[1] "###############################################################################################" [1] "STL_VegArea_d20" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.11 chr pos lod 16:32980055 1 237.24 1.414 2:20323512 2 91.80 1.909 3:19603970 3 48.24 1.098 4:63209955 4 199.97 0.756 9:44210662 5 7.91 4.733 7:8134312 6 366.67 1.741 9:13810436 7 61.71 1.375 12:38434736 8 342.19 2.277 9:51030547 9 269.70 1.355 11:11928910 10 233.80 0.897 6:36461890 11 407.04 1.382 4:70275026 12 423.27 2.019 14:13855237 13 315.82 1.354 7:22290526 14 75.31 3.020 7:38586105 15 198.18 2.749 16:37699437 16 307.77 3.393 [1] 4.108778 chr pos lod 9:44210662 5 7.91 4.73 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 557.1569 278.57843 4.733128 4.274081 1.848722e-05 1.97391e-05 Error 496 12478.5550 25.15838 Total 498 13035.7119 Estimated effects: ----------------- est SE t Intercept 21.1413 0.2248 94.039 5@7.9a -1.3456 0.3151 -4.270 5@7.9d -0.8532 0.4584 -1.861 chr pos lod 14:11966043 5 5.375721 3.732402 9:44210662 5 7.912251 4.733128 9:44355949 5 11.210550 3.722236 [1] "###############################################################################################" [1] "STL_VegArea_d113" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.31 chr pos lod 16:45728142 1 209.6 1.234 5:33801182 2 54.9 0.857 11:24938813 3 25.3 2.308 4:63209955 4 200.0 0.858 5:22878610 5 140.0 1.956 7:8134312 6 366.7 1.174 9:47898982 7 45.5 1.146 14:30570744 8 29.0 2.530 1:15297495 9 22.1 1.947 10:36025786 10 208.5 1.372 13:36278851 11 82.7 1.384 12:36922572 12 409.9 1.583 13:30406241 13 188.9 2.021 5:42519214 14 67.7 3.728 7:36845388 15 170.5 5.858 8:18258958 16 101.5 3.094 [1] 4.30709 chr pos lod 7:36845388 15 170 5.86 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 182293.2 91146.619 5.857869 5.262577 1.387174e-06 1.504349e-06 Error 496 3281660.7 6616.251 Total 498 3463953.9 Estimated effects: ----------------- est SE t Intercept 678.195 3.700 183.286 15@170.5a 25.602 4.966 5.156 15@170.5d -10.875 7.695 -1.413 chr pos lod 15:18977948 15 168.7683 4.804829 7:36845388 15 170.4877 5.857869 1:20324118 15 175.6033 3.280329 [1] "###############################################################################################" [1] "STL_VegArea_d282" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.18 chr pos lod 1:30800777 1 94.8 1.38 2:12973442 2 57.0 1.23 1:33854431 3 102.2 2.87 4:63610774 4 173.1 2.36 8:12354587 5 248.7 1.51 14:31852004 6 462.7 2.03 9:47898982 7 45.5 1.22 3:1466997 8 515.5 4.41 1:73932383 9 65.2 2.05 10:20404937 10 121.6 2.07 11:16284568 11 45.6 1.29 4:76452241 12 447.6 1.44 5:43079281 13 330.0 1.29 14:30766050 14 294.9 1.96 7:36845388 15 170.5 2.14 10:30378449 16 242.2 3.07 [1] 4.181049 chr pos lod 3:1466997 8 516 4.41 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 1943194 971596.77 4.408743 3.987078 3.901725e-05 4.147269e-05 Error 496 46794089 94342.92 Total 498 48737282 Estimated effects: ----------------- est SE t Intercept 1334.94 13.99 95.397 8@515.5a -44.88 18.76 -2.392 8@515.5d 115.67 30.22 3.828 chr pos lod 11:47139064 8 512.7560 3.256368 3:1466997 8 515.5047 4.408743 16:46152410 8 522.5231 2.591598 [1] "###############################################################################################" [1] "STL_VegArea_d362" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.18 chr pos lod 6:4032503 1 181.22 1.500 13:24783276 2 49.04 1.812 3:22133547 3 45.96 3.957 4:51324549 4 117.37 0.918 9:44044490 5 9.03 0.912 7:8134312 6 366.67 2.539 1:27623384 7 196.86 2.045 16:46152410 8 522.52 2.114 9:31372910 9 72.65 1.908 10:33417993 10 222.64 2.906 6:36461890 11 407.04 1.085 12:8171995 12 119.68 2.751 6:20417112 13 77.35 1.847 14:28966249 14 209.22 1.082 7:36845388 15 170.49 4.223 9:13212653 16 299.74 2.198 [1] 4.184417 chr pos lod 7:36845388 15 170 4.22 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 602184.4 301092.18 4.223167 3.822501 5.981819e-05 6.341954e-05 Error 496 15151490.7 30547.36 Total 498 15753675.0 Estimated effects: ----------------- est SE t Intercept 1047.591 7.951 131.761 15@170.5a 42.964 10.670 4.026 15@170.5d -36.393 16.535 -2.201 chr pos lod 10:6366304 15 119.8745 2.752210 7:36845388 15 170.4877 4.223167 15:24478085 15 298.8289 3.396163 [1] "###############################################################################################" [1] "STL_VegArea_d449" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.26 chr pos lod 1:48737122 1 147.3 1.530 2:3389216 2 11.1 1.546 11:50977604 3 40.0 2.876 5:40271085 4 290.0 2.212 12:18197705 5 53.2 1.719 6:24983786 6 327.9 1.292 2:37429117 7 184.7 1.530 16:40438164 8 491.3 1.247 14:7462787 9 222.6 1.463 10:36025786 10 208.5 2.574 11:65078950 11 453.2 2.001 4:77436489 12 492.3 1.671 13:32574275 13 196.6 2.768 14:28966249 14 209.2 0.803 15:18965373 15 169.0 3.808 8:18057773 16 103.5 1.552 [1] 4.256003 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_Y2_WinterSurvival" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 1:23754836 1 49.4 0.916 10:14118861 2 79.7 1.261 3:22133547 3 46.0 1.081 1:65620202 4 28.0 2.653 12:18197705 5 53.2 1.608 1:55323534 6 251.9 2.979 7:41151480 7 87.0 1.504 8:24860112 8 163.1 0.693 9:33324837 9 149.2 3.028 2:49427469 10 191.4 3.081 8:12475695 11 355.2 2.721 4:36679550 12 285.2 1.806 11:53202884 13 140.4 3.566 14:12100109 14 126.5 2.226 4:59794978 15 119.2 4.381 8:48840017 16 319.9 2.597 [1] 4.104548 chr pos lod 4:59794978 15 119 4.38 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 3.485249 1.742624 4.380971 3.962467 4.159379e-05 4.419438e-05 Error 496 84.471295 0.170305 Total 498 87.956544 