Cross-platform analysis of global microRNA expression technologies

被引:26
|
作者
Yauk, Carole L. [1 ]
Rowan-Carroll, Andrea [1 ]
Stead, John D. H. [2 ]
Williams, Andrew [1 ]
机构
[1] Hlth Cananda, Environm Hlth Sci & Res Bur, Ottawa, ON K1A 0K9, Canada
[2] Carleton Univ, Inst Neurosci, Ottawa, ON K1S 5B6, Canada
来源
BMC GENOMICS | 2010年 / 11卷
关键词
GENE-EXPRESSION; MICROARRAY; NORMALIZATION; COMPARABILITY; CONSISTENCY; BIOMARKERS;
D O I
10.1186/1471-2164-11-330
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: Although analysis of microRNAs (miRNAs) by DNA microarrays is gaining in popularity, these new technologies have not been adequately validated. We examined within and between platform reproducibility of four miRNA array technologies alongside TaqMan PCR arrays. Results: Two distinct pools of reference materials were selected in order to maximize differences in miRNA content. Filtering for miRNA that yielded signal above background revealed 54 miRNA probes (matched by sequence) across all platforms. Using this probeset as well as all probes that were present on an individual platform, within-platform analyses revealed Spearman correlations of >0.9 for most platforms. Comparing between platforms, rank analysis of the log ratios of the two reference pools also revealed high correlation (range 0.663-0.949). Spearman rank correlation and concordance correlation coefficients for miRNA arrays against TaqMan qRT-PCR arrays were similar for all of the technologies. Platform performances were similar to those of previous cross-platform exercises on mRNA and miRNA microarray technologies. Conclusions: These data indicate that miRNA microarray platforms generated highly reproducible data and can be recommended for the study of changes in miRNA expression.
引用
收藏
页数:10
相关论文
共 50 条
  • [1] Cross-platform analysis of global microRNA expression technologies
    Carole L Yauk
    Andrea Rowan-Carroll
    John DH Stead
    Andrew Williams
    BMC Genomics, 11
  • [2] Cross-Platform Analysis with Binarized Gene Expression Data
    Tuna, Salih
    Niranjan, Mahesan
    PATTERN RECOGNITION IN BIOINFORMATICS, PROCEEDINGS, 2009, 5780 : 439 - 449
  • [3] Cross-Platform Prediction of Gene Expression Signatures
    Lin, Shu-Hong
    Beane, Lauren
    Chasse, Dawn
    Zhu, Kevin W.
    Mathey-Prevot, Bernard
    Chang, Jeffrey T.
    PLOS ONE, 2013, 8 (11):
  • [4] Differential network analysis from cross-platform gene expression data
    Zhang, Xiao-Fei
    Le Ou-Yang
    Zhao, Xing-Ming
    Yan, Hong
    SCIENTIFIC REPORTS, 2016, 6
  • [5] Differential network analysis from cross-platform gene expression data
    Xiao-Fei Zhang
    Le Ou-Yang
    Xing-Ming Zhao
    Hong Yan
    Scientific Reports, 6
  • [6] APEX: cross-platform analysis program for EXAFS
    Dimakis, N
    Bunker, G
    JOURNAL OF SYNCHROTRON RADIATION, 1999, 6 : 274 - 275
  • [7] DSGeo: Software tools for cross-platform analysis of gene expression data in GEO
    Lacson, Ronilda
    Pitzer, Erik
    Kim, Jihoon
    Galante, Pedro
    Hinske, Christian
    Ohno-Machado, Lucila
    JOURNAL OF BIOMEDICAL INFORMATICS, 2010, 43 (05) : 709 - 715
  • [8] CROSS-PLATFORM COMPRESSION
    DION, PJ
    DR DOBBS JOURNAL, 1993, 18 (13): : 32 - &
  • [9] FACTOR ANALYSIS FOR CROSS-PLATFORM TUMOR CLASSIFICATION BASED ON GENE EXPRESSION PROFILES
    Wang, Shu-Lin
    Gui, Jie
    Li, Xueling
    JOURNAL OF CIRCUITS SYSTEMS AND COMPUTERS, 2010, 19 (01) : 243 - 258
  • [10] Cross-platform computing
    Anon
    Computer-Aided Engineering, 2000, 19 (12):