期刊论文详细信息
BMC Research Notes
Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results
Yi-Bu Chen2  Meng Li2  Ling Guo1  Yilin Dai1 
[1] Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49934, USA;Bioinformatics Service Program, Norris Medical Library, University of Southern California, 2003 Zonal Ave, Los Angeles, CA, 91007, USA
关键词: Probe reannotation;    Gene expression;    Microarray data analysis;   
Others  :  1166335
DOI  :  10.1186/1756-0500-5-282
 received in 2012-02-06, accepted in 2012-04-18,  发布年份 2012
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【 摘 要 】

Background

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results.

Findings

We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs.

Conclusion

Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

【 授权许可】

   
2012 Dai et al.; licensee BioMed Central Ltd.

【 预 览 】
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【 参考文献 】
  • [1]Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, et al.: Bioconductor: open software development for computational biology and bioinformatics. Genome biology 2004, 5:R80. BioMed Central Full Text
  • [2]Wettenhall JM, Simpson KM, Satterley K, Smyth GK: affylmGUI: a graphical user interface for linear modeling of single channel microarray data. Bioinformatics 2006, 22:897-899.
  • [3]Sanges R, Cordero F, Calogero RA: oneChannelGUI: a graphical interface to Bioconductor tools, designed for life scientists who are not familiar with R language. Bioinformatics 2007, 23:3406-3408.
  • [4]Xia X, McClelland M, Wang Y: WebArray: an online platform for microarray data analysis. BMC Bioinformatics 2005, 6:306. BioMed Central Full Text
  • [5]Rainer J, Sanchez-Cabo F, Stocker G, Sturn A, Trajanoski Z: CARMAweb: comprehensive R- and bioconductor-based web service for microarray data analysis. Nucleic Acids Res 2006, 34:W498-W503.
  • [6]Risueno A, Fontanillo C, Dinger ME: De Las Rivas J: GATExplorer: genomic and transcriptomic explorer; mapping expression probes to gene loci, transcripts, exons and ncRNAs. BMC Bioinformatics 2010, 11:221. BioMed Central Full Text
  • [7]Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, et al.: Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res 2005, 33:e175.
  • [8]Ballester B, Johnson N, Proctor G, Flicek P: Consistent annotation of gene expression arrays. BMC Genomics 2010, 11:294. BioMed Central Full Text
  • [9]Gautier L, Cope L, Bolstad BM, Irizarry RA: affy–analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 2004, 20:307-315.
  • [10]Nurtdinov RN, Vasiliev MO, Ershova AS, Lossev IS, Karyagina AS: PLANdbAffy: probe-level annotation database for Affymetrix expression microarrays. Nucleic Acids Res 2010, 38:D726-D730.
  • [11]Carter SL, Eklund AC, Mecham BH, Kohane IS, Szallasi Z: Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements. BMC Bioinformatics 2005, 6:107. BioMed Central Full Text
  • [12]Elo LL, Lahti L, Skottman H, Kylaniemi M, Lahesmaa R, Aittokallio T: Integrating probe-level expression changes across generations of Affymetrix arrays. Nucleic Acids Res 2005, 33:e193.
  • [13]Barbosa-Morais NL, Dunning MJ, Samarajiwa SA, Darot JF, Ritchie ME, Lynch AG, Tavare S: A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data. Nucleic Acids Research 2010, 38:e17.
  • [14]Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics 2008, 24:1547-1548.
  • [15]Sandberg R, Larsson O: Improved precision and accuracy for microarrays using updated probe set definitions. BMC Bioinformatics 2007, 8:48. BioMed Central Full Text
  • [16]Huang DW, Sherman BT, Lempicki RA: Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Research 2009, 37:1-13.
  • [17]Nam D, Kim SY: Gene-set approach for expression pattern analysis. Brief Bioinform 2008, 9:189-197.
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