Agilent GeneSpring GX

Category Genomics>Gene Expression Analysis/Profiling/Tools, Genomics>Genetic Data Analysis/Tools, and Cross-Omics>Pathway Analysis/Gene Regulatory Networks/Tools

Abstract Agilent's GeneSpring GX software provides advanced, accessible statistical tools for fast visualization and analysis of transcriptomics, genomics, proteomics and metabolomics data.

Designed specifically for the needs of biologists, GeneSpring GX offers an interactive desktop computing environment that promotes investigation and enables understanding of microarray data within a biological context.

Regarded as the gold standard in expression analysis, GeneSpring allows you to quickly and reliably identify targets of interest that are both statistically and biologically meaningful. GeneSpring has over 9,500 references in Google Scholar, including over 1,600 in peer reviewed publications.

Developed on avadisô from Strand Life Sciences, GeneSpring GX is part of Agilentís GeneSpring Analysis Platform, an expanding suite of integrated software applications for systems-level research.

Integrative platform for multi-omic data analysis --

GeneSpring 11.5 addresses the challenges in multi-omic data analysis by providing comprehensive analytical and visualization tools for multiple data types within a single data analysis application.

With this platform, heterogeneous data such as gene expression, miRNA, exon splicing, genomic copy number, genotyping, proteins, and metabolites, can be combined into one project, allowing researchers to analyze, compare, and view results from different experiments in a single user interface.

GeneSpring 11.5 facilitates integrative analysis through its translation function, linking probes across data types, array platforms, and organisms that map to the same biological entity.

By supporting analysis and translation of multiple data types in a single application, GeneSpring 11.5 avoids common issues of software interoperability and faulty semantic mapping to increase a researcherís ability to find linkages between data types.

Transcriptomic analysis --

GeneSpring 11.5 provides flexible and comprehensive workflows for a variety of transcriptomic applications. Specifically, several new features that leverage the new exon-level content of Agilentís Exon Microarrays have been implemented, including a new workflow, statistical routines, and a host of enhanced visualizations.

A broad spectrum of data pre-processing, linear and non-linear normalization methods is available for both one- and two-color gene expression data.

Depending on the researcherís level of expertise, data analysis can be performed using either the Guided Workflow or Advanced Analysis mode. Quality control can be performed using platform-specific metrics, enabling researchers to optimize pre-processing steps before statistical analysis.

Other key features for transcriptomic applications include:

1) Probe-or gene-level expression analysis on all major microarray platforms, including Agilent, Affymetrix, and Illumina;

2) microRNA analysis and identification of gene targets using integrated TargetScan information;

3) Exon splicing analysis using t-tests or multivariate splicing ANOVA and filtering for transcripts on splicing index;

4) Real-time PCR data analysis; and

5) NCBI Gene Expression Omnibus Importer tool for expression datasets.

Genomic copy number analysis --

GeneSpring 11.5 also supports the interrogation of genomic structural variations and their implications in disease susceptibility and progression. Providing workflows for paired and unpaired analysis of Affymetrix and Illumina genotyping array data, GeneSpring 11.5 enables scientists to quickly detect regions of genomic copy number variation (CNV) and loss of heterozygosity (LOH).

Once regions of interest are discovered, genes overlapping those regions can be identified and the biological impact of copy number variation can be assessed in downstream GO Analysis or pathway analysis.

Features of the genomic copy number workflow include:

1) Ability to create and use a custom reference in addition to packaged HapMap reference;

2) Batch effect correction method;

3) Circular Binary Segmentation;

4) Filters to identify copy-neutral LOH events and regions of allelic imbalance; and

5) The ability to identify common variations across a set of samples.

Genome-wide association analysis --

Genome-wide association studies (GWAS) utilize high-density genotyping microarrays to identify SNPs associated with qualitative or quantitative traits. GeneSpring 11.5 provides a comprehensive workflow for case-control GWAS using Affymetrix and Illumina genotyping microarray platforms.

The flexible workflow supports case-control experimental designs, offering a suite of statistical tests applied under various genetic models, multiple testing correction, and correction methods for population stratification.

After identifying genes harboring SNPs or haplotype blocks associated with trait, researchers can perform GO Analysis and pathway analysis to determine what biological process and pathways may be involved in the disease under study. Other key features for the genetic association workflow include:

1) EIGENSTRAT and Genomic Control population stratification correction;

2) Tag SNP identification; 3) Haplotype inference and Haplotype Trend Regression;

4) Pearsonís Chi-Square, Fisherís Exact, Cochran Armitage, and Chi-Square correlation;

5) Logistic and linear regression; and

6) LD plot.

Proteomic and metabolomic analysis --

GeneSpring 11.5 can also be used to analyze many different types of mass spectral data through integration with Agilentís Mass Profiler Professional - (see G6G Abstract Number 20056R), including GC/MS, LC/MS, CE/MS, and ICP-MS. An optional mzXML package expands these capabilities even further for other instruments.

Recursive analysis - a unique feature of Mass Profiler Professional - lets users easily re-mine data sets, based on preliminary data, to improve the quality of statistical analysis results.

