A sequence-based method to predict the impact of regulatory variants using random forest
Liu Q, Gan M, Jiang R. A sequence-based method to predict the impact of regulatory variants using random forest. BMC Systems Biology 2017, 11: 7. PMID: 28361702, PMCID: PMC5374684, DOI: 10.1186/s12918-017-0389-1.Peer-Reviewed Original ResearchConceptsSingle nucleotide polymorphismsGenome-wide association studiesK-mer featuresK-mersGenome sequenceChromatin regionsDNA sequencesGenetic variantsImpact of regulatory variantsRandom genomic sequencesSequence conservation featuresIdentification of genetic risk factorsDisease-Associated VariantsSequence-based methodsK-mer countingImpact of single nucleotide polymorphismsBreast cancer cell linesRegulatory variantsGenetic risk factorsNoncoding regionsComplex traitsAssociation studiesRegulatory elementsCancer cell linesPermutation experiments
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply