Analysis of dose-response effects on gene expression data with comparison of two microarray platforms

被引:26
|
作者
Hu, JH
Kapoor, M
Zhang, W
Hamilton, SR
Coombes, KR [1 ]
机构
[1] Univ Texas, MD Anderson Canc Ctr, Dept Biostat & Appl Math, Houston, TX 77030 USA
[2] Univ Texas, MD Anderson Canc Ctr, Dept Canc Genet, Houston, TX 77030 USA
[3] Univ Texas, MD Anderson Canc Ctr, Dept Pathol, Houston, TX 77030 USA
基金
美国国家卫生研究院;
关键词
D O I
10.1093/bioinformatics/bti592
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: The problems of analyzing dose effects on gene expression are gaining attention in biomedical research. A specific challenge is to detect genes with expression levels that change according to dose levels in a non-random manner, but nonetheless may be considered as potential biomarkers. Method: We are among the first to formally apply a tool that uses an isotonic (monotonic) regression approach to this area of study. We introduce a test statistic to select genes with significant dose-response expression in a monotonic fashion based on a permutation procedure. We then compare the results with those achieved from the application of a likelihood ratio-based test. Results: We apply the isotonic regression approach to a study of gene expression in the RKO colon carcinoma cell line in response to varying dosage levels of the chemotherapeutic agent 5-fluorouracil. A feature of both Affymetrix and printed 75mer oligomer cDNA arrays produced from the same samples provides an opportunity to compare the two microarray platforms.
引用
收藏
页码:3524 / 3529
页数:6
相关论文
共 50 条
  • [1] A comparison of multiple microarray platforms for gene expression
    Nelson, S
    Merriman, B
    AMERICAN JOURNAL OF HUMAN GENETICS, 2003, 73 (05) : 439 - 439
  • [2] IsoGeneGUI: Multiple Approaches for Dose-Response Analysis of Microarray Data Using R
    Otava, Martin
    Sengupta, Rudradev
    Shkedy, Ziv
    Lin, Dan
    Pramana, Setia
    Verbeke, Tobias
    Haldermans, Philippe
    Hothorn, Ludwig A.
    Gerhard, Daniel
    Kuiper, Rebecca M.
    Klinglmueller, Florian
    Kasim, Adetayo
    R JOURNAL, 2017, 9 (01): : 14 - 26
  • [3] Dose-response analysis of phthalate effects on gene expression in rat whole embryo culture
    Robinson, Joshua F.
    Verhoef, Aart
    van Beelen, Vincent A.
    Pennings, Jeroen L. A.
    Piersma, Aldert H.
    TOXICOLOGY AND APPLIED PHARMACOLOGY, 2012, 264 (01) : 32 - 41
  • [4] Dose-Response Analysis of Phthalate Effects on Gene Expression in Rat Whole Embryo Culture
    Robinson, J. F.
    Tonk, E. C. M.
    Verhoef, A.
    Van Beelen, V. A.
    Pennings, J. L. A.
    Piersma, A. H.
    BIRTH DEFECTS RESEARCH PART A-CLINICAL AND MOLECULAR TERATOLOGY, 2012, 94 (05) : 349 - 349
  • [5] Defining multigene dose-response relationships by microarray analysis
    Towndrow, KM
    Baker, TK
    Cummins, DJ
    Farmen, MW
    Thomas, CE
    Stevens, JL
    TOXICOLOGICAL SCIENCES, 2003, 72 : 91 - 91
  • [6] ANALYSIS AND COMPARISON OF SIGMOIDAL CURVES - APPLICATION TO DOSE-RESPONSE DATA
    MEDDINGS, JB
    SCOTT, RB
    FICK, GH
    AMERICAN JOURNAL OF PHYSIOLOGY, 1989, 257 (06): : G982 - G989
  • [7] Impact of DNA microarray data transformation on gene expression analysis - comparison of two normalization methods
    Schmidt, Marcin T.
    Handschuh, Luiza
    Zyprych, Joanna
    Szabelska, Alicja
    Olejnik-Schmidt, Agnieszka K.
    Siatkowski, Idzi
    Figlerowicz, Marek
    ACTA BIOCHIMICA POLONICA, 2011, 58 (04) : 573 - 580
  • [8] Dose-response analysis of the effects of persistent organic pollutants (POPs) on gene expression in human hepatocytes
    Mi-Kyung Song
    Jae-Chun Ryu
    Molecular & Cellular Toxicology, 2015, 11 : 323 - 334
  • [9] Dose-response analysis of the effects of persistent organic pollutants (POPs) on gene expression in human hepatocytes
    Song, Mi-Kyung
    Ryu, Jae-Chun
    MOLECULAR & CELLULAR TOXICOLOGY, 2015, 11 (03) : 323 - 334
  • [10] Are data from different gene expression microarray platforms comparable?
    Järvinen, AK
    Hautaniemi, S
    Edgren, H
    Auvinen, P
    Saarela, J
    Kallioniemi, OP
    Monni, O
    GENOMICS, 2004, 83 (06) : 1164 - 1168