Introduction

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.

Publications

  1. Exploring massive, genome scale datasets with the GenometriCorr package.
    Cite this
    Favorov A, Mularoni L, Cope LM, Medvedeva Y, Mironov AA, Makeev VJ, Wheelan SJ, 2012-05-01 - PLoS computational biology

Credits

  1. Alexander Favorov
    Developer

    Department of Oncology, Division of Biostatistics and Bioinformatics

  2. Loris Mularoni
    Developer

  3. Leslie M Cope
    Developer

  4. Yulia Medvedeva
    Developer

  5. Andrey A Mironov
    Developer

  6. Vsevolod J Makeev
    Developer

  7. Sarah J Wheelan
    Investigator

Community Ratings

UsabilityEfficiencyReliabilityRated By
0 user
Sign in to rate
Summary
AccessionBT001218
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted BySarah J Wheelan