Microarray data analysis software

Scan the array at 550 nm using a DNA microarray scanner and process the data using a DNA microarray data analysis software package (Fig. 5 see Note 12). 

TABLE 5.6-5. A Partial List of Microarray Data Analysis Software... 

GPR files are used in some biostatistical analyses. For example, the microarray data analysis software Acuity 4.0 by Molecular Devices uses this file format... 

Data analysis Training with the technical experts of PerkinElmer is necessary before performing microarray data analysis using the software package. 

Biostatistical analyses are needed to appropriately normalize, analyze, and interpret the vast amounts of data obtained from reverse capture studies. There are many analysis tools to extract rehable information from microarray data [commercial software packages as well as programs provided on the web at no cost to investigators (11)]. Regardless of the tools that are employed, reverse capture data must be normalized and transformed before reasonable data comparisons can be made (see Note 12). 

ToolBus comprises several data analysis software platforms such as multiple sequence alignment, phylogenetic trees, generic XML viewer, pathways, and microarray analysis, which are linked to each other as well as to major databases. SRS and NCBI serve as general data retrieval portals as well as provide links to specific analysis tools. 

Dudoit, S., Gentleman, R. C., and Quackenbush, J., Open source software for the analysis of microarray data, Biotechniques, Suppl., 45, 2003. 

The site mainly offers useful software for sequence alignment such as ALIGN. It also offers some other useful tools such as PRINTS (Protein motif fingerprint data) and MAXD for microarray data storage and analysis. 

All software produced by Eisen lab may be downloaded and used free of charge by academic and other non-profit researchers. Software is available for microarray image analysis, cluster analysis and visualization and combined expression data and sequence analysis. 

This section describes the use of the microarray technology for transcriptional profiling. The section includes a summary of the experimental procedures (section on Experimental design), the most widely used array platforms (section on Platforms for Gene Expression Analysis), and briefly summarizes the data analysis steps, the software that can be used, and the public microarray data repositories (sections on Analysis of microarray data and Data sharing). 

Tong W, Harris S, Cao X, et al. Development of public toxicogenomics software for microarray data management and analysis. MutatRes. 2004 549(l-2) 241-253. 

There are two simple principles underpinning MIAME. First, microarray data should be annotated in sufficient detail to be of most use to third parties. Second, while the microarray technology is still rapidly developing, it would be counterproductive to try to impose on researchers the use of any particular platforms or software, and any particular methods of data analysis. Instead, the standards should simply require revealing of data in sufficient detail. 

While control elements are important, other microarray structural features such as landmark elements will prove useful. A landmark element is labeled DNA printed at defined locations throughout the array, such as the four corners of the array or subarrays. These elements make it easier for the analysis software to locate an array for data acquisition. 

To use our Ab Microarray Analysis Workbook as described below, you must first calculate the Cy5/Cy3 fluorescent signal ratios for all coordinates on each array. This calculation can usually be done with your array analysis software (e.g., GenePix Pro). The Cy5/Cy3 values are required to calculate INRs, as described below. The Ab Microarray Analysis Workbook is a Microsoft Excel 97/98 file that converts your fluorescence data into INRs for each coordinate on the array. As described in the Introduction, the INR calculated by our workbook is a numerical value that represents the abundance of antigen in sample A relative to that of sample B. 

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