ArrayStar - Software for Large-Scale, Multi-Sample Variation Comparisons
ArrayStar is a powerful software tool for analyzing both global gene expression experiments as well as sequence variation data across a group of samples.
Gene ExpressionFor gene expression projects, ArrayStar handles data from oligonucleotide microarrays or spotted arrays and offers you statistical tools in conjunction with graphically rich visualizations to isolate gene sets of interest and identify their biological significance.
Sequence Variation AnalysisMulti-sample variation comparisons across genomic data utilize projects and SNP data explorted directly from SeqMan NGen, exported from SeqMan Pro, or via a wizard for customized importing. ArrayStar also offers the optional QSeq application, for RNA-Seq, ChIP-Seq, and miRNA analysis.
To learn more, see the Features or Resources tabs below.
"It has been a pleasure to use ArrayStar. It is incredibly intuitive and allows microarray analysis novices to produce complex analyses quickly and simply."
Lynette Foo, Stanford University
Cancer Genomics and Clinical Research
Create categories to associate clinical metadata, including phenotypic traits.
Identify SNPs and genes of interest using dbNSFP, dbSNP, COSMIC and GERP information from SeqMan NGen assemblies or using variant data and annotations from VCF files.
Compare groups of individuals through advanced filtering features and set confidence levels based on a variety of variables.
Use statistical methods, such as the Fisher's Exact Test and Odds Ratio, to assist with your association studies.
Identify relationships between genes with particular biological functions. See it!
Determine the relative importance of genes in specific processes using the numerous statistical comparisons shown in the association tree.
Download the gene ontology tree structure from the Gene Ontology Consortium. View its full name, ID and description when you hover over the term.
For large, multi-sample SNP projects, use the Gene Ontology View to discover how variations may impact gene function.
Visualize the expression level changes in individual genes over the course of the experiment through the use of line graphs.
Multi-functional scatter plots can be generated to easily select groups of genes for analysis. Selected genes are shown in white. See it!
Undock and move views out of the main window so that you can have several views displayed on your screen simultaneously. All views are interactive, so that subsets of genes selected in one view will be selected in all other views.
The various tabular views allow you to view detailed information for your genes, as well as manage and organize your data and gene sets.
After importing data from a variety of formats, select the normalization method to be applied to your data; RMA, PLIER, quantile normalization, or average summarization.
Cluster your data using hierarchical clustering or k-means. By default, hierarchical groups are displayed on the heat map and k-means groups are displayed as line graph thumbnails. See it!
Compare SNPs across individuals using the SNP Table, Venn diagrams, and advanced filtering tools.
Use statistical analysis tools and techniques to assist with your gene selection studies. ArrayStar's filtering capabilities allow users to quickly examine and re-examine data based on different experimental assumptions.
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