Estimated effects: ----------------- est SE t Intercept 1.46402 0.01865 78.501 15@119.2a 0.09341 0.02524 3.701 15@119.2d 0.10176 0.03921 2.596 chr pos lod 7:49389992 15 111.5516 2.807420 4:59794978 15 119.2141 4.380971 1:95517659 15 126.6390 2.523170 [1] "###############################################################################################" [1] "STL_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.15 chr pos lod 1:23754836 1 49.38 2.018 4:71495784 2 160.96 3.998 3:6646979 3 16.56 0.750 8:29340250 4 0.00 1.154 13:10519969 5 62.80 1.665 4:74361903 6 38.26 1.840 6:36241387 7 41.21 2.322 12:20242993 8 106.07 1.071 9:61492433 9 352.86 1.500 10:31586103 10 173.52 2.007 11:427721 11 3.25 0.877 12:20352117 12 231.39 2.750 13:13894869 13 121.11 5.842 14:10411123 14 105.47 2.194 15:29552641 15 122.22 18.588 8:14960115 16 87.49 2.586 [1] 4.147024 chr pos lod 13:13894869 13 121 5.84 15:29552641 15 122 18.59 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 123733.7 30933.415 23.83911 19.74863 0 0 Error 494 502809.5 1017.833 Total 498 626543.2 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 13@133.3 2 24988 5.255 3.988 12.27 0 6.27e-06 *** 15@124.1 2 93982 18.568 15.000 46.17 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 90.1096 1.4482 62.224 13@133.3a -9.4363 1.9067 -4.949 13@133.3d 0.2795 2.9328 0.095 15@124.1a -19.0422 1.9866 -9.585 15@124.1d -1.4809 2.9154 -0.508 chr pos lod 1:13104150 13 68.5256 2.797359 13:16997221 13 133.3248 5.255329 12:16406897 13 136.8295 4.061215 chr pos lod 2:32435469 15 117.4328 17.18204 7:21469210 15 124.0928 18.56751 3:71868047 15 135.9358 17.20991 [1] "###############################################################################################" [1] "STL_Y2_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 1:45894938 1 127.37 2.085 2:20907352 2 113.32 1.379 3:3834184 3 0.00 1.140 8:54143666 4 259.17 1.100 13:18363562 5 80.12 2.668 6:2282979 6 105.06 1.650 3:72289104 7 105.27 2.859 12:43434052 8 86.40 1.903 14:7462787 9 222.56 2.273 10:21730628 10 130.82 2.834 3:10116162 11 15.84 2.470 10:20599449 12 362.86 0.727 11:31364224 13 27.88 2.550 14:1370803 14 10.55 1.572 10:623367 15 4.82 14.382 10:30071638 16 244.48 2.981 [1] 4.077922 chr pos lod 10:623367 15 4.82 14.4 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 21564.95 10782.4766 14.38245 12.43009 4.107825e-15 5.107026e-15 Error 496 151924.98 306.3004 Total 498 173489.93 Estimated effects: ----------------- est SE t Intercept 173.3473 0.7855 220.695 15@4.8a -9.1289 1.0901 -8.374 15@4.8d 0.5488 1.6021 0.343 chr pos lod 10:408250 15 0.000000 14.12285 10:623367 15 4.817643 14.38245 2:22527385 15 25.652745 12.56769 [1] "###############################################################################################" [1] "STL_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.16 chr pos lod 1:23754836 1 49.4 2.359 4:71495784 2 161.0 3.559 3:3834184 3 0.0 0.856 4:59346003 4 287.3 0.747 13:10519969 5 62.8 2.029 4:74361903 6 38.3 1.936 9:14052724 7 40.8 2.806 12:20242993 8 106.1 1.232 9:16750327 9 46.0 1.885 10:21730628 10 130.8 2.490 3:10116162 11 15.8 1.764 13:8187850 12 201.6 1.713 13:13894869 13 121.1 5.446 14:12063300 14 134.7 1.377 15:29552641 15 122.2 15.137 16:33348755 16 233.6 2.638 [1] 4.157338 chr pos lod 13:13894869 13 121 5.45 15:29552641 15 122 15.14 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 210270.3 52567.573 20.1799 16.99225 0 0 Error 494 1027178.0 2079.308 Total 498 1237448.3 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 13@133.3 2 48935 5.043 3.955 11.77 0 1.02e-05 *** 15@122.2 2 152699 15.018 12.340 36.72 0 1.33e-15 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 263.3299 2.0853 126.277 13@133.3a -13.1885 2.7243 -4.841 13@133.3d 0.7247 4.1919 0.173 15@122.2a -24.0476 2.8071 -8.567 15@122.2d -0.8260 4.3839 -0.188 chr pos lod 11:33891463 13 26.46368 3.576872 13:16997221 13 133.32477 5.042950 11:53206172 13 134.37729 3.981495 chr pos lod 15:7715396 15 103.7063 13.18623 15:29552641 15 122.2169 15.01765 3:71868047 15 135.9358 13.67903 [1] "###############################################################################################" [1] "STL_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.14 chr pos lod 3:22199021 1 226.9 1.84 1:15716147 2 166.6 3.34 3:6646979 3 16.6 1.51 4:37069916 4 71.2 1.39 13:39902459 5 313.6 2.02 1:57392789 6 115.2 1.54 6:36241387 7 41.2 3.41 9:2378979 8 287.4 1.12 1:25065517 9 46.8 1.73 10:21730628 10 130.8 1.52 11:30566263 11 234.6 2.61 12:20352117 12 231.4 2.67 5:11464934 13 135.1 7.69 14:12088618 14 132.2 1.89 1:95517659 15 126.6 16.30 9:52855213 16 50.0 1.85 [1] 4.141457 chr pos lod 5:11464934 13 135 7.69 1:95517659 15 127 16.30 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 121363.1 30340.764 23.62457 19.58958 0 0 Error 494 498165.6 1008.432 Total 498 619528.6 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 13@133.0 2 34820 7.321 5.62 17.26 0 5.66e-08 *** 15@126.6 2 79514 16.046 12.83 39.42 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 48.802 1.441 33.865 13@133.0a -10.917 1.899 -5.748 13@133.0d -4.113 2.920 -1.409 15@126.6a -17.156 1.985 -8.643 15@126.6d -5.558 2.895 -1.920 chr pos lod 5:603865 13 128.6728 4.316603 13:15073993 13 133.0467 7.320858 13:15924766 13 141.6882 6.024489 chr pos lod 7:21469210 15 124.0928 14.70412 1:95517659 15 126.6390 16.04623 11:12951583 15 127.6028 14.90498 [1] "###############################################################################################" [1] "STL_Y2_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 5:32730717 1 300.5 1.49 4:71495784 2 161.0 2.47 