TreeWAS – [N45.0] Orchitis, epididymitis and epididymo-orchitis with abscess

Variant effects

Click on a variant to see its association results.

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Genome-wide Chromosomes: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

Results table

Variant	Risk posterior probability	No effect posterior probability	Protective posterior probability
rs117898740 lBF = `16.4579` Chr`17` : `78,886,505`	0.609	0.390	0.000
rs116996274 lBF = `16.8749` Chr`17` : `72,204,105`	0.584	0.416	0.000
rs79719602 lBF = `22.0554` Chr`17` : `68,033,186`	0.569	0.431	0.000
rs116920450 lBF = `24.9206` Chr`17` : `48,653,130`	0.530	0.470	0.000
rs58842514 lBF = `17.5944` Chr`17` : `76,367,270`	0.523	0.477	0.000
rs8753 lBF = `31.436` Chr`17` : `7,417,640`	0.494	0.506	0.000
rs75493593 lBF = `2.71768` Chr`17` : `6,945,087`	0.449	0.550	0.000
rs75418188 lBF = `2.82841` Chr`17` : `6,945,483`	0.449	0.551	0.000
rs78378222 lBF = `67.1003` Chr`17` : `7,571,752`	0.437	0.562	0.000
rs117611723 lBF = `13.8737` Chr`17` : `35,913,589`	0.436	0.564	0.000
rs117478093 lBF = `18.0142` Chr`17` : `6,027,422`	0.435	0.565	0.000
rs295891 lBF = `12.2585` Chr`17` : `35,117,132`	0.430	0.570	0.000
rs16966833 lBF = `11.2571` Chr`17` : `30,035,727`	0.429	0.571	0.000
rs117140019 lBF = `22.4153` Chr`17` : `27,396,153`	0.422	0.578	0.000
rs147068743 lBF = `2.09018` Chr`17` : `1,363,475`	0.420	0.580	0.000
rs11571358 lBF = `14.967` Chr`17` : `6,899,106`	0.414	0.586	0.000
rs117010525 lBF = `14.7473` Chr`17` : `46,605,689`	0.412	0.588	0.000
rs118134255 lBF = `10.2692` Chr`17` : `78,461,019`	0.405	0.595	0.000
rs79989254 lBF = `16.0938` Chr`17` : `63,468,858`	0.389	0.610	0.000
rs117174162 lBF = `17.8894` Chr`17` : `27,546,321`	0.375	0.625	0.000
rs117891146 lBF = `16.7401` Chr`17` : `77,212,307`	0.358	0.642	0.000
rs7211756 lBF = `2.27651` Chr`17` : `15,899,675`	0.350	0.650	0.000
rs116971837 lBF = `14.357` Chr`17` : `8,680,917`	0.343	0.657	0.000
rs117813251 lBF = `20.0984` Chr`17` : `74,197,931`	0.339	0.661	0.000
rs35850753 lBF = `52.2551` Chr`17` : `7,578,671`	0.309	0.691	0.000
rs118155463 lBF = `21.1268` Chr`17` : `8,079,842`	0.308	0.692	0.000
rs2005705 lBF = `18.9001` Chr`17` : `36,096,300`	0.289	0.711	0.000
rs2250422 lBF = `11.7971` Chr`17` : `48,351,018`	0.288	0.712	0.000
rs147985248 lBF = `11.1689` Chr`17` : `61,615,545`	0.286	0.714	0.000
rs77697917 lBF = `0.477247` Chr`17` : `41,840,849`	0.280	0.720	0.000
rs61753150 lBF = `23.5631` Chr`17` : `15,973,774`	0.277	0.722	0.000
rs72820359 lBF = `9.17012` Chr`17` : `1,523,967`	0.271	0.729	0.000
rs181807530 lBF = `6.07401` Chr`17` : `4,774,814`	0.268	0.731	0.000
rs72845883 lBF = `14.3782` Chr`17` : `61,658,297`	0.267	0.733	0.000
rs8072843 lBF = `1.06281` Chr`17` : `54,638,948`	0.255	0.745	0.000
rs116847944 lBF = `14.8527` Chr`17` : `32,238,030`	0.251	0.749	0.000
rs117647575 lBF = `15.1304` Chr`17` : `71,591,669`	0.243	0.757	0.000
rs181387571 lBF = `18.0545` Chr`17` : `16,249,665`	0.242	0.758	0.000
rs117654928 lBF = `7.86182` Chr`17` : `72,690,643`	0.242	0.758	0.000
rs34289250 lBF = `9.46458` Chr`17` : `59,880,646`	0.240	0.760	0.000
rs4788957 lBF = `12.6822` Chr`17` : `74,924,327`	0.235	0.764	0.000
rs117156109 lBF = `29.2944` Chr`17` : `75,856,929`	0.231	0.768	0.000
rs190627217 lBF = `13.7219` Chr`17` : `45,811,915`	0.183	0.817	0.000
rs76731769 lBF = `14.8647` Chr`17` : `35,063,138`	0.180	0.820	0.000
rs62076101 lBF = `21.8133` Chr`17` : `45,882,243`	0.177	0.823	0.000
rs11263763 lBF = `28.9425` Chr`17` : `36,103,565`	0.156	0.844	0.000
