Li, ZilinZilinLiLi, XihaoXihaoLiZhou, HufengHufengZhouGaynor, Sheila MSheila MGaynorSelvaraj, Margaret SunithaMargaret SunithaSelvarajArapoglou, TheodoreTheodoreArapoglouQuick, CorbinCorbinQuickLiu, YaowuYaowuLiuChen, HanHanChenSun, RyanRyanSunDey, RounakRounakDeyArnett, Donna KDonna KArnettAuer, Paul LPaul LAuerBielak, Lawrence FLawrence FBielakBis, Joshua CJoshua CBisBlackwell, Thomas WThomas WBlackwellBlangero, JohnJohnBlangeroBoerwinkle, EricEricBoerwinkleBowden, Donald WDonald WBowdenBrody, Jennifer AJennifer ABrodyCade, Brian EBrian ECadeConomos, Matthew PMatthew PConomosCorrea, AdolfoAdolfoCorreaCupples, L AdrienneL AdrienneCupplesCurran, Joanne EJoanne ECurrande Vries, Paul SPaul Sde VriesDuggirala, RavindranathRavindranathDuggiralaFranceschini, NoraNoraFranceschiniFreedman, Barry IBarry IFreedmanGöring, Harald H HHarald H HGöringGuo, XiuqingXiuqingGuoKalyani, Rita RRita RKalyaniKooperberg, CharlesCharlesKooperbergKral, Brian GBrian GKralLange, Leslie ALeslie ALangeLin, Bridget MBridget MLinManichaikul, AniAniManichaikulManning, Alisa KAlisa KManningMartin, Lisa WLisa WMartinMathias, Rasika ARasika AMathiasMeigs, James BJames BMeigsMitchell, Braxton DBraxton DMitchellMontasser, May EMay EMontasserMorrison, Alanna CAlanna CMorrisonNaseri, TakeTakeNaseriO'Connell, Jeffrey RJeffrey RO'ConnellPalmer, Nicholette DNicholette DPalmerPeyser, Patricia APatricia APeyserPsaty, Bruce MBruce MPsatyRaffield, Laura MLaura MRaffieldRedline, SusanSusanRedlineReiner, Alexander PAlexander PReinerReupena, Muagututi'a SefuivaMuagututi'a SefuivaReupenaRice, Kenneth MKenneth MRiceRich, Stephen SStephen SRichSmith, Jennifer AJennifer ASmithTaylor, Kent DKent DTaylorTaub, Margaret AMargaret ATaubVasan, Ramachandran SRamachandran SVasanWeeks, Daniel EDaniel EWeeksWilson, James GJames GWilsonYanek, Lisa RLisa RYanekZhao, WeiWeiZhaoRotter, Jerome IJerome IRotterWiller, Cristen JCristen JWillerNatarajan, PradeepPradeepNatarajanPeloso, Gina MGina MPelosoLin, XihongXihongLinLEE-MING CHUANG et al.2024-04-262024-04-262022-1215487091https://scholars.lib.ntu.edu.tw/handle/123456789/642059Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.enjournal article10.1038/s41592-022-01640-x363030182-s2.0-85143379527https://api.elsevier.com/content/abstract/scopus_id/85143379527