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AnyExpress: integrated toolkit for analysis of cross-platform gene expression data using a fast interval matching

Jihoon Kim¹, Kiltesh Patel, Hyunchul Jung

¹Division of Biomedical Informatics, University of California, San Diego, CA, USA.

BMC Bioinformatics

|March 18, 2011

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AnyExpress integrates gene expression data across platforms like next-generation sequencing and microarrays. This flexible software allows custom references and filtering, improving cross-platform analysis accuracy.

Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Gene expression analysis across diverse platforms presents significant challenges due to intricate, multi-layered processes.
Existing tools lack flexibility, are limited to single platforms, and struggle with custom modifications for new methods or data.
Tight coupling with potentially erroneous or outdated reference data (genomes, transcriptomes, SNPs) leads to inaccurate results.

Purpose of the Study:

To develop a flexible and comprehensive software package for cross-platform gene expression data integration.
To enable users to define custom references and filtering criteria for improved analysis accuracy.
To provide scalable processing features not found in current tools.

Main Methods:

Developed AnyExpress, a software package utilizing a fast interval-matching algorithm for cross-platform data integration.

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Supported diverse platforms including next-generation sequencing (NGS), microarray, SAGE, and MPSS.

Enabled user-defined custom transcriptome references and probe/read filtering criteria.

Incorporated scalable processing features: binding, normalization, and summarization.

Main Results:

AnyExpress successfully combined gene expression data from Affymetrix microarray and Illumina NGS RNA-Seq.
High within-platform correlation coefficients (mean 0.98) were observed for human kidney and liver samples.
A mean cross-platform correlation coefficient of 0.73 was achieved, validating original and secondary study findings.
Applying custom filtering enhanced agreement between microarray and NGS data, as indicated by an agreement index.

Conclusions:

AnyExpress effectively integrates cross-platform gene expression data from open and closed platforms.
The software allows custom reference selection and filtering of undesirable probes/reads.
AnyExpress supports quantile-normalization for large microarray datasets and is freely available.
The package is characterized by speed, comprehensiveness, and flexibility.