rs6258 lBF = `5.18323` Chr`17` : `7,534,678`	0.149	0.850	0.000
rs79665456 lBF = `13.4635` Chr`17` : `36,203,084`	0.144	0.855	0.000
rs193042029 lBF = `0.233194` Chr`17` : `4,667,984`	0.129	0.871	0.000
rs9906595 lBF = `0.476633` Chr`17` : `37,101,380`	0.121	0.878	0.001
rs8066099 lBF = `8.67262` Chr`17` : `14,889,925`	0.122	0.878	0.000
rs12943829 lBF = `1.06626` Chr`17` : `70,826,404`	0.117	0.883	0.000
rs74969489 lBF = `14.9351` Chr`17` : `45,452,257`	0.108	0.892	0.000
rs55749608 lBF = `15.2225` Chr`17` : `3,800,118`	0.104	0.895	0.001
rs1178422 lBF = `6.83318` Chr`17` : `5,863,924`	0.105	0.895	0.000
rs117180213 lBF = `18.1114` Chr`17` : `46,070,227`	0.102	0.898	0.000
rs77068175 lBF = `13.8412` Chr`17` : `11,117,116`	0.093	0.906	0.000
rs11651052 lBF = `28.1116` Chr`17` : `36,102,381`	0.091	0.909	0.000
rs79045038 lBF = `6.0483` Chr`17` : `66,397,041`	0.088	0.912	0.000
rs117024145 lBF = `17.1515` Chr`17` : `8,005,847`	0.086	0.914	0.000
rs143813799 lBF = `18.0084` Chr`17` : `60,023,795`	0.081	0.919	0.000
rs61735289 lBF = `10.6259` Chr`17` : `73,747,128`	0.077	0.923	0.000
rs2663357 lBF = `14.3146` Chr`17` : `811,874`	0.069	0.931	0.000
rs7221360 lBF = `16.9886` Chr`17` : `52,448,143`	0.067	0.933	0.000
rs10908278 lBF = `30.2505` Chr`17` : `36,099,952`	0.057	0.943	0.000
rs11652121 lBF = `15.4813` Chr`17` : `28,532,332`	0.057	0.943	0.000
rs3744064 lBF = `4.44478` Chr`17` : `75,211,208`	0.056	0.944	0.000
rs8064454 lBF = `28.4566` Chr`17` : `36,101,586`	0.054	0.946	0.000
rs34826591 lBF = `8.99693` Chr`17` : `38,246,454`	0.050	0.950	0.000
rs16969149 lBF = `15.1993` Chr`17` : `74,640,113`	0.046	0.952	0.001
rs62070016 lBF = `9.95585` Chr`17` : `9,170,659`	0.045	0.955	0.000
rs12603526 lBF = `5.55678` Chr`17` : `800,593`	0.045	0.955	0.000
rs150418526 lBF = `0.141922` Chr`17` : `36,853,840`	0.043	0.956	0.000
rs12150130 lBF = `14.6179` Chr`17` : `14,117,282`	0.042	0.958	0.000
rs7221713 lBF = `15.6984` Chr`17` : `59,735,398`	0.038	0.962	0.000
rs118166304 lBF = `25.1727` Chr`17` : `48,951,566`	0.037	0.962	0.000
rs7405776 lBF = `13.8246` Chr`17` : `36,093,022`	0.000	0.964	0.036
rs76597414 lBF = `16.1863` Chr`17` : `72,191,445`	0.034	0.966	0.000
rs77855512 lBF = `16.0644` Chr`17` : `12,141,091`	0.034	0.966	0.000
rs73335365 lBF = `15.72` Chr`17` : `6,140,995`	0.033	0.966	0.000
rs114144436 lBF = `12.5218` Chr`17` : `2,832,984`	0.033	0.967	0.001
rs56150553 lBF = `20.6531` Chr`17` : `73,389,145`	0.031	0.969	0.000
rs117032670 lBF = `19.5025` Chr`17` : `7,807,438`	0.029	0.971	0.000
rs7501939 lBF = `23.6632` Chr`17` : `36,101,156`	0.000	0.974	0.026
rs74471121 lBF = `15.6908` Chr`17` : `6,108,771`	0.024	0.975	0.000
rs111816999 lBF = `0.159181` Chr`17` : `6,882,443`	0.021	0.978	0.000
rs9913352 lBF = `7.55706` Chr`17` : `53,818,042`	0.022	0.978	0.000
rs41282071 lBF = `12.1955` Chr`17` : `73,316,880`	0.021	0.979	0.000
rs62086354 lBF = `9.78308` Chr`17` : `73,039,818`	0.021	0.979	0.000
rs35042707 lBF = `15.0584` Chr`17` : `33,861,639`	0.020	0.980	0.000
rs79549931 lBF = `22.7675` Chr`17` : `66,178,996`	0.019	0.980	0.000
rs55771008 lBF = `13.6178` Chr`17` : `73,338,557`	0.020	0.980	0.000
rs74976893 lBF = `0.505264` Chr`17` : `69,729,925`	0.015	0.985	0.000
rs3744763 lBF = `8.02105` Chr`17` : `36,090,885`	0.000	0.986	0.014
rs79392787 lBF = `0.0415236` Chr`17` : `6,250,054`	0.013	0.987	0.001
rs12602637 lBF = `7.79106` Chr`17` : `72,766,408`	0.012	0.988	0.000
rs74618301 lBF = `5.19595` Chr`17` : `52,933,266`	0.012	0.988	0.000
