title: Software and tools for microarray data analysis.
abstract: A typical microarray experiment results in series of images, depending on the experimental design and number of samples. Software analyses the images to obtain the intensity at each spot and quantify the expression for each transcript. This is followed by normalization, and then various data analysis techniques are applied on the data. The whole analysis pipeline requires a large number of software to accurately handle the massive amount of data. Fortunately, there are large number of freely available and commercial software to churn the massive amount of data to manageable sets of differentially expressed genes, functions, and pathways. This chapter describes the software and tools which can be used to analyze the gene expression data right from the image analysis to gene list, ontology, and pathways.
authors: Conway Institute, University College Dublin, Ireland. jai.mehta@ucd.ie
authors: Jai Prakash
authors: JP
authors: Mehta
authors: Sweta
authors: S
authors: Rani
mesh_terms: D016000:Cluster Analysis; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics; D046228:Microarray Analysis / Q000706:statistics & numerical data*; D012333:RNA, Messenger / Q000032:analysis*; D012107:Research Design; D012984:Software; D013223:Statistics as Topic
chemical_list: D012333:RNA, Messenger