2-AIN-506 a 2-AIN-252: Seminár z bioinformatiky (2) a (4)
Leto 2016

Emma Pierson, Daphne Koller, Alexis Battle, Sara Mostafavi, Kristin G. Ardlie, Gad Getz, Fred A. Wright, Manolis Kellis, Simona Volpi, Emmanouil T. Dermitzakis. Sharing and Specificity of Co-expression Networks across 35 Human Tissues. PLoS Comput Biol, 11(5):e1004220. 2015.

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To understand the regulation of tissue-specific gene expression, the GTEx
Consortium generated RNA-seq expression data for more than thirty distinct human 
tissues. This data provides an opportunity for deriving shared and tissue
specific gene regulatory networks on the basis of co-expression between genes.
However, a small number of samples are available for a majority of the tissues,
and therefore statistical inference of networks in this setting is highly
underpowered. To address this problem, we infer tissue-specific gene
co-expression networks for 35 tissues in the GTEx dataset using a novel
algorithm, GNAT, that uses a hierarchy of tissues to share data between related
tissues. We show that this transfer learning approach increases the accuracy with
which networks are learned. Analysis of these networks reveals that
tissue-specific transcription factors are hubs that preferentially connect to
genes with tissue specific functions. Additionally, we observe that genes with
tissue-specific functions lie at the peripheries of our networks. We identify
numerous modules enriched for Gene Ontology functions, and show that modules
conserved across tissues are especially likely to have functions common to all
tissues, while modules that are upregulated in a particular tissue are often
instrumental to tissue-specific function. Finally, we provide a web tool,
available at mostafavilab.stat.ubc.ca/GNAT, which allows exploration of gene
function and regulation in a tissue-specific manner.