ArticleNucleic acids research2009
A computational procedure to identify significant overlap of differentially expressed and genomic imbalanced regions in cancer datasets.
Article in Nucleic acids research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- A meta-analysis of multiple matched copy number and transcriptomics data sets for inferring gene regulatory relationships.PloS one · 2014Pooled it
- Trial
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- Efficient weighted univariate clustering maps outstanding dysregulated genomic zones in human cancers.Bioinformatics (Oxford, England) · 2020Article
- An Integrated Approach for RNA-seq Data Normalization.Cancer informatics · 2016Article
- Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential.BMC systems biology · 2015Review
- An integrated approach to reveal miRNAs' impacts on the functional consequence of copy number alterations in cancer.Scientific reports · 2015Article
- Article
- Detection of candidate tumor driver genes using a fully integrated Bayesian approach.Statistics in medicine · 2014Article
- An integrative characterization of recurrent molecular aberrations in glioblastoma genomes.Nucleic acids research · 2013Article
- Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review.Briefings in bioinformatics · 2013Review
- integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory.Bioinformatics (Oxford, England) · 2012Article
- Lessons from a decade of integrating cancer copy number alterations with gene expression profiles.Briefings in bioinformatics · 2012Article
- Comparative analysis of algorithms for integration of copy number and expression data.Nature methods · 2012Article
- Patient-specific data fusion defines prognostic cancer subtypes.PLoS computational biology · 2011Article
Corrections and comments
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of high-throughput genomic data represents an opportunity for deciphering the interplay between structural and functional organization of genomes and for discovering novel biomarkers. However, the development of integrative approaches to complement gene expression (GE) data with other types of gene information, such as copy number (CN) and chromosomal localization, still represents a computational challenge in the genomic arena. This work presents a computational procedure that directly integrates CN and GE profiles at genome-wide level. When applied to DNA/RNA paired data, this approach leads to the identification of Significant Overlaps of Differentially Expressed and Genomic Imbalanced Regions (SODEGIR). This goal is accomplished in three steps. The first step extends to CN a method for detecting regional imbalances in GE. The second part provides the integration of CN and GE data and identifies chromosomal regions with concordantly altered genomic and transcriptional status in a tumor sample. The last step elevates the single-sample analysis to an entire dataset of tumor specimens. When applied to study chromosomal aberrations in a collection of astrocytoma and renal carcinoma samples, the procedure proved to be effective in identifying discrete chromosomal regions of coordinated CN alterations and changes in transcriptional levels.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.