3:22133547 3 46.0 2.32 4:47743189 4 94.9 1.08 4:45122679 5 285.3 2.45 1:57392789 6 115.2 1.88 7:41151480 7 87.0 2.43 16:40589957 8 492.6 1.43 9:31372910 9 72.7 2.13 10:21730628 10 130.8 2.65 5:30314840 11 73.3 1.50 10:19215565 12 115.6 2.06 13:6295376 13 45.5 2.64 14:12063300 14 134.7 2.49 2:32435469 15 117.4 7.25 15:5242175 16 243.0 2.70 [1] 4.081816 chr pos lod 2:32435469 15 117 7.25 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 331150.8 165575.388 7.246543 6.468965 5.668355e-08 6.266477e-08 Error 496 4787918.0 9653.061 Total 498 5119068.8 Estimated effects: ----------------- est SE t Intercept 386.174 4.443 86.909 15@117.4a -34.943 5.968 -5.855 15@117.4d -1.973 9.250 -0.213 chr pos lod 15:10352582 15 98.72252 4.100174 2:32435469 15 117.43280 7.246543 7:34111585 15 159.62885 5.442250 [1] "###############################################################################################" [1] "STL_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.17 chr pos lod 6:4032503 1 181.2 1.56 11:5523798 2 166.6 3.23 3:22133547 3 46.0 1.84 12:39698340 4 195.2 1.12 4:45122679 5 285.3 2.65 1:57392789 6 115.2 2.16 4:12365209 7 107.2 2.96 16:40589957 8 492.6 1.23 9:31372910 9 72.7 2.27 10:21730628 10 130.8 2.75 5:30314840 11 73.3 1.21 4:27694339 12 198.6 2.20 13:6295376 13 45.5 4.02 14:12063300 14 134.7 2.72 1:95517659 15 126.6 10.78 10:30071638 16 244.5 2.40 [1] 4.166945 chr pos lod 1:95517659 15 127 10.8 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 804431.2 402215.62 10.78317 9.472423 1.647527e-11 1.91277e-11 Error 496 7687917.9 15499.83 Total 498 8492349.2 Estimated effects: ----------------- est SE t Intercept 434.243 5.581 77.806 15@126.6a -55.804 7.774 -7.179 15@126.6d -5.480 11.314 -0.484 chr pos lod 15:7615948 15 104.4736 9.470465 1:95517659 15 126.6390 10.783166 7:34111585 15 159.6288 8.634202 [1] "###############################################################################################" [1] "STL_PC1_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.11 chr pos lod 16:45728142 1 209.6 1.209 4:71495784 2 161.0 2.049 11:50977604 3 40.0 2.612 4:25291802 4 356.1 0.801 5:2896986 5 51.0 1.474 11:2492600 6 235.1 1.203 6:36241387 7 41.2 1.925 16:46169693 8 549.1 2.843 9:61492433 9 352.9 1.829 10:32866045 10 97.1 0.580 3:43489105 11 259.0 0.922 13:13673011 12 373.0 1.191 13:17084147 13 132.7 2.828 14:28966249 14 209.2 0.876 7:20684520 15 115.6 5.429 16:5917292 16 43.7 1.213 [1] 4.105875 chr pos lod 7:20684520 15 116 5.43 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 110.4789 55.239440 5.429295 4.887127 3.721388e-06 4.011862e-06 Error 496 2150.1309 4.334941 Total 498 2260.6097 Estimated effects: ----------------- est SE t Intercept -0.01912 0.09350 -0.205 15@115.6a -0.54872 0.12819 -4.281 15@115.6d -0.50595 0.19012 -2.661 chr pos lod 15:18595189 15 4.149284 4.279960 7:20684520 15 115.632481 5.429295 7:34111585 15 159.628849 3.828318 [1] "###############################################################################################" [1] "STL_PC2_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.15 chr pos lod 1:56073060 1 169.5 1.391 2:53060547 2 242.0 1.292 3:27857134 3 95.8 1.296 2:53733273 4 18.9 2.567 12:18197705 5 53.2 0.849 6:17818623 6 218.3 1.783 15:7550189 7 11.0 1.533 12:38674739 8 386.6 2.605 9:34203090 9 131.0 1.339 10:31586103 10 173.5 4.479 11:10633347 11 54.3 1.647 12:8186771 12 101.2 1.231 1:21127339 13 78.2 3.168 14:12095087 14 114.7 1.942 10:6366304 15 119.9 7.930 16:18006320 16 114.9 2.619 [1] 4.14596 chr pos lod 10:31586103 10 174 4.48 10:6366304 15 120 7.93 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 171.5797 42.894935 11.74418 10.27177 5.05388e-11 6.231959e-11 Error 494 1498.8219 3.034053 Total 498 1670.4017 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@11.8 2 53.7 3.814 3.215 8.85 0 0.000167 *** 15@119.9 2 126.3 8.767 7.561 20.81 0 2.1e-09 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.023637 0.078965 -0.299 10@11.8a -0.018387 0.108920 -0.169 10@11.8d -0.669755 0.159294 -4.205 15@119.9a -0.687361 0.106543 -6.452 15@119.9d -0.009415 0.167023 -0.056 chr pos lod 2:1779905 10 0.00000 2.946299 1:8976535 10 11.77515 3.814420 2:49427469 10 191.39096 2.524532 chr pos lod 2:32435469 15 117.4328 6.880592 10:6366304 15 119.8745 8.766561 1:95517659 15 126.6390 7.350123 [1] "###############################################################################################" [1] "STL_PC3_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.11 chr pos lod 3:60661969 1 389.24 2.603 2:4474391 2 13.75 2.096 3:27868251 3 91.70 0.641 12:40158974 4 205.28 1.284 9:44210662 5 7.91 4.630 5:37649947 6 263.51 1.502 16:23479272 7 111.33 1.701 16:46169693 8 549.11 2.039 5:20448874 9 85.17 2.179 10:36025786 10 208.49 1.247 11:56631671 11 422.63 1.739 3:76281745 12 496.24 1.615 2:33772566 13 159.62 1.927 7:22290526 14 75.31 2.444 6:22467589 15 189.73 1.755 16:22070671 16 199.14 1.743 [1] 4.110536 chr pos lod 9:44210662 5 7.91 4.63 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 21.91945 10.959724 4.630214 4.183119 2.343075e-05 2.498176e-05 Error 496 502.07823 1.012254 Total 498 523.99768 Estimated effects: ----------------- est SE t Intercept -0.007918 0.045095 -0.176 5@7.9a -0.275686 0.063210 -4.361 5@7.9d -0.138236 0.091952 -1.503 chr pos lod 9:43982011 5 0.000000 1.666367 9:44210662 5 7.912251 4.630214 9:44355949 5 11.210550 3.531407 [1] "###############################################################################################" [1] "STL_sqrt_VegArea_d20" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.13 chr pos lod 12:45616154 1 246.70 2.093 