Itís also easy to export an inclusion list for Q-TOF MS/MS analysis and re-import the results into Mass Profiler Professional. A single, consistent user interface supports all data types, and advanced visualization tools let users inspect and annotate their results in new ways.

With functionality for unsupervised (classification without prior group assignments) or supervised (using pre-classified groups) analysis, the software lets users:

1) Quickly and easily discover differences between sample groups;

2) Plot changing patterns of compound abundances over time; and

3) Develop useful multivariate models for class prediction.

Comprehensive analytical and visualization toolkit --

At the core of GeneSpring 11.5 is a set of statistical tests, algorithms, and visualization tools that allow researchers to analyze a broad range of experimental designs.

Statistical tools for testing differential expression --

GeneSpring 11.5 provides a comprehensive suite of statistical tests so that differential analysis can be applied robustly on a variety of experimental designs.

GeneSpring 11.5 statistical toolkit includes parametric and non-parametric tests that can be applied to paired and unpaired experimental designs, permutative and asymptotic p-value computation, and multiple testing correction methods, including permutation based options.

Post-hoc statistical tests can also be applied to pinpoint pairs of experimental conditions where differential expression is detected. Multivariate analysis is available to test the effects of each factor, and their interaction, on changes in expression across experimental conditions.

Pattern discovery --

GeneSpring 11.5 provides a broad choice of tools to identify unique patterns in data. Clustering algorithms can be employed to group entities and/or samples based on the similarity of their expression profiles, revealing information regarding the biological function or the co-regulation of genes.

GeneSpring 11.5 also provides robust classification algorithms that use training datasets to find clinically predictive expression patterns. By offering multiple classifiers including Decision Tree, Support Vector Machine, Naive Bayesian, Neural Network, and Partial least squares discriminate, GeneSpring 11.5 enables biomarker discovery for a variety of experimental designs.

Extensible functionality with Jython and R --

GeneSpring 11.5 provides scientists the ability to write, execute, and save their own scripts to combine operations in GeneSpring 11.5 with a more general Jython (Python with Java class import capabilities) programming framework. Userscan develop their own data transformation operations, automatically pull up data views, and run external algorithms within GeneSpring 11.5.

An embedded R scripting editor will also allow R scripts to be written and run from within GeneSpring 11.5. Any R function can be given access to GeneSpring 11.5 data, with results being automatically incorporated back into the GeneSpring 11.5 environment.

Intuitive graphical displays --

GeneSpring 11.5 displays data in ways that help users conceptualize and convey the information in their data. The various types of plots, graphs and diagrams highlight different aspects of the data, allowing visual information to be extracted in multiple ways. Virtually any graphical image can be exported as HTML or as image in .tiff, .jpeg, .png or .bmp format compatible with publishing software applications.

An interactive and advanced Genome Browser is a key component to visualizing genomic structural data and integrating results from multi-omic studies. Results from different experiments can be dragged and dropped into individual data tracks and viewed simultaneously.

The image overlay feature permits the user to overlay any data or annotation tracks, thus allowing researchers to qualitatively assess correlation between different data types. Other visualization tools in GeneSpring 11.5 include scatter plot, MvA, profile plot, histogram, and many more. With it you can:

1) Quickly and easily discover differences between sample groups;

2) Plot changing patterns of compound abundances over time; and

3) Develop useful multivariate models for class prediction.

Integrated toolbox for pathway analysis and biological contextualization --

Genes and proteins interact in a biochemical network to orchestrate the biological processes involved in disease. GeneSpring 11.5 provides modeling capabilities to allow researchers to quickly generate and dynamically explore these networks.

Using a set of algorithms and provided organism-specific interaction databases, researchers can build a range of network types, including targets and regulators, transcription regulators, biological processes, and shortest connect. Networks can also be created based on user-specified MeSH terms.

Networks generated in GeneSpring 11.5 are dynamic and interactive, allowing overlay of expression values and analysis results onto the network, interrogation of nodes and edges, and expansion of network from selected nodes.

Natural language processing-based (NLP) algorithms can be applied to a body of text, HTML, a PDF, or Medline XML to extract and add interactions to an existing interaction database. GeneSpring 11.5 facilitates the process of extracting relevant interactions by allowing scientists to use MeSH terms to retrieve Medline abstracts that the NLP will run on. This allows researchers to customize network analysis to their experimental models.

In addition to network building, GeneSpring 11.5 allows researchers to import and view any pathways in the BioPAX exchange format. These pathways can be used in the Find Similar Pathway tool, where researchers could quickly determine if there is an enrichment of the genes of interest in any pathways.

In addition to providing built-in pathway and network analysis tools, GeneSpring 11.5 extends biological contextualization capabilities through its integration with Ingenuity Pathway Analysis (IPA) - (see G6G Abstract Number 20017U), where lists of genes and experimental data can be seamlessly transferred between the two applications for iterative analysis.

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Manufacturer Web Site Agilent GeneSpring GX

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G6G Abstract Number 20003R

G6G Manufacturer Number 100130