Mapping transcription mechanisms from multimodal genomic data
Name
Chang-2010-Mapping transcription mechanisms from multimodal genomic data.pdf
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Author(s)
Chang, Hsun-Hsien
McGeachie, Michael John
Alterovitz, Gil
Ramoni, Marco F.
Date Issued
October 2010
Journal
BMC Bioinformatics
Publisher
Springer (Biomed Central Ltd.)
Citation
Chang, Hsun-Hsien et al. “Mapping Transcription Mechanisms from Multimodal Genomic Data.” BMC Bioinformatics 11.Suppl 9 (2010): S2. Web. 9 Mar. 2012.
Version
Final published version
Abstract
Background
Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene expression data, raising a new computational challenge due to the tremendous size of data.
Results
We develop a method to identify eQTLs. The method represents eQTLs as information flux between genetic variants and transcripts. We use information theory to simultaneously interrogate SNP and gene expression data, resulting in a Transcriptional Information Map (TIM) which captures the network of transcriptional information that links genetic variations, gene expression and regulatory mechanisms. These maps are able to identify both cis- and trans- regulating eQTLs. The application on a dataset of leukemia patients identifies eQTLs in the regions of the GART, PCP4, DSCAM, and RIPK4 genes that regulate ADAMTS1, a known leukemia correlate.
Conclusions
The information theory approach presented in this paper is able to infer the dependence networks between SNPs and transcripts, which in turn can identify cis- and trans-eQTLs. The application of our method to the leukemia study explains how genetic variants and gene expression are linked to leukemia.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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DOI of Published Version
https://doi.org/10.1186/1471-2105-11-s9-s2
