{"doi":"10.1093/bioinformatics/btq009","title":"Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS","abstract":"<h4>Motivation</h4>Epistasis, the presence of gene-gene interactions, has been hypothesized to be at the root of many common human diseases, but current genome-wide association studies largely ignore its role. Multifactor dimensionality reduction (MDR) is a powerful model-free method for detecting epistatic relationships between genes, but computational costs have made its application to genome-wide data difficult. Graphics processing units (GPUs), the hardware responsible for rendering computer games, are powerful parallel processors. Using GPUs to run MDR on a genome-wide dataset allows for statistically rigorous testing of epistasis.<h4>Results</h4>The implementation of MDR for GPUs (MDRGPU) includes core features of the widely used Java software package, MDR. This GPU implementation allows for large-scale analysis of epistasis at a dramatically lower cost than the standard CPU-based implementations. As a proof-of-concept, we applied this software to a genome-wide study of sporadic amyotrophic lateral sclerosis (ALS). We discovered a statistically significant two-SNP classifier and subsequently replicated the significance of these two SNPs in an independent study of ALS. MDRGPU makes the large-scale analysis of epistasis tractable and opens the door to statistically rigorous testing of interactions in genome-wide datasets.<h4>Availability</h4>MDRGPU is open source and available free of charge from http://www.sourceforge.net/projects/mdr.","journal":"Bioinformatics","year":2010,"id":5702,"datarank":0.6307038929086449,"base_score":4.204692619390966,"endowment":4.204692619390966,"self_citation_contribution":0.6307038929086449,"citation_network_contribution":0.0,"self_endowment_contribution":0.6307038929086449,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":66,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0427,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2010-01-16","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":23882,"name":"Nicholas A Sinnott-Armstrong","orcid":null,"position":1,"is_corresponding":false},{"id":1208,"name":"Daniel S. Himmelstein","orcid":"0000-0002-3012-7446","position":2,"is_corresponding":false},{"id":55227,"name":"Paul J. Park","orcid":null,"position":3,"is_corresponding":false},{"id":14812,"name":"Jason H. Moore","orcid":"0000-0002-5015-1099","position":4,"is_corresponding":false},{"id":55228,"name":"Brent T. Harris","orcid":"0000-0002-9746-4906","position":5,"is_corresponding":false},{"id":23896,"name":"Nicholas A. Sinnott‐Armstrong","orcid":null,"position":6,"is_corresponding":false},{"id":308,"name":"Casey S. Greene","orcid":"0000-0001-8713-9213","position":0,"is_corresponding":true}],"reference_count":10,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}