2:20323512 2 91.80 1.755 3:19603970 3 48.24 1.392 4:81751122 4 334.85 0.811 9:44210662 5 7.91 3.419 7:8134312 6 366.67 1.994 13:8869976 7 99.35 1.109 12:38434736 8 342.19 2.589 9:51030547 9 269.70 1.681 11:11928910 10 233.80 0.743 3:24740967 11 374.10 1.583 4:70275026 12 423.27 1.999 5:35760407 13 14.38 1.579 7:22290526 14 75.31 2.778 7:38586105 15 198.18 2.147 16:37699437 16 307.77 3.561 [1] 4.131064 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_sqrt_VegArea_d113" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.16 chr pos lod 16:45728142 1 209.6 1.316 5:33801182 2 54.9 0.986 11:24938813 3 25.3 2.704 12:23612410 4 45.5 0.881 5:22878610 5 140.0 1.646 7:8134312 6 366.7 1.217 9:47898982 7 45.5 0.999 14:30570744 8 29.0 2.281 1:73932383 9 65.2 2.164 10:36025786 10 208.5 1.331 11:12035462 11 44.2 1.501 12:15749892 12 195.9 1.384 5:35760407 13 14.4 2.035 5:42519214 14 67.7 3.880 7:36845388 15 170.5 5.289 8:18258958 16 101.5 2.807 [1] 4.15954 chr pos lod 7:36845388 15 170 5.29 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 64.79648 32.398238 5.288698 4.763634 5.144014e-06 5.534749e-06 Error 496 1295.43550 2.611765 Total 498 1360.23197 Estimated effects: ----------------- est SE t Intercept 25.49306 0.07352 346.766 15@170.5a 0.48542 0.09866 4.920 15@170.5d -0.18129 0.15289 -1.186 chr pos lod 15:18977948 15 168.7683 4.200271 7:36845388 15 170.4877 5.288698 1:20324118 15 175.6033 2.849941 [1] "###############################################################################################" [1] "STL_sqrt_VegArea_d282" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 1:30800777 1 94.8 1.58 2:12973442 2 57.0 1.19 1:33854431 3 102.2 2.68 4:63610774 4 173.1 1.56 8:12354587 5 248.7 1.84 14:31852004 6 462.7 1.58 9:47898982 7 45.5 1.22 3:1466997 8 515.5 3.94 1:73932383 9 65.2 2.47 10:20404937 10 121.6 2.21 11:16284568 11 45.6 1.20 4:76452241 12 447.6 1.16 5:43079281 13 330.0 1.39 14:30766050 14 294.9 2.06 7:36845388 15 170.5 1.89 10:30378449 16 242.2 3.12 [1] 4.074571 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_sqrt_VegArea_d362" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.02 chr pos lod 6:4032503 1 181.2 1.313 13:24783276 2 49.0 1.541 3:22133547 3 46.0 3.167 4:51324549 4 117.4 1.127 12:18197705 5 53.2 0.939 7:8134312 6 366.7 2.354 3:72289104 7 105.3 2.352 16:46152410 8 522.5 1.799 1:25065517 9 46.8 2.571 10:33417993 10 222.6 2.513 12:17123560 11 308.5 1.129 10:19215565 12 115.6 2.477 5:603865 13 128.7 1.766 14:28966249 14 209.2 1.206 7:36845388 15 170.5 4.109 9:13212653 16 299.7 2.374 [1] 4.017338 chr pos lod 7:36845388 15 170 4.11 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 260.1876 130.09380 4.108538 3.720702 7.788652e-05 8.244473e-05 Error 496 6732.7830 13.57416 Total 498 6992.9706 Estimated effects: ----------------- est SE t Intercept 31.8397 0.1676 189.974 15@170.5a 0.8887 0.2249 3.951 15@170.5d -0.7701 0.3485 -2.209 chr pos lod 15:17467828 15 154.7855 2.022206 7:36845388 15 170.4877 4.108538 15:24478085 15 298.8289 3.406488 [1] "###############################################################################################" [1] "STL_sqrt_VegArea_d449" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.12 chr pos lod 10:19314812 1 186.0 1.360 2:3389216 2 11.1 1.878 3:15492288 3 38.9 3.131 5:40271085 4 290.0 2.055 12:18197705 5 53.2 1.561 11:24601891 6 416.4 1.153 1:27623384 7 196.9 1.620 16:40589957 8 492.6 1.422 14:7462787 9 222.6 1.746 10:36025786 10 208.5 2.836 11:56311979 11 356.4 1.687 3:76281745 12 496.2 1.249 13:32574275 13 196.6 3.113 14:28966249 14 209.2 0.894 15:18965373 15 169.0 3.182 8:18057773 16 103.5 1.498 [1] 4.116623 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_sqrt_Y2_WinterSurvival" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.13 chr pos lod 1:8853032 1 16.85 0.983 2:17139912 2 231.66 1.169 3:22133547 3 45.96 1.219 4:33186034 4 9.27 1.923 5:2851543 5 46.11 1.722 12:50354342 6 280.03 2.294 4:63418601 7 38.97 1.317 16:40589957 8 492.59 0.858 9:33324837 9 149.17 2.059 2:49427469 10 191.39 3.540 8:12475695 11 355.19 2.495 4:36679550 12 285.16 1.352 11:53202884 13 140.42 3.683 14:12100109 14 126.55 1.813 4:59794978 15 119.21 3.535 8:48840017 16 319.88 2.632 [1] 4.131497 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_sqrt_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.18 chr pos lod 1:23754836 1 49.38 1.948 4:71495784 2 160.96 3.259 3:6646979 3 16.56 1.070 8:29340250 4 0.00 1.590 9:44326627 5 11.21 2.145 1:88293831 6 52.47 1.774 6:36241387 7 41.21 3.491 12:20254636 8 105.37 0.872 5:1557856 9 439.62 1.729 10:31586103 10 173.52 1.822 11:424487 11 6.62 0.731 12:20352117 12 231.39 3.340 13:13894869 13 121.11 5.603 5:2229593 14 99.72 2.140 7:21469210 15 124.09 15.354 8:14666516 16 90.45 2.647 [1] 4.183523 chr pos lod 13:13894869 13 121 5.6 7:21469210 15 124 15.4 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 623.2726 155.818154 20.22617 17.02769 0 0 Error 494 3037.0749 6.147925 Total 498 3660.3475 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 13@133.3 2 139.7 4.872 3.816 11.36 0 1.50e-05 *** 15@124.1 2 460.5 15.297 12.581 37.45 0 6.66e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 8.72553 0.11255 77.527 13@133.3a -0.70472 0.14819 -4.756 13@133.3d 0.04193 0.22794 0.184 15@124.1a -1.33571 0.15440 -8.651 15@124.1d -0.02182 0.22659 -0.096 chr pos lod 13:5004885 13 37.89504 3.768212 13:16997221 13 133.32477 4.872384 12:16406897 13 136.82955 3.721592 chr pos lod 4:59794978 15 119.2141 14.28376 7:21469210 15 124.0928 15.29698 3:71868047 15 135.9358 14.15529 [1] "###############################################################################################" [1] "STL_sqrt_Y2_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.98 chr pos lod 1:45894938 1 127.4 1.740 2:12973442 2 57.0 1.165 3:3834184 3 0.0 1.545 2:26262023 4 253.6 0.926 13:18363562 5 80.1 2.075 6:2282979 6 105.1 1.532 3:72289104 7 105.3 2.578 12:43434052 8 86.4 2.002 9:16750327 9 46.0 2.300 10:21730628 10 130.8 2.818 3:10116162 11 15.8 2.440 4:22246164 12 185.3 0.915 11:31364224 13 27.9 2.199 14:1370803 14 10.6 1.476 10:408250 15 0.0 9.072 10:30378449 16 242.2 3.475 [1] 3.981561 chr pos lod 10:408250 15 0 9.07 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 38.07788 19.0389388 9.071678 8.031189 8.478563e-10 9.613055e-10 Error 496 436.04714 0.8791273 Total 498 474.12502 Estimated effects: ----------------- est SE t Intercept 13.07354 0.04269 306.269 15@0.0a -0.37049 0.05666 -6.539 15@0.0d -0.09240 0.08956 -1.032 chr pos lod 10:408250 15 0.00000 9.071678 10:408250 15 0.00000 9.071678 2:22527385 15 25.65274 7.426020 [1] "###############################################################################################" [1] "STL_sqrt_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 1:23754836 1 49.4 2.432 4:71495784 2 161.0 3.366 3:3834184 3 0.0 0.959 8:29340250 4 0.0 0.738 13:18363562 5 80.1 2.159 1:57392789 6 115.2 2.047 4:12365209 7 107.2 3.389 12:20242993 8 106.1 1.267 9:16750327 9 46.0 1.942 10:21730628 10 130.8 2.555 3:10116162 11 15.8 1.735 13:8187850 12 201.6 1.934 13:13894869 13 121.1 5.163 14:12063300 14 134.7 1.347 15:29552641 15 122.2 12.882 8:123751 16 228.8 2.616 [1] 4.101698 chr pos lod 13:13894869 13 121 5.16 15:29552641 15 122 12.88 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 218.7943 54.698581 17.72322 15.08878 1.110223e-16 1.110223e-16 Error 494 1231.2519 2.492413 Total 498 1450.0462 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 13@133.3 2 56.26 4.842 3.88 11.29 0 1.61e-05 *** 15@122.2 2 153.32 12.716 10.57 30.76 0 2.58e-13 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 16.07779 0.07220 222.690 13@133.3a -0.44633 0.09432 -4.732 13@133.3d 0.04178 0.14513 0.288 15@122.2a -0.76200 0.09719 -7.841 15@122.2d -0.02534 0.15178 -0.167 chr pos lod 11:33891463 13 26.46368 3.610960 13:16997221 13 133.32477 4.841623 11:53206172 13 134.37729 3.823298 chr pos lod 15:7715396 15 103.7063 11.36637 15:29552641 15 122.2169 12.71645 3:71868047 15 135.9358 11.63225 [1] "###############################################################################################" [1] "STL_sqrt_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 3:22199021 1 226.88 2.054 1:15716147 2 166.64 3.857 3:6646979 3 16.56 1.677 4:37069916 4 71.18 0.966 9:44044490 5 9.03 1.994 2:48466162 6 113.67 1.636 6:36241387 7 41.21 5.030 5:39588264 8 208.92 1.076 7:13944336 9 35.75 1.656 10:21730628 10 130.82 1.980 11:30566263 11 234.59 2.092 12:20352117 12 231.39 3.274 13:15073993 13 133.05 6.639 14:12063300 14 134.67 2.131 1:95517659 15 126.64 16.359 14:27377764 16 91.41 1.798 [1] 4.068498 chr pos lod 6:36241387 7 41.2 5.03 13:15073993 13 133.0 6.64 1:95517659 15 126.6 16.36 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 887.1899 147.864980 28.91881 23.42395 0 0 Error 492 2900.3426 5.895005 Total 498 3787.5325 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 7@41.2 2 169.4 6.152 4.473 14.37 0 8.60e-07 *** 13@133.0 2 210.3 7.586 5.553 17.84 0 3.31e-08 *** 15@126.6 2 465.5 16.128 12.290 39.48 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 5.9028 0.1107 53.336 7@41.2a -0.7334 0.1560 -4.700 7@41.2d 0.6772 0.2323 2.915 13@133.0a -0.8549 0.1455 -5.876 13@133.0d -0.2890 0.2239 -1.291 15@126.6a -1.3357 0.1521 -8.784 15@126.6d -0.2717 0.2214 -1.227 chr pos lod 4:63418601 7 38.97318 4.792979 6:36241387 7 41.21329 6.151866 1:12636544 7 51.57834 4.944479 chr pos lod 5:603865 13 128.6728 4.614720 13:15073993 13 133.0467 7.586143 13:15933488 13 139.1735 6.127770 chr pos lod 15:29552641 15 122.2169 14.99880 1:95517659 15 126.6390 16.12793 3:71868047 15 135.9358 14.80448 [1] "###############################################################################################" [1] "STL_sqrt_Y2_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.15 chr pos lod 6:4032503 1 181.2 1.43 1:15716147 2 166.6 2.47 13:15697176 3 76.4 2.28 4:51324549 4 117.4 1.01 5:46314491 5 346.2 1.71 1:57392789 6 115.2 2.07 4:12365209 7 107.2 2.88 8:26545939 8 207.8 1.51 9:31372910 9 72.7 2.34 2:26454190 10 109.2 2.78 5:30314840 11 73.3 1.81 10:19215565 12 115.6 2.50 13:6295376 13 45.5 2.61 14:12063300 14 134.7 1.97 2:32435469 15 117.4 5.72 15:5242175 16 243.0 3.55 [1] 4.147669 chr pos lod 2:32435469 15 117 5.72 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 222.3174 111.158701 5.71768 5.139929 1.915665e-06 2.073454e-06 Error 496 4102.9835 8.272144 Total 498 4325.3009 Estimated effects: ----------------- est SE t Intercept 19.26358 0.13008 148.095 15@117.4a -0.90543 0.17471 -5.182 15@117.4d -0.04906 0.27079 -0.181 chr pos lod 15:10352582 15 98.72252 2.724280 2:32435469 15 117.43280 5.717680 7:34111585 15 159.62885 4.173814 [1] "###############################################################################################" [1] "STL_sqrt_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.24 chr pos lod 6:4032503 1 181.2 1.63 11:5523798 2 166.6 3.47 3:22133547 3 46.0 1.94 12:27963161 4 74.9 1.01 4:45122679 5 285.3 2.03 1:57392789 6 115.2 2.40 4:12365209 7 107.2 3.85 8:26545939 8 207.8 1.32 9:31372910 9 72.7 2.42 10:21730628 10 130.8 2.87 5:30314840 11 73.3 1.39 4:27694339 12 198.6 2.48 13:6295376 13 45.5 3.89 14:12063300 14 134.7 2.33 2:32435469 15 117.4 9.20 