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Table 1 True and estimated QTL effects for the simulated data with main and epistatic effects.

From: Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping

Markersa Position Trueb EBLASSOc EBc
( i, j ) (cM, cM) β ( h 2 )   
(11,11) (50,50) 4.47(0.0975) 4.5801(0.1612) 4.8593(0.2075)
(26,26) (125,125) 3.16(0.0524) 3.0768(0.1576) 3.3221(0.2035)
(42,42) (205,205) -2.24(0.0250) -2.3169(0.1796) -2.2769(0.2262)
(48,48) (235,235) -1.58(0.0128) -1.3171(0.1720) -1.3634(0.2205)
(72,72) (355,355) 2.24(0.0247) - 1.6537(0.4277)
(73,73) (360,360) 3.16(0.0506) 5.1247(0.1555) 3.8771(0.4219)
(123,123) (610,610) 1.10(0.0062) - 1.5168(0.2432)
(127,127) (630,630) -1.10(0.0063) - -1.1834(0.2460)
(161,161) (800,800) 0.77(0.0030) - -
(181,181) (900,900) 1.73(0.0152) - -
(182,182) (905,905) 3.81(0.0725) 5.6744(0.2400) 5.5127(0.2894)
(185,185) (920,920) 2.25(0.0263) 1.7123(0.2327) 1.7070(0.2858)
(221,221) (1100,1100) -1.30(0.0088) -1.4276(0.1506) -1.0867(0.1956)d
(243,243) (1210,1210) -1.00(0.0051) -0.8603(0.1486) -
(262,262) (1305,1305) -2.24(0.0245) -2.2539(0.1826) -1.6078(0.2417)
(268,268) (1335,1335) 1.58(0.0120) 2.4264(0.2040) 2.1736(0.2509)
(270,270) (1345,1345) 1.00(0.0049) - -
(274,274) (1365,1365) -1.73(0.0147) -1.4114(0.1800) -1.4935(0.2254)
(361,361) (1800,1800) 0.71(0.0026) 0.7856(0.1457) 0.6520(0.1859)d
(461,461) (2300,2300) 0.89(0.0040) - -
(5,6) (20,25) 2.24(0.0230) 1.7839(0.1654) 1.5752(0.2886)
(6,39) (25,190) 2.25(0.0128) 1.9691(0.2168) -
(42,220) (205,1095) 4.47(0.0511) 4.3836(0.2198) 4.6414(0.3394)
(75,431) (370,2150) 0.77(0.0014) 1.1360(0.2124)d -
(81,200) (400,995) -2.24(0.0128) -2.4190(0.2460) -
(82,193) (405,960) 1.58(0.0063) 1.6345(0.2442) -
(87,164) (430,815) 3.16(0.0235) 2.9263(0.2254) 1.7059(0.3319)d
(87,322) (430,1605) 3.81(0.0342) 4.1019(0.2274) 3.7040(0.3632)
(92,395) (455,1970) 1.73(0.0081) 1.5714(0.2065)d -
(104,328) (515,1635) 1.00(0.0024) 0.8081(0.1979)d -
(118,278) (585,1385) -2.24(0.0120) -2.0796(0.2221) -2.2590(0.3460)
(150,269) (745,1340) 1.10(0.0028) 1.0740(0.2142) -
(237,313) (1180,1560) 0.71(0.0014) - -
(246,470) (1225,2345) -1.10(0.0032) -1.2381(0.2114)d -
(323,464) (1610,2315) 0.89(0.0020) - -
(328,404) (1635,2015) -1.73(0.0079) -2.3036(0.2123) -1.9428(0.3330)
(342,420) (1705,2095) -1.30(0.0041) -1.3886(0.2121)d -
(344,407) (1715,2030) -1.00(0.0025) - -
(373,400) (1860,1995) -1.58(0.0070) -1.4732(0.2028) -
(431,439) (2150,2190) 3.16(0.0278) 2.6700(0.2121) 2.2454(0.3366)d
μ   100 100.70 100.59
  10 11.76 0.25
CPU time    3.4 mins 249 hrs
  1. aWhen i = j, the QTL is a main effect; otherwise, it is an epistatic effect.
  2. bThe true value of a QTL effect is denoted by β and the proportion of variance contributed by the QTL is denoted by h2.
  3. cThe estimated QTL effect is denoted by and the standard error is denoted by . The EBLASSO algorithm used hyperparameters a = b = 0.1 and the EB algorithm used hyperparameters τ = -1 and ω = 0.001.
  4. dThe estimated QTL effect was obtained from a neighboring marker (≤ 20 cM away) rather than from the maker with the true effect.