Spark: A navigational paradigm for genomic data exploration
- Cydney B Nielsen1,10,
- Hamid Younesy2,
- Henriette O'Geen3,
- Xiaoqin Xu3,
- Andrew R Jackson4,
- Aleksandar Milosavljevic4,
- Ting Wang5,
- Joseph F Costello6,
- Martin Hirst7,
- Peggy J Farnham8 and
- Steven JM Jones9
- 1 BC Cancer Agency, Genome Science Centre;
- 2 Simon Fraser University;
- 3 University of California - Davis;
- 4 Epigenome Center, Department of Molecular and Human Genetics, Baylor College of Medicine;
- 5 Washington University School of Medicine;
- 6 UCSF;
- 7 BCCA-Genome Sciences Centre;
- 8 University of Southern California;
- 9 BC Cancer Agency
- ↵* Corresponding author; email: cydneyn{at}bcgsc.ca
Abstract
Biologists possess the detailed knowledge critical for extracting biological insight from genome-wide data resources and yet they are increasingly faced with non-trivial computational analysis challenges posed by genome-scale methodologies. To lower this computational barrier, particularly in the early data exploration phases, we have developed an interactive pattern discovery and visualization approach, Spark, designed with epigenomic data in mind. Here we demonstrate Spark's ability to reveal both known and novel epigenetic signatures, including a previously unappreciated binding association between the YY1 transcription factor and the co-repressor CTBP2 in human embryonic stem cells.
- Received March 16, 2012.
- Accepted August 10, 2012.
- © 2012, Published by Cold Spring Harbor Laboratory Press
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