15:5242175 16 243.0 3.06 [1] 4.239147 chr pos lod 2:32435469 15 117 9.2 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 451.8224 225.9112 9.2008 8.140718 6.297967e-10 7.153454e-10 Error 496 5098.3319 10.2789 Total 498 5550.1543 Estimated effects: ----------------- est SE t Intercept 20.4373 0.1450 140.949 15@117.4a -1.2880 0.1948 -6.613 15@117.4d -0.1590 0.3019 -0.527 chr pos lod 15:7615948 15 104.4736 8.062147 2:32435469 15 117.4328 9.200800 7:34111585 15 159.6288 7.549145 [1] "###############################################################################################" [1] "STL_PC1_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 1:63866275 1 202.1 1.021 4:71495784 2 161.0 1.816 11:50977604 3 40.0 2.257 4:25291802 4 356.1 1.002 5:2896986 5 51.0 1.481 6:17223204 6 224.4 1.572 9:14224700 7 47.1 1.493 16:46169693 8 549.1 2.816 9:61492433 9 352.9 1.776 13:3891503 10 56.5 0.348 3:43489105 11 259.0 0.870 10:19215565 12 115.6 0.974 13:17084147 13 132.7 2.609 14:28966249 14 209.2 0.995 7:28140741 15 10.3 3.353 13:27802009 16 188.9 1.390 [1] 4.097536 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "STL_PC2_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.05 chr pos lod 12:4532386 1 172.6 1.48 2:20313326 2 94.2 1.34 3:27857134 3 95.8 1.26 2:53733273 4 18.9 2.22 5:2789173 5 57.9 1.15 6:17818623 6 218.3 1.75 7:41151480 7 87.0 2.06 2:3676022 8 402.9 2.93 2:39305456 9 122.2 1.12 10:31586103 10 173.5 4.87 3:24740967 11 374.1 1.82 4:27670003 12 203.9 1.63 13:16997221 13 133.3 3.70 14:9865881 14 93.4 2.00 15:29552641 15 122.2 8.47 16:18006320 16 114.9 2.85 [1] 4.047918 chr pos lod 10:31586103 10 174 4.87 15:29552641 15 122 8.47 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 499 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 178.3588 44.589706 12.54414 10.93176 8.536838e-12 1.068401e-11 Error 494 1453.2071 2.941715 Total 498 1631.5659 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@11.8 2 56.5 4.133 3.463 9.603 0 8.10e-05 *** 15@119.9 2 130.9 9.343 8.021 22.242 0 5.63e-10 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.03001 0.07775 -0.386 10@11.8a -0.04455 0.10725 -0.415 10@11.8d -0.68462 0.15685 -4.365 15@119.9a -0.69693 0.10491 -6.643 15@119.9d -0.09360 0.16446 -0.569 chr pos lod 2:7862321 10 5.803915 2.604130 1:8976535 10 11.775146 4.132888 2:49427469 10 191.390962 2.674989 chr pos lod 2:32435469 15 117.4328 7.643644 10:6366304 15 119.8745 9.342826 11:45152737 15 165.3840 7.670465 [1] "###############################################################################################" [1] "STL_PC3_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 3:60661969 1 389.24 2.212 13:3909654 2 40.79 1.708 3:27868251 3 91.70 0.760 12:40158974 4 205.28 0.989 9:44210662 5 7.91 3.665 4:69597562 6 262.92 1.411 16:23479272 7 111.33 1.549 8:55957541 8 470.13 2.263 5:20448874 9 85.17 1.151 2:23692711 10 88.75 0.985 14:482749 11 401.99 1.997 4:71262432 12 431.76 1.730 2:33772566 13 159.62 2.234 7:22290526 14 75.31 2.107 6:22467589 15 189.73 1.098 16:22070671 16 199.14 1.417 [1] 4.101877 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_VegArea_d9" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.07 chr pos lod 1:33306399 1 51.9 2.47 2:53721287 2 224.9 1.11 3:33906721 3 103.2 1.63 12:44548948 4 283.0 2.04 2:42590224 5 204.3 1.57 9:10577366 6 81.3 1.73 7:16201840 7 36.6 1.30 12:43434052 8 86.4 2.48 15:28717267 9 197.9 3.75 2:3195052 10 21.1 1.67 2:38822938 11 196.7 1.22 15:11847034 12 217.1 2.49 13:32574275 13 196.6 1.85 6:37248590 14 233.8 3.34 14:638860 15 194.8 3.57 5:40219562 16 253.0 3.37 [1] 4.072065 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_VegArea_d119" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.09 chr pos lod 1:83353562 1 307.2 2.804 10:31284492 2 180.6 1.682 3:23461389 3 82.1 1.242 4:56219512 4 153.6 1.830 5:24894211 5 200.5 1.281 4:38211289 6 98.3 2.638 15:7550189 7 11.0 0.681 16:9723253 8 50.4 2.169 9:8256294 9 13.1 1.464 10:7507542 10 66.3 1.706 11:21014028 11 94.8 2.407 13:25521369 12 327.5 2.268 13:30406241 13 188.9 1.063 11:23963636 14 68.6 4.690 7:36845388 15 170.5 1.495 9:1910231 16 220.7 1.527 [1] 4.092509 chr pos lod 11:23963636 14 68.6 4.69 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 1081972 540985.78 4.689725 4.227439 2.043032e-05 2.179785e-05 Error 497 24512048 49320.02 Total 499 25594020 Estimated effects: ----------------- est SE t Intercept 637.299 9.951 64.041 14@68.6a -64.065 13.860 -4.622 14@68.6d -19.688 20.100 -0.979 chr pos lod 14:1370803 14 10.55127 3.525628 11:23963636 14 68.56053 4.689725 12:12164012 14 98.65476 3.525456 [1] "###############################################################################################" [1] "GFL_VegArea_d200" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.09 chr pos lod 1:14958330 1 29.3 1.814 3:10236118 2 74.7 0.699 4:66745692 3 107.7 2.588 1:65731018 4 27.1 1.070 2:42590224 5 204.3 1.479 14:2854972 6 90.2 1.528 4:79719441 7 103.9 1.036 12:43462005 8 91.1 3.912 1:80176225 9 368.0 1.518 10:36025786 10 208.5 2.685 10:20730030 11 95.0 1.554 13:8187850 12 201.6 1.895 13:40111895 13 200.9 1.384 14:9865881 14 93.4 0.863 7:36845388 15 170.5 5.267 16:21820807 16 183.4 1.816 [1] 4.091143 chr pos lod 7:36845388 15 170 5.27 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 501260.2 250630.1 5.267387 4.735641 5.402723e-06 5.810547e-06 Error 497 10083584.9 20288.9 Total 499 10584845.1 Estimated effects: ----------------- est SE t Intercept 576.788 6.476 89.065 15@170.5a 42.896 8.684 4.940 15@170.5d -13.112 13.467 -0.974 chr pos lod 15:22908455 15 167.2427 3.931045 7:36845388 