Interpretation of genomic data: Questions and answers

被引:8
作者
Simon, Richard [1 ]
机构
[1] NCI, Biometr Res Branch, Bethesda, MD 20892 USA
关键词
D O I
10.1053/j.seminhematol.2008.04.008
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Using a question and answer format we describe important aspects of using genomic technologies in cancer research. The main challenges are not managing the mass of data, but rather the design, analysis, and accurate reporting of studies that result in increased biological knowledge and medical utility. Many analysis issues address the use of expression microarrays but are also applicable to other whole genome assays. Microarray-based clinical investigations have generated both unrealistic hype and excessive skepticism. Genomic technologies are tremendously powerful and will play instrumental roles in elucidating the mechanisms of oncogenesis and in bringing on an era of predictive medicine in which treatments are tailored to individual tumors. Achieving these goals involves challenges in rethinking many paradigms for the conduct of basic and clinical cancer research and for the organization of interdisciplinary collaboration.
引用
收藏
页码:196 / 204
页数:9
相关论文
共 53 条
  • [1] Selection bias in gene extraction on the basis of microarray gene-expression data
    Ambroise, C
    McLachlan, GJ
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2002, 99 (10) : 6562 - 6566
  • [2] [Anonymous], 2003, Design and Analysis of DNA Microarray Investigations
  • [3] Semi-supervised methods to predict patient survival from gene expression data
    Bair, E
    Tibshirani, R
    [J]. PLOS BIOLOGY, 2004, 2 (04) : 511 - 522
  • [4] Tissue classification with gene expression profiles
    Ben-Dor, A
    Bruhn, L
    Friedman, N
    Nachman, I
    Schummer, M
    Yakhini, Z
    [J]. JOURNAL OF COMPUTATIONAL BIOLOGY, 2000, 7 (3-4) : 559 - 583
  • [5] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING
    BENJAMINI, Y
    HOCHBERG, Y
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) : 289 - 300
  • [6] Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial
    Bogaerts, Jan
    Cardoso, Fatima
    Buyse, Marc
    Braga, Sofia
    Loi, Sherene
    Harrison, Jillian A.
    Bines, Jacques
    Mook, Stella
    Decker, Nuria
    Ravdin, Peter
    Therasse, Patrick
    Rutgers, Emiel
    van't Veer, Laura J.
    Piccart, Martine
    [J]. NATURE CLINICAL PRACTICE ONCOLOGY, 2006, 3 (10): : 540 - 551
  • [7] Sample size determination in microarray experiments for class comparison and prognostic classification
    Dobbin, K
    Simon, R
    [J]. BIOSTATISTICS, 2005, 6 (01) : 27 - 38
  • [8] Questions and answers on design of dual-label microarrays for identifying differentially expressed genes
    Dobbin, K
    Shih, JH
    Simon, R
    [J]. JOURNAL OF THE NATIONAL CANCER INSTITUTE, 2003, 95 (18) : 1362 - 1369
  • [9] How large a training set is needed to develop a classifier for microarray data?
    Dobbin, Kevin K.
    Zhao, Yingdong
    Simon, Richard M.
    [J]. CLINICAL CANCER RESEARCH, 2008, 14 (01) : 108 - 114
  • [10] Sample size planning for developing classifiers using high-dimensional DNA microarray data
    Dobbin, Kevin K.
    Simon, Richard M.
    [J]. BIOSTATISTICS, 2007, 8 (01) : 101 - 117