rs186788172 lBF = `0.0152099` Chr`17` : `1,239,189`	0.011	0.989	0.000
rs78288136 lBF = `13.1867` Chr`17` : `12,422,621`	0.010	0.989	0.001
rs73976923 lBF = `0.0340911` Chr`17` : `6,282,471`	0.010	0.989	0.000
rs17138899 lBF = `5.85345` Chr`17` : `35,573,686`	0.010	0.990	0.000
rs113865542 lBF = `9.26168` Chr`17` : `77,176,256`	0.009	0.991	0.000
rs62078063 lBF = `17.445` Chr`17` : `34,286,452`	0.008	0.992	0.000
rs74577983 lBF = `12.6549` Chr`17` : `5,392,791`	0.008	0.992	0.000
rs74986892 lBF = `9.97307` Chr`17` : `12,326,683`	0.006	0.992	0.001
rs75238886 lBF = `22.8661` Chr`17` : `34,313,612`	0.007	0.993	0.000
rs7224438 lBF = `0.00992166` Chr`17` : `58,966,538`	0.007	0.993	0.000
rs12943679 lBF = `7.76211` Chr`17` : `64,027,553`	0.006	0.993	0.000
rs149464898 lBF = `0.0111314` Chr`17` : `78,947,333`	0.006	0.993	0.000
rs11655470 lBF = `1.92618` Chr`17` : `43,795,433`	0.007	0.993	0.000
rs75003023 lBF = `19.4031` Chr`17` : `75,537,040`	0.005	0.993	0.002
rs79124699 lBF = `7.72862` Chr`17` : `64,093,897`	0.006	0.994	0.000
rs34145262 lBF = `0.00758998` Chr`17` : `32,880,882`	0.005	0.994	0.000
rs142643109 lBF = `4.78759` Chr`17` : `60,387,921`	0.005	0.994	0.000
rs79169085 lBF = `7.81341` Chr`17` : `46,297,515`	0.005	0.995	0.000
rs1801689 lBF = `8.10652` Chr`17` : `64,210,580`	0.005	0.995	0.001
rs140564516 lBF = `-0.002253` Chr`17` : `37,029,972`	0.005	0.995	0.000
rs78726323 lBF = `10.6127` Chr`17` : `45,944,894`	0.004	0.996	0.000
rs12451840 lBF = `0.364503` Chr`17` : `71,807,713`	0.004	0.996	0.000
rs4791641 lBF = `0.0320253` Chr`17` : `8,161,149`	0.000	0.996	0.003
rs78414518 lBF = `7.79778` Chr`17` : `7,478,402`	0.003	0.996	0.000
rs80282661 lBF = `0.017531` Chr`17` : `13,252,073`	0.003	0.996	0.000
rs7218761 lBF = `0.0300051` Chr`17` : `11,693,587`	0.000	0.997	0.003
rs17711010 lBF = `20.9663` Chr`17` : `47,485,962`	0.003	0.997	0.000
rs143323161 lBF = `0.00353244` Chr`17` : `66,346,556`	0.003	0.997	0.000
rs57166100 lBF = `0.0869019` Chr`17` : `62,506,280`	0.000	0.997	0.003
rs7213234 lBF = `7.51298` Chr`17` : `36,980,163`	0.003	0.997	0.000
rs62072914 lBF = `10.3081` Chr`17` : `79,332,221`	0.003	0.997	0.000
rs8081319 lBF = `0.0106304` Chr`17` : `35,731,081`	0.002	0.997	0.000
rs80301618 lBF = `14.6641` Chr`17` : `70,922,471`	0.002	0.997	0.001
rs113937434 lBF = `20.1272` Chr`17` : `34,313,674`	0.002	0.997	0.000
rs117843447 lBF = `14.1413` Chr`17` : `20,921,845`	0.002	0.997	0.000
rs2270518 lBF = `0.00863214` Chr`17` : `7,758,522`	0.002	0.998	0.000
rs117677736 lBF = `7.64402` Chr`17` : `74,828,485`	0.002	0.998	0.000
rs2019872 lBF = `0.117668` Chr`17` : `2,010,318`	0.002	0.998	0.000
rs74361281 lBF = `11.9464` Chr`17` : `14,629,706`	0.002	0.998	0.000
rs8067912 lBF = `0.79653` Chr`17` : `56,313,904`	0.002	0.998	0.000
rs7226127 lBF = `11.5848` Chr`17` : `73,959,466`	0.002	0.998	0.000
rs8078051 lBF = `0.00157654` Chr`17` : `72,251,240`	0.001	0.998	0.000
rs72848438 lBF = `5.74751` Chr`17` : `77,991,750`	0.002	0.998	0.000
rs9303521 lBF = `1.38622` Chr`17` : `43,805,194`	0.002	0.998	0.000
rs79969149 lBF = `11.2075` Chr`17` : `26,270,925`	0.001	0.998	0.000
rs2597167 lBF = `0.158913` Chr`17` : `46,047,656`	0.000	0.998	0.001
rs12600691 lBF = `11.8554` Chr`17` : `75,535,526`	0.000	0.999	0.001
rs3744728 lBF = `0.0269455` Chr`17` : `6,093,951`	0.001	0.999	0.000
rs10852799 lBF = `10.56` Chr`17` : `11,522,764`	0.001	0.999	0.000
rs4790333 lBF = `-0.0403491` Chr`17` : `2,262,703`	0.000	0.999	0.001
rs73989024 lBF = `0.00079784` Chr`17` : `48,009,469`	0.001	0.999	0.000
