Estimating Enrichment of Repetitive Elements from High-throughput Sequence Data

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Estimating Enrichment of Repetitive Elements from High-throughput Sequence Data

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Title: Estimating Enrichment of Repetitive Elements from High-throughput Sequence Data
Author: Day, Daniel Sindt; Luquette, Lovelace j; Park, Peter J.; Kharchenko, Peter Vasili

Note: Order does not necessarily reflect citation order of authors.

Citation: Day, Daniel S., Lovelace J. Luquette, Peter J. Park, and Peter V. Kharchenko. 2010. Estimating enrichment of repetitive elements from high-throughput sequence data. Genome Biology 11(6): R69.
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Abstract: We describe computational methods for analysis of repetitive elements from short-read sequencing data, and apply them to study histone modifications associated with the repetitive elements in human and mouse cells. Our results demonstrate that while accurate enrichment estimates can be obtained for individual repeat types and small sets of repeat instances, there are distinct combinatorial patterns of chromatin marks associated with major annotated repeat families, including H3K27me3/H3K9me3 differences among the endogenous retroviral element classes.
Published Version: doi:10.1186/gb-2010-11-6-r69
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2911117/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:4725502

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