15 170.4877 5.267387 1:20324118 15 175.6033 4.148207 [1] "###############################################################################################" [1] "GFL_VegArea_d295" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.11 chr pos lod 1:75602312 1 278.73 2.011 4:72987262 2 4.79 2.107 3:11692564 3 26.09 5.282 8:29340250 4 0.00 1.085 4:45122679 5 285.29 2.497 8:42323421 6 203.61 0.530 7:46567025 7 167.39 1.896 12:20254636 8 105.37 3.091 9:16750327 9 46.05 1.362 2:30462916 10 137.70 1.419 3:24740967 11 374.10 2.018 12:2494257 12 63.56 1.470 5:44841923 13 341.39 0.915 14:12100109 14 126.55 1.094 15:3511683 15 26.79 6.840 16:16400433 16 125.01 2.331 [1] 4.110479 chr pos lod 3:11692564 3 26.1 5.28 15:3511683 15 26.8 6.84 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 9850.742 2462.686 13.32662 11.55088 1.493583e-12 1.895706e-12 Error 495 75430.569 152.385 Total 499 85281.311 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 3@26.1 2 4644 6.487 5.445 15.24 0 3.79e-07 *** 15@26.8 2 5801 8.045 6.803 19.03 0 1.09e-08 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 29.4813 0.5603 52.621 3@26.1a -3.8627 0.7593 -5.087 3@26.1d -1.8941 1.1366 -1.667 15@26.8a 4.6307 0.7656 6.048 15@26.8d 1.6327 1.1582 1.410 chr pos lod 3:3834184 3 0.00000 5.511503 3:11692564 3 26.08561 6.486754 3:15498840 3 41.77036 5.224938 chr pos lod 12:25588206 15 19.63532 5.555832 15:3511683 15 26.78866 8.044751 4:25497969 15 29.60658 6.298406 [1] "###############################################################################################" [1] "GFL_VegArea_d354" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 3.98 chr pos lod 1:75602312 1 278.73 2.734 4:72987262 2 4.79 3.103 3:3834184 3 0.00 4.071 4:72372162 4 169.61 1.374 13:40268467 5 296.69 1.433 14:23497690 6 305.22 0.526 1:27203774 7 203.17 2.202 15:4312433 8 143.94 1.912 9:16750327 9 46.05 1.275 2:30462916 10 137.70 2.109 3:24740967 11 374.10 1.672 4:39758917 12 297.89 2.084 5:797440 13 124.34 1.903 14:28966249 14 209.22 1.825 15:3511683 15 26.79 5.788 14:20320328 16 84.39 1.942 [1] 3.979891 chr pos lod 3:3834184 3 0.0 4.07 15:3511683 15 26.8 5.79 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 2076.009 519.00221 10.61375 9.313004 6.190911e-10 7.473094e-10 Error 495 20215.496 40.83939 Total 499 22291.505 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 3@25.3 2 918.8 4.826 4.122 11.25 0 1.67e-05 *** 15@26.8 2 1277.9 6.655 5.733 15.65 0 2.58e-07 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 19.2457 0.2891 66.571 3@25.3a -1.8034 0.3973 -4.539 3@25.3d -0.5672 0.5829 -0.973 15@26.8a 2.0908 0.3963 5.275 15@26.8d 1.2141 0.5996 2.025 chr pos lod 3:3834184 3 0.00000 4.239993 11:24938813 3 25.32617 4.826053 3:15498840 3 41.77036 3.464545 chr pos lod 12:25588206 15 19.63532 4.067160 15:3511683 15 26.78866 6.655089 4:25497969 15 29.60658 5.447012 [1] "###############################################################################################" [1] "GFL_VegArea_d452" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 1:39571620 1 121.72 2.452 4:72987262 2 4.79 1.162 3:3834184 3 0.00 3.991 2:42995823 4 293.64 2.223 13:40268467 5 296.69 1.959 6:34038926 6 381.56 0.799 1:27623384 7 196.86 2.814 15:4312433 8 143.94 2.222 9:56247502 9 306.74 1.483 11:13705185 10 146.16 1.346 6:38852275 11 252.02 1.917 4:39758917 12 297.89 1.304 9:33924138 13 104.31 0.671 14:28966249 14 209.22 1.091 15:3511683 15 26.79 4.166 14:20320328 16 84.39 2.453 [1] 4.096763 chr pos lod 15:3511683 15 26.8 4.17 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 13900.67 6950.3347 4.165724 3.764102 6.827724e-05 7.232198e-05 Error 497 355395.11 715.0807 Total 499 369295.78 Estimated effects: ----------------- est SE t Intercept 48.322 1.202 40.215 15@26.8a 6.738 1.655 4.070 15@26.8d 4.561 2.508 1.819 chr pos lod 12:25588206 15 19.63532 2.730296 15:3511683 15 26.78866 4.165724 5:43747231 15 36.25529 3.130427 [1] "###############################################################################################" [1] "GFL_Lifespan" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.26 chr pos lod 1:14958330 1 29.28 1.690 2:1044968 2 8.92 0.959 11:24938813 3 25.33 2.947 4:59533350 4 284.16 1.501 4:41932007 5 266.65 1.809 6:24138281 6 338.22 1.787 1:27203774 7 203.17 1.648 16:15693842 8 103.85 5.665 9:56525818 9 324.84 0.891 1:76724390 10 64.49 1.927 11:17787306 11 55.37 1.897 4:39758917 12 297.89 1.339 13:32574275 13 196.57 2.032 14:9865881 14 93.37 2.102 15:3511683 15 26.79 4.941 14:20320328 16 84.39 3.302 [1] 4.257631 chr pos lod 16:15693842 8 103.9 5.67 15:3511683 15 26.8 4.94 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 176.269 44.067262 11.08999 9.709921 2.15694e-10 2.626666e-10 Error 495 1639.081 3.311275 Total 499 1815.350 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@105.4 2 95.51 6.149 5.261 14.42 0 8.17e-07 *** 15@26.8 2 84.15 5.436 4.636 12.71 0 4.15e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 12.90071 0.08209 157.153 8@105.4a -0.54374 0.11420 -4.761 8@105.4d 0.37958 0.17167 2.211 15@26.8a 0.54954 0.11268 4.877 15@26.8d 0.24298 0.17083 1.422 chr pos lod 2:43577988 8 63.38158 3.861353 12:20254636 8 105.36713 6.149259 12:20137997 8 109.59131 4.313273 chr pos lod 12:25588206 15 19.63532 4.103033 15:3511683 15 26.78866 5.435878 15:4151672 15 41.04141 4.429462 [1] "###############################################################################################" [1] "GFL_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 1:89102036 1 287.2 3.21 2:34009301 2 151.6 2.12 3:15498840 3 41.8 2.84 4:69317182 4 159.9 2.68 13:11227907 5 70.9 1.75 1:55323534 