rs117172443 lBF = `-0.0137883` Chr`17` : `71,713,116`	0.001	0.999	0.000
rs77542162 lBF = `16.8585` Chr`17` : `67,081,278`	0.001	0.999	0.000
rs76839023 lBF = `0.0477737` Chr`17` : `51,275,574`	0.001	0.999	0.000
rs8067165 lBF = `-0.0740107` Chr`17` : `8,031,936`	0.000	0.999	0.001
rs2291447 lBF = `-0.113286` Chr`17` : `43,212,963`	0.000	0.999	0.001
rs11867410 lBF = `3.32541` Chr`17` : `64,227,363`	0.001	0.999	0.000
rs781856 lBF = `0.0000959` Chr`17` : `3,950,224`	0.001	0.999	0.000
rs116965022 lBF = `11.9178` Chr`17` : `15,764,366`	0.001	0.999	0.000
rs11652466 lBF = `5.34235` Chr`17` : `56,061,709`	0.001	0.999	0.000
rs12938078 lBF = `0.273225` Chr`17` : `55,743,277`	0.000	0.999	0.001
rs55663797 lBF = `5.4195` Chr`17` : `43,544,379`	0.000	0.999	0.001
rs227724 lBF = `-0.0418164` Chr`17` : `54,778,817`	0.001	0.999	0.000
rs17320971 lBF = `5.32299` Chr`17` : `40,546,917`	0.001	0.999	0.000
rs8074751 lBF = `-0.0660515` Chr`17` : `63,642,542`	0.001	0.999	0.000
rs4795067 lBF = `0.315804` Chr`17` : `26,106,675`	0.001	0.999	0.000
rs3751972 lBF = `0.408036` Chr`17` : `26,206,414`	0.000	0.999	0.001
rs111926416 lBF = `0.0311968` Chr`17` : `71,943,575`	0.001	0.999	0.001
rs12602300 lBF = `0.00022381` Chr`17` : `68,661,635`	0.001	0.999	0.000
rs79480822 lBF = `0.049201` Chr`17` : `61,654,225`	0.000	0.999	0.001
rs16948200 lBF = `0.00011259` Chr`17` : `47,566,312`	0.001	0.999	0.000
rs140385970 lBF = `0.00003247` Chr`17` : `59,560,349`	0.000	0.999	0.001
rs2306658 lBF = `0.00000242` Chr`17` : `35,306,312`	0.000	0.999	0.001
rs1549519 lBF = `-0.0354373` Chr`17` : `53,757,787`	0.000	0.999	0.001
rs2233359 lBF = `23.4181` Chr`17` : `47,286,962`	0.001	0.999	0.000
rs8178393 lBF = `0.00007991` Chr`17` : `56,340,451`	0.001	0.999	0.000
rs16973424 lBF = `0.00003852` Chr`17` : `66,904,001`	0.001	0.999	0.000
rs144460277 lBF = `0` Chr`17` : `9,075,744`	0.001	0.999	0.001
rs141829479 lBF = `0` Chr`17` : `56,305,064`	0.001	0.999	0.001
rs146255527 lBF = `0` Chr`17` : `56,950,568`	0.001	0.999	0.001
rs142991058 lBF = `0` Chr`17` : `73,046,170`	0.001	0.999	0.001
rs9899375 lBF = `0` Chr`17` : `7,811,615`	0.001	0.999	0.001
rs111786708 lBF = `0` Chr`17` : `56,289,177`	0.001	0.999	0.001
rs61744862 lBF = `0` Chr`17` : `17,068,182`	0.001	0.999	0.001
rs188840013 lBF = `0` Chr`17` : `51,992,003`	0.001	0.999	0.001
rs186171056 lBF = `0` Chr`17` : `59,606,089`	0.001	0.999	0.001
rs116284889 lBF = `0` Chr`17` : `56,316,722`	0.001	0.999	0.001
rs144908958 lBF = `0` Chr`17` : `31,532,414`	0.001	0.999	0.001
rs9904045 lBF = `0` Chr`17` : `64,051,726`	0.001	0.999	0.001
rs78507937 lBF = `0` Chr`17` : `6,987,841`	0.001	0.999	0.001
rs188757965 lBF = `0` Chr`17` : `41,119,569`	0.001	0.999	0.001
rs116372990 lBF = `0` Chr`17` : `56,310,262`	0.001	0.999	0.001
rs138387343 lBF = `0` Chr`17` : `57,060,633`	0.001	0.999	0.001
rs75041531 lBF = `0` Chr`17` : `38,393,151`	0.001	0.999	0.001
rs146873050 lBF = `0` Chr`17` : `56,291,326`	0.001	0.999	0.001
rs113203253 lBF = `0` Chr`17` : `56,348,068`	0.001	0.999	0.001
rs140543894 lBF = `0` Chr`17` : `56,289,109`	0.001	0.999	0.001
rs150758818 lBF = `0` Chr`17` : `56,324,768`	0.001	0.999	0.001
rs7210100 lBF = `0` Chr`17` : `47,436,749`	0.001	0.999	0.001
rs12949468 lBF = `0` Chr`17` : `60,593,816`	0.001	0.999	0.001
rs78133126 lBF = `12.6154` Chr`17` : `16,345,753`	0.001	0.999	0.000
rs116885154 lBF = `-0.00001053` Chr`17` : `71,784,375`	0.001	0.999	0.000
rs12453524 lBF = `-0.00003894` Chr`17` : `66,575,117`	0.000	0.999	0.001
rs9635759 lBF = `-0.0807129` Chr`17` : `49,613,785`	0.000	0.999	0.001
rs34422007 lBF = `9.49411` Chr`17` : `40,248,644`	0.000	0.999	0.001
rs242557 lBF = `0.174769` Chr`17` : `44,019,712`	0.001	0.999	0.000
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rs199498 lBF = `4.33325` Chr`17` : `44,865,603`	0.000	1.000	0.000
rs11649743 lBF = `1.66786` Chr`17` : `36,074,979`	0.000	1.000	0.000
rs75213074 lBF = `1.24058` Chr`17` : `5,612,640`	0.000	1.000	0.000
rs143123127 lBF = `1.06585` Chr`17` : `38,007,190`	0.000	1.000	0.000
rs57968458 lBF = `0.235154` Chr`17` : `16,820,099`	0.000	1.000	0.000
rs228769 lBF = `0.109429` Chr`17` : `42,193,185`	0.000	1.000	0.000
rs79947075 lBF = `0.0194576` Chr`17` : `38,921,043`	0.000	1.000	0.000
rs75023836 lBF = `0.0141657` Chr`17` : `9,188,598`	0.000	1.000	0.000
rs191241826 lBF = `0.00303601` Chr`17` : `38,953,327`	0.000	1.000	0.000
rs11653989 lBF = `-0.00309586` Chr`17` : `75,004,213`	0.000	1.000	0.000
rs170149 lBF = `-0.0080491` Chr`17` : `6,595,930`	0.000	1.000	0.000
rs2006933 lBF = `-0.0142823` Chr`17` : `26,601,133`	0.000	1.000	0.000
rs7224610 lBF = `-0.0163906` Chr`17` : `53,364,788`	0.000	1.000	0.000
rs7209847 lBF = `-0.025317` Chr`17` : `12,804,550`	0.000	1.000	0.000
rs1877644 lBF = `-0.0397122` Chr`17` : `11,342,608`	0.000	1.000	0.000
rs6565681 lBF = `-0.0627288` Chr`17` : `78,348,494`	0.000	1.000	0.000
rs11654699 lBF = `-0.124536` Chr`17` : `30,903,310`	0.000	1.000	0.000
rs72883103 lBF = `10.4164` Chr`17` : `74,629,898`	0.000	1.000	0.000
Affx-13924026 lBF = `9.56415` Chr`17` : `43,723,189`	0.000	1.000	0.000
Affx-13924388 lBF = `9.2939` Chr`17` : `43,749,454`	0.000	1.000	0.000
Affx-13928154 lBF = `9.24312` Chr`17` : `43,978,320`	0.000	1.000	0.000
Affx-13923818 lBF = `9.15062` Chr`17` : `43,705,601`	0.000	1.000	0.000
Affx-13924269 lBF = `9.06314` Chr`17` : `43,740,856`	0.000	1.000	0.000
rs2942164 lBF = `8.97968` Chr`17` : `43,721,283`	0.000	1.000	0.000
rs62062784 lBF = `8.9602` Chr`17` : `44,024,552`	0.000	1.000	0.000
Affx-13923840 lBF = `8.92182` Chr`17` : `43,707,619`	0.000	1.000	0.000
Affx-13926563 lBF = `8.9188` Chr`17` : `43,879,308`	0.000	1.000	0.000
Affx-13930382 lBF = `8.91846` Chr`17` : `44,108,906`	0.000	1.000	0.000
Affx-13930186 lBF = `8.87319` Chr`17` : `44,098,861`	0.000	1.000	0.000
rs393152 lBF = `8.81827` Chr`17` : `43,719,143`	0.000	1.000	0.000
Affx-13927230 lBF = `8.8163` Chr`17` : `43,923,266`	0.000	1.000	0.000
Affx-13930010 lBF = `8.78176` Chr`17` : `44,088,926`	0.000	1.000	0.000
rs79446318 lBF = `8.77806` Chr`17` : `74,612,692`	0.000	1.000	0.000
Affx-13930107 lBF = `8.75309` Chr`17` : `44,093,319`	0.000	1.000	0.000
Affx-13929593 lBF = `8.74793` Chr`17` : `44,061,278`	0.000	1.000	0.000
Affx-13931220 lBF = `8.69044` Chr`17` : `44,155,707`	0.000	1.000	0.000
Affx-13926609 lBF = `8.66443` Chr`17` : `43,881,790`	0.000	1.000	0.000
Affx-13931266 lBF = `8.6395` Chr`17` : `44,159,102`	0.000	1.000	0.000
Affx-13928074 lBF = `8.54366` Chr`17` : `43,972,581`	0.000	1.000	0.000
Affx-13927245 lBF = `8.50198` Chr`17` : `43,924,073`	0.000	1.000	0.000
rs17689882 lBF = `8.49719` Chr`17` : `43,906,828`	0.000	1.000	0.000
Affx-13928230 lBF = `8.42537` Chr`17` : `43,982,159`	0.000	1.000	0.000
Affx-13930495 lBF = `8.40782` Chr`17` : `44,117,119`	0.000	1.000	0.000
rs10445337 lBF = `7.56478` Chr`17` : `44,067,400`	0.000	1.000	0.000
rs4795406 lBF = `6.87863` Chr`17` : `38,100,134`	0.000	1.000	0.000
rs4065986 lBF = `6.82996` Chr`17` : `38,102,641`	0.000	1.000	0.000
Affx-13922976 lBF = `5.36343` Chr`17` : `43,659,975`	0.000	1.000	0.000
