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Han B, Altman NS, Mong JA, et al. Comparing quantitative trait Loci and gene expression data. Adv Bioinformatics. 2008;719818doi: 10.1155/2008/719818.
Han, B., Altman, N. S., Mong, J. A., Klein, L. C., Pfaff, D. W., & Vandenbergh, D. J. (2008). Comparing quantitative trait Loci and gene expression data. Advances in bioinformatics, 719818. https://doi.org/10.1155/2008/719818
Han, Bing, et al. "Comparing quantitative trait Loci and gene expression data." Advances in bioinformatics vol. (2008): 719818. doi: https://doi.org/10.1155/2008/719818
Han B, Altman NS, Mong JA, Klein LC, Pfaff DW, Vandenbergh DJ. Comparing quantitative trait Loci and gene expression data. Adv Bioinformatics. 2008;719818. doi: 10.1155/2008/719818. Epub 2008 Sep 16. PMID: 19920989; PMCID: PMC2775685.
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Adv Bioinformatics. 2008;719818. doi: 10.1155/2008/719818. Epub 2008 Sep 16.

Comparing quantitative trait Loci and gene expression data.

Advances in bioinformatics

Bing Han, Naomi S Altman, Jessica A Mong, Laura Cousino Klein, Donald W Pfaff, David J Vandenbergh

Affiliations

  1. RAND Corporation, Santa Monica, CA 90407, USA.

PMID: 19920989 PMCID: PMC2775685 DOI: 10.1155/2008/719818

Abstract

We develop methods to compare the positions of quantitative trait loci (QTL) with a set of genes selected by other methods, such as microarray experiments, from a sequenced genome. We apply our methods to QTL for addictive behavior in mouse, and a set of genes upregulated in a region of the brain associated with addictive behavior, the nucleus accumbens (NA). The association between the QTL and NA genes is not significantly stronger than expected by chance. However, chromosomes 2 and 16 do show strong associations suggesting that genes on these chromosomes might be associated with addictive behavior. The statistical methodology developed for this study can be applied to similar studies to assess the mutual information in microarray and QTL analyses.

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