MD-SeeGH: a platform for integrative analysis of multi-dimensional genomic data.

Abstract:

BACKGROUND:Recent advances in global genomic profiling methodologies have enabled multi-dimensional characterization of biological systems. Complete analysis of these genomic profiles require an in depth look at parallel profiles of segmental DNA copy number status, DNA methylation state, single nucleotide polymorphisms, as well as gene expression profiles. Due to the differences in data types it is difficult to conduct parallel analysis of multiple datasets from diverse platforms. RESULTS:To address this issue, we have developed an integrative genomic analysis platform MD-SeeGH, a software tool that allows users to rapidly and directly analyze genomic datasets spanning multiple genomic experiments. With MD-SeeGH, users have the flexibility to easily update datasets in accordance with new genomic builds, make a quality assessment of data using the filtering features, and identify genetic alterations within single or across multiple experiments. Multiple sample analysis in MD-SeeGH allows users to compare profiles from many experiments alongside tracks containing detailed localized gene information, microRNA, CpG islands, and copy number variations. CONCLUSION:MD-SeeGH is a new platform for the integrative analysis of diverse microarray data, facilitating multiple profile analyses and group comparisons.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Chi B,deLeeuw RJ,Coe BP,Ng RT,MacAulay C,Lam WL

doi

10.1186/1471-2105-9-243

subject

Has Abstract

pub_date

2008-05-20 00:00:00

pages

243

issn

1471-2105

pii

1471-2105-9-243

journal_volume

9

pub_type

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