rs199533 lBF = `4.38624` Chr`17` : `44,828,931`	0.000	1.000	0.000
rs2732703 lBF = `4.25554` Chr`17` : `44,353,222`	0.000	1.000	0.000
rs415430 lBF = `3.99129` Chr`17` : `44,859,144`	0.000	1.000	0.000
rs199515 lBF = `3.83286` Chr`17` : `44,856,641`	0.000	1.000	0.000
rs2941509 lBF = `3.15758` Chr`17` : `37,921,194`	0.000	1.000	0.000
rs7220711 lBF = `0.388513` Chr`17` : `41,789,965`	0.000	1.000	0.000
rs12946454 lBF = `0.0866074` Chr`17` : `43,208,121`	0.000	1.000	0.000
rs708382 lBF = `0.0582183` Chr`17` : `42,442,344`	0.000	1.000	0.000
rs6065 lBF = `0.0495717` Chr`17` : `4,836,381`	0.000	1.000	0.000
rs4792800 lBF = `0.0384245` Chr`17` : `16,845,167`	0.000	1.000	0.000
rs12602978 lBF = `0.0138007` Chr`17` : `25,567,080`	0.000	1.000	0.000
rs12602486 lBF = `0.00105779` Chr`17` : `42,241,929`	0.000	1.000	0.000
rs9912181 lBF = `-0.00769798` Chr`17` : `39,039,241`	0.000	1.000	0.000
rs117364231 lBF = `-0.0135547` Chr`17` : `32,306,423`	0.000	1.000	0.000
rs8073783 lBF = `-0.0163119` Chr`17` : `51,237,941`	0.000	1.000	0.000
rs34111070 lBF = `-0.0224477` Chr`17` : `61,794,198`	0.000	1.000	0.000
rs891684 lBF = `-0.0303389` Chr`17` : `70,713,539`	0.000	1.000	0.000
rs8077577 lBF = `-0.0325183` Chr`17` : `18,064,730`	0.000	1.000	0.000
rs17662217 lBF = `-0.0338281` Chr`17` : `32,862,190`	0.000	1.000	0.000
rs2378870 lBF = `-0.0356024` Chr`17` : `59,638,623`	0.000	1.000	0.000
rs9899891 lBF = `-0.0393476` Chr`17` : `14,629,746`	0.000	1.000	0.000
rs218676 lBF = `-0.0535661` Chr`17` : `6,607,018`	0.000	1.000	0.000
rs9895232 lBF = `-0.0671079` Chr`17` : `4,519,139`	0.000	1.000	0.000
rs3091316 lBF = `-0.0699381` Chr`17` : `32,593,974`	0.000	1.000	0.000
Affx-13924674 lBF = `9.55855` Chr`17` : `43,763,202`	0.000	1.000	0.000
rs8070723 lBF = `9.45423` Chr`17` : `44,081,064`	0.000	1.000	0.000
Affx-13923864 lBF = `9.42808` Chr`17` : `43,709,415`	0.000	1.000	0.000
rs145809511 lBF = `8.94119` Chr`17` : `44,633,014`	0.000	1.000	0.000
Affx-13926945 lBF = `8.61102` Chr`17` : `43,906,828`	0.000	1.000	0.000
rs12185233 lBF = `8.57671` Chr`17` : `43,923,654`	0.000	1.000	0.000
Affx-13930187 lBF = `8.42486` Chr`17` : `44,098,862`	0.000	1.000	0.000
rs62057061 lBF = `7.97487` Chr`17` : `43,856,639`	0.000	1.000	0.000
Affx-13925098 lBF = `7.82839` Chr`17` : `43,789,698`	0.000	1.000	0.000
Affx-13929317 lBF = `7.74855` Chr`17` : `44,043,378`	0.000	1.000	0.000
rs345166 lBF = `7.71775` Chr`17` : `58,209,589`	0.000	1.000	0.000
rs72831252 lBF = `7.09209` Chr`17` : `57,411,671`	0.000	1.000	0.000
rs6503525 lBF = `6.47206` Chr`17` : `38,095,174`	0.000	1.000	0.000
rs17608766 lBF = `5.23478` Chr`17` : `45,013,271`	0.000	1.000	0.000
rs199443 lBF = `4.99457` Chr`17` : `44,819,565`	0.000	1.000	0.000
rs11868441 lBF = `4.42506` Chr`17` : `59,239,221`	0.000	1.000	0.000
rs2732614 lBF = `3.83853` Chr`17` : `44,364,209`	0.000	1.000	0.000
rs1509123 lBF = `0.983378` Chr`17` : `6,683,878`	0.000	1.000	0.000
rs4796793 lBF = `0.27199` Chr`17` : `40,542,210`	0.000	1.000	0.000
rs2366017 lBF = `0.0131421` Chr`17` : `67,850,901`	0.000	1.000	0.000
rs11653176 lBF = `0.012337` Chr`17` : `59,447,369`	0.000	1.000	0.000
rs7226229 lBF = `0.0088149` Chr`17` : `20,924,077`	0.000	1.000	0.000
rs1642764 lBF = `0.0051968` Chr`17` : `7,557,834`	0.000	1.000	0.000
rs4561508 lBF = `0.00038807` Chr`17` : `16,848,750`	0.000	1.000	0.000
rs7209435 lBF = `-0.0111395` Chr`17` : `61,712,964`	0.000	1.000	0.000
rs11658329 lBF = `-0.01479` Chr`17` : `61,763,031`	0.000	1.000	0.000
rs12603284 lBF = `-0.0174122` Chr`17` : `2,771,512`	0.000	1.000	0.000

