The Jackson Laboratory for Genomic Medicine, Farmington, United States of America

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Summary
AccessionBT001637
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByR Krishna Murthy Karuturi