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Bioinformatics. 2014 Jun 1;30(11):1493-500. doi: 10.1093/bioinformatics/btu035. Epub 2014 Jan 30.

Comparing DNA integration site clusters with scan statistics.

Author information

1
Division of Biostatistics and BioInformatics, Department of Family and Preventive Medicine, University of California at San Diego, La Jolla, CA 92093-0901 and Department of Microbiology, Perelman School of Medicine at the University of Pennsylvania, 425 Johnson Pavilion, Philadelphia, PA 19104-6076, USA.

Abstract

MOTIVATION:

Gene therapy with retroviral vectors can induce adverse effects when those vectors integrate in sensitive genomic regions. Retroviral vectors are preferred that target sensitive regions less frequently, motivating the search for localized clusters of integration sites and comparison of the clusters formed by integration of different vectors. Scan statistics allow the discovery of spatial differences in clustering and calculation of false discovery rates providing statistical methods for comparing retroviral vectors.

RESULTS:

A scan statistic for comparing two vectors using multiple window widths is proposed with software to detect clustering differentials and compute false discovery rates. Application to several sets of experimentally determined HIV integration sites demonstrates the software. Simulated datasets of various sizes and signal strengths are used to determine the power to discover clusters and evaluate a convenient lower bound. This provides a toolkit for planning evaluations of new gene therapy vectors.

AVAILABILITY AND IMPLEMENTATION:

The geneRxCluster R package containing a simple tutorial and usage hints is available from http://www.bioconductor.org.

PMID:
24489369
PMCID:
PMC4029028
DOI:
10.1093/bioinformatics/btu035
[Indexed for MEDLINE]
Free PMC Article

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