Distributed gene expression modelling for exploring variability in epigenetic function.
BACKGROUND
Predictive gene expression modelling is an important tool in computational biology due to the volume of high-throughput sequencing data generated by recent consortia. However, the scope of previous studies has been restricted to a small set of cell-lines or experimental conditions due an inability to leverage distributed processing architectures for large, sharded data-sets.


RESULTS
We present a distributed implementation of gene expression modelling using the MapReduce paradigm and prove that performance improves as a linear function of available processor cores. We then leverage the computational efficiency of this framework to explore the variability of epigenetic function across fifty histone modification data-sets from variety of cancerous and non-cancerous cell-lines.


CONCLUSIONS
We demonstrate that the genome-wide relationships between histone modifications and mRNA transcription are lineage, tissue and karyotype-invariant, and that models trained on matched -omics data from non-cancerous cell-lines are able to predict cancerous expression with equivalent genome-wide fidelity.
Massachusetts Institute of Technology, Computer Science and Artificial Intelligence Laboratory, Cambridge, 02139, USA. budden@csail.mit.edu.|Systems Biology Laboratory, Melbourne School of Engineering, the University of Melbourne, Parkville, 3010, Australia. budden@csail.mit.edu.
David M
DM
Budden
Systems Biology Laboratory, Melbourne School of Engineering, the University of Melbourne, Parkville, 3010, Australia.|ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Parkville, 3010, Australia.|Department of Mathematics and Statistics, the University of Melbourne, Parkville, 3010, Australia.|School of Medicine, the University of Melbourne, Parkville, 3010, Australia.
Edmund J
EJ
Crampin
D047369:Chromatin Immunoprecipitation / Q000379:methods; D019295:Computational Biology / Q000379:methods*; D057890:Epigenomics; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D015894:Genome, Human; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods; D006657:Histones / Q000235:genetics* / Q000378:metabolism; D006801:Humans; D009369:Neoplasms / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods; D014158:Transcription, Genetic / Q000235:genetics*
D006657:Histones
Epigenetics; Gene expression; Histone modifications; MapReduce