Finding associations among histone modifications using sparse partial correlation networks.
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ABSTRACT: Histone modifications are known to play an important role in the regulation of transcription. While individual modifications have received much attention in genome-wide analyses, little is known about their relationships. Some authors have built Bayesian networks of modifications, however most often they have used discretized data, and relied on unrealistic assumptions such as the absence of feedback mechanisms or hidden confounding factors. Here, we propose to infer undirected networks based on partial correlations between histone modifications. Within the partial correlation framework, correlations among two variables are controlled for associations induced by the other variables. Partial correlation networks thus focus on direct associations of histone modifications. We apply this metho
SUBMITTER: Lasserre J
PROVIDER: S-EPMC3764007 | biostudies-literature | 2013
REPOSITORIES: biostudies-literature
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