Integromics Biomarker Discovery (IBD)

Category Genomics>Gene Expression Analysis/Profiling/Tools and Cross-Omics>Biomarker Discovery/Analysis/Tools

Abstract Integromics Biomarker Discovery™ (IBD) for TIBCO Spotfire is a custom bioinformatics application that is focused on preprocessing, normalization and interpretation of raw microarray gene expression data.

As part of TIBCO Spotfire, IBD offers a new visual and intuitive way to interact with the data, answer any question on demand, interactively filter data, automatically calculate and recalculate cross-tables and graphs, and produce reports of results.

It provides users with analysis workflows for biomarker discovery in the fields of gene expression and CGH data analysis.

There are specific workflows for the main gene expression platforms: Affymetrix and Two-Channel as well as a flexible integration of all included analytical methodologies that will allow the analysis of other types of data beyond gene expression.

Additionally, state of the art data mining tools are available for the integrated analysis of experimental and functional data (e.g. gene annotations). Throughout the analysis process, the step-by-step guide facilitates statistical analysis making it possible for user of all levels to produce meaningful and reliable results.

IBD Guided Workflows and Tools --

IBD has an easy-to-use workflow that integrates advanced statistics and interactive visualizations to extract biological signals and draw reliable conclusions from differentially expressed genes. Designed for high-throughput genomic studies - the workflow guides the data analysis from start to finish.

IBD Steps of the workflow analysis include:

1) Importing Microarray Data - This step includes selecting a platform, importing the data, creating an experimental design, performing probe level analysis, filtering and dye swap.

2) Quality Control - The three (3) steps of quality control include monitoring the quality of the raw data, determining the quality of the array replicates and examination of the signal distribution of the different arrays.

3) Array Normalization - Normalize data and perform fold change calculations. There are two (2) methods used in this process: within array normalization and between array normalization.

4) Differential Expression Analysis - Differential expression computes the relative expression levels among hybridization groups to identify genes that are expressed differentially. There are two (2) methods for this kind of analysis, parametric and non-parametric.

5) Cluster Analysis - Clustering is the classification of samples into groups. This step enables the user to perform hierarchical clustering.

IBD Tools -

Ingenuity Pathways Analysis Integration - Ingenuity Pathways Analysis (IPA) is a software application that enables biologists and bioinformaticians to identify biological mechanisms, pathways and functions most relevant to their experimental datasets and genes of interest - (see G6G Abstract Number 20017U and below...).

Gene Ontology Browser - The Gene Ontology Browser is used to see where the records in your data set are located in a gene ontology hierarchy. With this tool, you can see subsets of genes from the visualizations, which appear in the ontology hierarchy and vice versa. It is also possible to perform searches in the gene ontology (GO) hierarchy.

Pathway Viewer - The Pathway Viewer is a custom panel which allows you to integrate pathway map information with your data set. You can visualize data from your analysis in pathway maps and highlight genes that are up- or down-regulated or differentially expressed.

Functional Analysis - Functional analysis is used to gain information about the biological processes affected by the experiment. IBD offers two (2) options for functional analysis: Annotation and Biological Enrichment.

CLICK AND GO® for one-click analysis --

Tools for Ad Hoc Analysis - The tools that are present in TIBCO Spotfire depend on the application package and licenses purchased. IBD includes Tools for: Data Preprocessing, Access, Statistical Analysis, Clustering, Class Prediction, Annotation Management, and Annotations.

Class Prediction - This step allows users to predict a response using a trained model. IBD provides two (2) algorithms for classification: Support Vector Machine (SVM) and Tree-based Ensemble Classifier.

Using a training dataset, it is possible to build several models and choose the appropriate one, while trying several combinations of kernel types and different parameters. Additionally, it is also possible to save all these models and use them for prediction of a desired response.

CLICK AND GO® - Launch a fully automatic execution of the analysis. At the end of the analysis, the steps of the analysis are generated displaying the results. Review any of the individual analysis steps, modify the data or the analysis parameters, and run the analysis again. Generate and save the Analysis Profile settings that will contain the parameters used in each step of the guided workflow.

How to Get the Most Out of IBD?

Support for common commercial array platforms - IBD accepts Affymetrix CEL, CHP and CDF files, or tab-delimited text files, including the standard output from Illumina, Agilent CGH, Agilent Two-Channel Gene Expression, Genepix, QuantArray, ScanArray, SMD, and Spot arrays.

Enhanced Human-Data Interaction - It is critical to ensure the reproducibility of the results and conclusions by carefully tracking the analysis steps.

Too often it is impossible for an independent group to repeat the same analysis using the same data - reducing the consistency and impact of the results.

During the analysis, a strict workflow should be followed to minimize inconsistencies or errors from discretional criteria or input of humans in the process.

IBD enables the users to follow a structured yet flexible process which will allow obtaining reliable and reproducible results. All steps in the Guide include a Help icon that explains all software features, and users are guided through the workflow.

The workflow enables the user to analyze the data tables, while linked to the TIBCO Spotfire advanced graphical and reporting capabilities for statistical analysis.

The user can go back and forth within the workflow, conducting various strategies and recalculating the results. It is also possible to perform a user driven analysis using the Tools to redesign and customize the workflow.

Advanced Statistics and Interactive Visualizations - Differential expression aims at computing the relative expression levels among hybridization groups. Methods are both for parametric and non-parametric data (as stated above…).

Explore Functional Annotations and Biological Enrichment - The functional analysis provides information concerning the Biological Processes, Cellular Components and Molecular Functions associated with the list of those genes appearing as differentially expressed under the conditions studied.

Different significance parameters are provided with the results obtained, allowing the user to filter and keep only those significant biological functionalities associated with the set of genes of interest.

Ingenuity Pathways Analysis Integration - Ingenuity Pathways Analysis (IPA) is a web-based software application that enables users to identify the biological mechanisms, pathways and functions most relevant to their experimental datasets or genes of interest.

IBD directly integrates with IPA allowing users to:

1) Understand microarray results in a biological context. Rapidly identify pathways, molecules, or diseases related to the respective data;

2) Analyze changes in biological states across time and dosages;

3) Create customized pathways for their targets, biomarkers, processes, and diseases of interest;

4) Integrate proprietary biological relationships into IPA pathways;

5) Analyze customized pathways to derive biological function;

6) Compute “shortest paths” between genes or sets of genes;

7) Search literature to access information on genes, pathways, or diseases; and

8) Easily create customized, publication quality graphics.

The Ingenuity Pathways Knowledge Base is one of the world’s largest databases of biological networks created from millions of individually modeled relationships between proteins, genes, complexes, cells, tissues, drugs, and diseases - (see G6G Abstract Number 20018U).

System Requirements

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Manufacturer Web Site Integromics Biomarker Discovery (IBD)

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G6G Abstract Number 20102

G6G Manufacturer Number 101520