Exploring massive, genome scale datasets with the GenometriCorr package

We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically...

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Bibliographic Details
Published in:PLoS computational biology 2012-05, Vol.8 (5), p.e1002529-e1002529
Main Authors: Favorov, Alexander, Mularoni, Loris, Cope, Leslie M, Medvedeva, Yulia, Mironov, Andrey A, Makeev, Vsevolod J, Wheelan, Sarah J
Format: Article
Language:English
Subjects:
Analysis
Animals
Biology
Chromosomes
Databases, Genetic
Epigenomics
Genetic Loci
Genome
Genomes
Genomics - methods
Humans
Information Storage and Retrieval
Internet
Mathematics
Models, Genetic
Models, Statistical
RNA, Transfer - genetics
Software
Statistical methods
Statistics, Nonparametric
User-Computer Interface
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Summary:We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1002529