Prior biological knowledge-based approaches for the analysis of genome-wide expression profiles using gene sets and pathways

Wu, Michael C.; Xihong Lin
December 2009
Statistical Methods in Medical Research;Dec2009, Vol. 18 Issue 6, p577
Academic Journal
An increasing challenge in analysis of microarray data is how to interpret and gain biological insight of profiles of thousands of genes. This article provides a review of statistical methods for analysis of microarray data by incorporating prior biological knowledge using gene sets and biological pathways, which consist of groups of biologically similar genes. We first discuss issues of individual gene analysis. We compare several methods for analysis of gene sets including over-representation anlaysis, gene set enrichment analysis, principal component analysis, global test and kernel machine. We discuss the assumptions of these methods and their pros and cons. We illustrate these methods by application to a type II diabetes data set.


Related Articles

  • Validation of oligoarrays for quantitative exploration of the transcriptome. Nygaard, Vigdis; Fang Liu; Holden, Marit; Kuo, Winston P.; Trimarchi, Jeff; Ohno-Machado, Lucila; Cepko, Connie L.; Frigessi, Arnoldo; Glad, Ingrid K.; van de Wiel, Mark A.; Hovig, Eivind; Heidi Lyng // BMC Genomics;2008, Vol. 9, Special section p1 

    Background: Oligoarrays have become an accessible technique for exploring the transcriptome, but it is presently unclear how absolute transcript data from this technique compare to the data achieved with tag-based quantitative techniques, such as massively parallel signature sequencing (MPSS)...

  • Improved double kernel local linear quantile regression. Jones, M. C.; Keming Yu // Statistical Modelling: An International Journal;2007, Vol. 7 Issue 4, p377 

    As sample quantiles can be obtained as maximum likelihood estimates of location parameters in suitable asymmetric Laplace distributions, so kernel estimates of quantiles can be obtained as maximum likelihood estimates of location parameters in a general class of distributions with simple...

  • Microarrays on the Spot Year in Review. Casey, Steve // Pharmaceutical Discovery;Nov/Dec2005, Vol. 5 Issue 9, p16 

    With this final column for Microarrays on the Spot, I felt it would be important to look back over the year and highlight the tremendous scientific and medical advancements that have been made in microarrays and pharmacogenomics. Without question, in this author's opinion, the ability to measure...

  • Consistent annotation of gene expression arrays. Ballester, Benoît; Johnson, Nathan; Proctor, Glenn; Flicek, Paul // BMC Genomics;2010, Vol. 11, p294 

    Background: Gene expression arrays are valuable and widely used tools for biomedical research. Today's commercial arrays attempt to measure the expression level of all of the genes in the genome. Effectively translating the results from the microarray into a biological interpretation requires an...

  • Genetic architecture of maize kernel row number and whole genome prediction. Liu, Lei; Du, Yanfang; Huo, Dongao; Wang, Man; Shen, Xiaomeng; Yue, Bing; Qiu, Fazhan; Zheng, Yonglian; Yan, Jianbing; Zhang, Zuxin // Theoretical & Applied Genetics;Nov2015, Vol. 128 Issue 11, p2243 

    Key message: Maize kernel row number might be dominated by a set of large additive or partially dominant loci and several small dominant loci and can be accurately predicted by fewer than 300 top KRN-associated SNPs. Abstract: Kernel row number (KRN) is an important yield component in maize and...

  • Statistical Guidelines.  // Annals of Clinical Biochemistry;Jul2002, Vol. 39 Issue 4, p1 

    The article discusses guidelines to statistical analysis which were intended as aids to authors in preparing statistical data for medical research. The number and source of data must be put forward and conclusions having statistical basis should be supported by inclusion of appropriate...

  • Patient treatment satisfaction after switching to NovoMix 30 (BIAsp 30) in the IMPROVEâ„¢ study: an analysis of the influence of prior and current treatment factors. Brod, Meryl; Valensi, Paul; Shaban, Joseph A.; Bushnell, Don M.; Christensen, Torsten L. // Quality of Life Research;Nov2010, Vol. 19 Issue 9, p1285 

    Purpose: Understanding treatment satisfaction (TS) for diabetes is increasingly important as treatment options increase. This study examines treatment satisfaction with NovoMix 30 in an observational study in patients with type 2 diabetes. Methods: The DiabMedSat assesses Overall, Treatment...

  • Investigation of reproducibility of differentially expressed genes in DNA microarrays through statistical simulation. Xiaohui Fan; Leming Shi; Hong Fang; Harris, Stephen; Perkins, Roger; Weida Tong // BMC Proceedings;2009 Supplement 2, Vol. 3, p1 

    Recent publications have raised concerns about the reliability of microarray technology because of the lack of reproducibility of differentially expressed genes (DEGs) from highly similar studies across laboratories and platforms. The rat toxicogenomics study of the MicroArray Quality Control...

  • Kernel based methods for accelerated failure time model with ultra-high dimensional data. Zhenqiu Liu; Dechang Chen; Ming Tan; Feng Jiang; Gartenhaus, Ronald B. // BMC Bioinformatics;2010, Vol. 11, p606 

    Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survival analysis with high-dimensional genomic data. However, when the sample size n « m (the number of genes),...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics