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Pathway-based analysis of microarray and RNAseq data using Pathway Processor 2.0.

Luca Beltrame¹, Luca Bianco², Paolo Fontana²

¹Translational Genomics Unit, Department of Oncology, Mario Negri Research Institute, Milan, Italy.

Current Protocols in Bioinformatics

|March 19, 2013

Summary

This summary is machine-generated.

Pathway Processor 2.0 enhances pathway analysis for high-throughput data, supporting more species and RNAseq. This tool offers improved methods for understanding system-level experimental results and phenotypic differences.

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Area of Science:

Bioinformatics
Systems Biology
Genomics

Background:

High-throughput technologies generate vast amounts of experimental data.
Pathway analysis is crucial for interpreting system-level biological insights.
Existing tools require updates to handle new data types and analysis methods.

Purpose of the Study:

To introduce Pathway Processor 2.0, an upgraded web-based tool for pathway analysis.
To expand support for diverse species, analysis techniques, and RNA sequencing (RNAseq) data alongside microarrays.
To provide novel methods for investigating phenotypic differences through pathway-based approaches.

Main Methods:

Implementation of traditional Fisher's Test and novel topology-aware analyses.
Development of a new pathway-based method for phenotype comparison.
Web-based interface design for user accessibility and ease of use.

Main Results:

Pathway Processor 2.0 supports an expanded range of species and data types (microarrays and RNAseq).
The tool incorporates both traditional and advanced topology-aware pathway analysis methods.
A new method enables the investigation of differences between biological phenotypes.

Conclusions:

Pathway Processor 2.0 provides a versatile and enhanced platform for systems-level biological data interpretation.
The updated tool facilitates deeper understanding of experimental results through advanced pathway analysis.
It addresses the growing need for sophisticated analysis of high-throughput biological data.