This table lists the top 500 variants ordered by p(effect).

The full results table can be downloaded from this page.

Variant clusters with highest protective effect

(posterior probability > 0.05)

Cluster X0300

log Bayes Factor = 109.684

contains 3 variants

0.7036

Cluster X0202

log Bayes Factor = 106.378

contains 5 variants

0.5693

Cluster X0289

log Bayes Factor = 60.4564

contains 1 variants

0.5588

Cluster X0317

log Bayes Factor = 95.4365

contains 2 variants

0.0975

Cluster X0333

log Bayes Factor = 38.671

contains 2 variants

0.0752

Cluster X0335

log Bayes Factor = 12.3689

contains 1 variants

0.0582

Variant clusters with highest risk effect

(posterior probability > 0.05)

Cluster X0119

log Bayes Factor = 114.358

contains 6 variants

0.7935

Cluster X0091

log Bayes Factor = 303.64

contains 12 variants

0.7904

Cluster X0325

log Bayes Factor = 58.453

contains 4 variants

0.7528

Cluster X0126

log Bayes Factor = 384.432

contains 15 variants

0.7139

Cluster X0141

log Bayes Factor = 742.063

contains 30 variants

0.7008

Cluster X0051

log Bayes Factor = 376.793

contains 14 variants

0.6947

Cluster X0166

log Bayes Factor = 230.746

contains 8 variants

0.6754

Cluster X0120

log Bayes Factor = 79.6695

contains 4 variants

0.6712

Cluster X0122

log Bayes Factor = 219.114

contains 9 variants

0.6635

Cluster X0192

log Bayes Factor = 402.511

contains 14 variants

0.6260

Cluster X0155

log Bayes Factor = 348.568

contains 12 variants

0.6172

Cluster X0146

log Bayes Factor = 686.343

contains 22 variants

0.5438

Cluster X0225

log Bayes Factor = 36.4143

contains 3 variants

0.5407

Cluster X0246

log Bayes Factor = 121.08

contains 5 variants

0.5346

Cluster X0257

log Bayes Factor = 281.184

contains 10 variants

0.5246

Cluster X0194

log Bayes Factor = 189.9

contains 5 variants

0.4909

Cluster X0068

log Bayes Factor = 127.774

contains 6 variants

0.4893

Cluster X0081

log Bayes Factor = 278.568

contains 10 variants

0.4621

Cluster X0288

log Bayes Factor = 92.1513

contains 2 variants

0.4612

Cluster X0212

log Bayes Factor = 300.777

contains 10 variants

0.4414

Cluster X0290

log Bayes Factor = 333.908

contains 13 variants

0.4351

Cluster X0012

log Bayes Factor = 112.432

contains 5 variants

0.4052

Cluster X0244

log Bayes Factor = 122.647

contains 5 variants

0.3927

Cluster X0004

log Bayes Factor = 32.8452

contains 2 variants

0.3828

Cluster X0047

log Bayes Factor = 378.621

contains 14 variants

0.3781

Cluster X0087

log Bayes Factor = 894.58

contains 26 variants

0.3773

Cluster X0173

log Bayes Factor = 654.164

contains 9 variants

0.3679

Cluster X0237

log Bayes Factor = 123.902

contains 6 variants

0.3622

Cluster X0161

log Bayes Factor = 609.219

contains 20 variants

0.3560

Cluster X0177

log Bayes Factor = 254.872

contains 10 variants

0.3370

Cluster X0059

log Bayes Factor = 922.497

contains 26 variants

0.3350

Cluster X0132

log Bayes Factor = 267.393

contains 11 variants

0.3312

Cluster X0164

log Bayes Factor = 463.793

contains 16 variants

0.3174

Cluster X0274

log Bayes Factor = 454.783

contains 18 variants

0.3161

Cluster X0320

log Bayes Factor = 110.964

contains 6 variants

0.3117

Cluster X0043

log Bayes Factor = 517.108

contains 20 variants

0.3105

Cluster X0044

log Bayes Factor = 1165.44

contains 34 variants

0.3005

Cluster X0098

log Bayes Factor = 246.226

contains 8 variants

0.2937

Cluster X0142

log Bayes Factor = 295.63

contains 12 variants

0.2887

Cluster X0203

log Bayes Factor = 363.522

contains 11 variants

0.2883

Cluster X0178

log Bayes Factor = 225.6

contains 9 variants

0.2869

Cluster X0172

log Bayes Factor = 80.2701

contains 3 variants

0.2863

Cluster X0029

log Bayes Factor = 709.102

contains 23 variants

0.2835

Cluster X0063

log Bayes Factor = 107.557

contains 5 variants

0.2694

Cluster X0210

log Bayes Factor = 426.159

contains 17 variants

0.2662

Cluster X0201

log Bayes Factor = 368.049

contains 13 variants

0.2597

Cluster X0094

