MD-SeeGH: a platform for integrative analysis of multi-dimensional genomic data
Bryan Chi1, Ronald J deLeeuw, Bradley P Coe
1Department of Cancer Genetics and Developmental Biology, British Columbia Cancer Research Centre, Vancouver, BC, Canada. bchi@bccrc.ca
BMC Bioinformatics
|May 22, 2008
Summary
MD-SeeGH integrates diverse genomic datasets for multi-dimensional analysis. This software tool enables rapid comparison of multiple genomic experiments, aiding in the identification of genetic alterations.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Global genomic profiling advances enable multi-dimensional biological system characterization.
- Comprehensive analysis requires integrating diverse data types like DNA copy number, methylation, SNPs, and gene expression.
- Analyzing multiple datasets from different platforms presents significant challenges.
Purpose of the Study:
- To develop an integrative genomic analysis platform for multi-dimensional datasets.
- To facilitate rapid and direct analysis of genomic data from various experiments.
- To enable parallel analysis of multiple genomic profiles.
Main Methods:
- Development of the MD-SeeGH software platform.
- Implementation of features for updating datasets with new genomic builds.
- Inclusion of data quality assessment and filtering capabilities.
- Support for analyzing single or multiple experiments.
Main Results:
- MD-SeeGH allows rapid, direct analysis of genomic datasets across multiple experiments.
- Users can easily update datasets and perform quality assessments.
- The platform identifies genetic alterations within single or across multiple experiments.
- MD-SeeGH supports multiple sample analysis, comparing profiles with gene information, microRNA, CpG islands, and copy number variations.
Conclusions:
- MD-SeeGH is a novel platform for the integrative analysis of diverse microarray data.
- It facilitates multi-profile analyses and group comparisons.
- The tool enhances the ability to study complex genomic data.
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