log Bayes Factor = 562.956

contains 18 variants

0.2569

Cluster X0213

log Bayes Factor = 405.918

contains 15 variants

0.2385

Cluster X0231

log Bayes Factor = 82.3185

contains 5 variants

0.2300

Cluster X0150

log Bayes Factor = 861.091

contains 26 variants

0.2294

Cluster X0189

log Bayes Factor = 149.681

contains 5 variants

0.2258

Cluster X0042

log Bayes Factor = 307.243

contains 12 variants

0.2180

Cluster X0205

log Bayes Factor = 674.183

contains 18 variants

0.2148

Cluster X0199

log Bayes Factor = 350.038

contains 3 variants

0.2103

Cluster X0049

log Bayes Factor = 597.061

contains 18 variants

0.2066

Cluster X0248

log Bayes Factor = 254.854

contains 10 variants

0.2048

Cluster X0040

log Bayes Factor = 542.747

contains 16 variants

0.2002

Cluster X0106

log Bayes Factor = 980.916

contains 30 variants

0.1984

Cluster X0277

log Bayes Factor = 726.213

contains 23 variants

0.1877

Cluster X0145

log Bayes Factor = 274.587

contains 11 variants

0.1868

Cluster X0015

log Bayes Factor = 356.23

contains 15 variants

0.1842

Cluster X0072

log Bayes Factor = 1189.98

contains 37 variants

0.1760

Cluster X0170

log Bayes Factor = 264.081

contains 11 variants

0.1679

Cluster X0073

log Bayes Factor = 785.614

contains 25 variants

0.1556

Cluster X0256

log Bayes Factor = 211.588

contains 9 variants

0.1447

Cluster X0020

log Bayes Factor = 557.721

contains 18 variants

0.1372

Cluster X0224

log Bayes Factor = 278.692

contains 11 variants

0.1331

Cluster X0019

log Bayes Factor = 372.36

contains 16 variants

0.1308

Cluster X0100

log Bayes Factor = 730.252

contains 26 variants

0.1292

Cluster X0222

log Bayes Factor = 431.582

contains 17 variants

0.1288

Cluster X0185

log Bayes Factor = 84.7127

contains 6 variants

0.1247

Cluster X0001

log Bayes Factor = 167.541

contains 7 variants

0.1214

Cluster X0088

log Bayes Factor = 243.609

contains 9 variants

0.1171

Cluster X0045

log Bayes Factor = 446.264

contains 16 variants

0.1068

Cluster X0253

log Bayes Factor = 331.491

contains 13 variants

0.1042

Cluster X0270

log Bayes Factor = 41.2082

contains 4 variants

0.1040

Cluster X0229

log Bayes Factor = 347.165

contains 13 variants

0.1001

Cluster X0037

log Bayes Factor = 171.712

contains 6 variants

0.0903

Cluster X0021

log Bayes Factor = 338.631

contains 13 variants

0.0878

Cluster X0162

log Bayes Factor = 144.479

contains 9 variants

0.0869

Cluster X0074

log Bayes Factor = 353.38

contains 15 variants

0.0828

Cluster X0156

log Bayes Factor = 226.954

contains 9 variants

0.0813

Cluster X0079

log Bayes Factor = 413.803

contains 22 variants

0.0789

Cluster X0197

log Bayes Factor = 158.582

contains 8 variants

0.0784

Cluster X0102

log Bayes Factor = 99.5678

contains 5 variants

0.0722

Cluster X0058

log Bayes Factor = 183.199

contains 8 variants

0.0670

Cluster X0143

log Bayes Factor = 179.808

contains 8 variants

0.0647

Cluster X0165

log Bayes Factor = 303.727

contains 12 variants

0.0590

The TreeWAS Database is the result of research conducted at the Oxford Big Data Institute at the University of Oxford.

This research has been conducted using the UK Biobank Resource (application number 10625). This work uses data provided by patients and collected by the NHS as part of their care and support.

This research has been conducted with the support of the Wellcome Trust (100956/Z/13/Z and 090532/Z/09/Z and 100308/Z/12/Z), the Danish National Research Foundation, Takeda, the Medical Research Council (MC_UU_12010/3), the Oak Foundation (OCAY-15-520), the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC), the Wellcome Trust/Royal Society (204290/Z/16/Z) and the Li Ka Shing Foundation.

Diagnostic term associations

Hospitalization Episode Statistics (`HES`)

(posterior probability > 0.05)

(posterior probability > 0.05)

Diagnostic term associations

Hospitalization Episode Statistics (HES)

(posterior probability > 0.05)

(posterior probability > 0.05)

Hospitalization Episode Statistics (`HES`)