6 251.9 4.36 1:27623384 7 196.9 4.54 6:4290974 8 101.6 3.94 14:7462787 9 222.6 2.00 6:22247148 10 124.4 5.40 3:57548673 11 344.3 1.91 4:12209794 12 126.7 1.07 10:11515826 13 82.0 1.76 14:30766050 14 294.9 1.24 15:1508578 15 16.2 19.80 10:36469603 16 69.0 1.86 [1] 4.077465 chr pos lod 1:55323534 6 251.9 4.36 1:27623384 7 196.9 4.54 6:22247148 10 124.4 5.40 15:1508578 15 16.2 19.80 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 165942.2 20742.7724 36.07786 28.27203 0 0 Error 491 421006.1 857.4462 Total 499 586948.3 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 6@190.0 2 14125 3.583 2.407 8.237 0 0.000303 *** 7@67.3 2 24218 6.072 4.126 14.122 0 1.09e-06 *** 10@154.7 2 25897 6.481 4.412 15.101 0 4.32e-07 *** 15@16.2 2 101846 23.523 17.352 59.389 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 104.400 1.353 77.168 6@190.0a -4.260 1.767 -2.410 6@190.0d -9.694 2.876 -3.371 7@67.3a -9.804 1.918 -5.112 7@67.3d 4.976 2.877 1.729 10@154.7a -10.093 1.875 -5.381 10@154.7d -2.508 2.704 -0.928 15@16.2a -19.115 1.805 -10.593 15@16.2d 6.300 2.733 2.305 chr pos lod 16:39243215 6 179.3731 1.684624 16:22354126 6 190.0351 3.582976 6:12652965 6 199.1632 2.395954 chr pos lod 9:13810436 7 61.70976 3.742924 8:22625723 7 67.29747 6.072481 7:40914429 7 79.00477 3.578500 chr pos lod 6:22247148 10 124.3752 5.266282 10:28013669 10 154.7321 6.481305 6:17008073 10 159.0318 4.937237 chr pos lod 10:460986 15 2.563844 21.22106 15:1508578 15 16.165883 23.52266 15:1661776 15 17.418410 22.22506 [1] "###############################################################################################" [1] "GFL_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.34 chr pos lod 12:45616154 1 246.70 3.635 2:34009301 2 151.57 2.148 3:15492288 3 38.87 3.881 13:4690147 4 280.28 2.932 13:11227907 5 70.86 2.431 1:55323534 6 251.88 4.398 1:21935569 7 70.56 4.073 6:4290974 8 101.55 4.972 9:14658828 9 23.57 1.986 6:22247148 10 124.38 8.072 3:57548673 11 344.30 2.063 4:39758917 12 297.89 0.964 10:11515826 13 81.96 1.440 14:30766050 14 294.89 0.799 10:623367 15 4.82 11.311 10:30071638 16 244.48 1.617 [1] 4.341052 chr pos lod 1:55323534 6 251.88 4.40 6:4290974 8 101.55 4.97 6:22247148 10 124.38 8.07 10:623367 15 4.82 11.31 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 206459.5 25807.44 29.14725 23.5441 0 0 Error 491 670446.0 1365.47 Total 499 876905.5 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 6@190.0 2 23483 3.738 2.678 8.599 0 0.000214 *** 8@105.4 2 37992 5.985 4.333 13.912 0 1.33e-06 *** 10@154.7 2 62372 9.658 7.113 22.839 0 3.28e-10 *** 15@16.2 2 79079 12.106 9.018 28.957 0 1.30e-12 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 121.857 1.711 71.238 6@190.0a -6.080 2.235 -2.721 6@190.0d -11.779 3.623 -3.251 8@105.4a -10.161 2.321 -4.377 8@105.4d 9.421 3.492 2.698 10@154.7a -15.354 2.361 -6.502 10@154.7d -5.538 3.408 -1.625 15@16.2a -16.345 2.268 -7.207 15@16.2d 7.944 3.447 2.305 chr pos lod 16:39243215 6 179.3731 2.155258 16:22354126 6 190.0351 3.737865 6:24138281 6 338.2193 2.694093 chr pos lod 5:32180397 8 71.00267 4.165243 12:20254636 8 105.36713 5.984504 12:20137997 8 109.59131 4.642625 chr pos lod 11:48857563 10 148.8921 8.485595 10:28013669 10 154.7321 9.658010 6:17008073 10 159.0318 8.432406 chr pos lod 10:460986 15 2.563844 11.03689 15:1508578 15 16.165883 12.10554 15:1635552 15 18.388893 10.73088 [1] "###############################################################################################" [1] "GFL_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.22 chr pos lod 12:45616154 1 246.70 4.355 2:2422437 2 7.79 2.722 11:24941941 3 29.43 3.480 13:4690147 4 280.28 2.215 13:10519969 5 62.80 1.208 6:18418652 6 275.97 4.492 1:27203774 7 203.17 2.075 8:23184561 8 197.46 2.554 9:6998378 9 22.88 3.383 6:22247148 10 124.38 8.471 11:46881163 11 315.46 0.715 9:33377779 12 482.97 1.762 3:42387029 13 246.08 1.743 14:12107518 14 118.50 1.139 10:623367 15 4.82 32.132 4:70101069 16 15.58 1.494 [1] 4.22359 chr pos lod 12:45616154 1 246.70 4.36 6:18418652 6 275.97 4.49 6:22247148 10 124.38 8.47 10:623367 15 4.82 32.13 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 2771099 346387.349 49.00261 36.32198 0 0 Error 491 4858162 9894.424 Total 499 7629261 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 1@246.7 2 178238 3.912 2.336 9.007 0.000 0.000144 *** 6@276.0 2 136316 3.005 1.787 6.889 0.001 0.001121 ** 10@173.5 2 401346 8.618 5.261 20.281 0.000 3.44e-09 *** 15@4.8 2 1882445 35.557 24.674 95.127 0.000 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 201.301 4.768 42.219 1@246.7a -20.516 5.823 -3.523 1@246.7d -24.122 9.977 -2.418 6@276.0a -22.554 6.387 -3.531 6@276.0d -12.561 9.163 -1.371 10@173.5a -36.786 6.052 -6.078 10@173.5d -19.137 10.080 -1.899 15@4.8a -82.855 6.214 -13.334 15@4.8d 29.656 9.176 3.232 chr pos lod 11:50754971 1 239.2163 1.129927 12:45616154 1 246.6996 3.912064 11:50748322 1 257.0858 2.363049 chr pos lod 16:22354126 6 190.0351 1.920914 6:18418652 6 275.9682 3.004533 10:24600411 6 285.1893 1.778603 chr pos lod 10:22722532 10 144.7864 7.279778 10:31586103 10 173.5174 8.618277 10:33914528 10 177.6154 7.491471 chr pos lod 10:460986 15 2.563844 32.81304 10:623367 15 4.817643 35.55676 7:28140741 15 10.321470 31.76411 [1] "###############################################################################################" [1] "GFL_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.08 chr pos lod 12:45616154 1 246.70 4.922 2:2422437 2 7.79 2.928 11:24941941 3 29.43 4.304 13:4690147 4 280.28 2.287 13:18363562 5 80.12 1.596 6:18418652 6 275.97 3.870 1:27203774 7 203.17 3.298 8:23184561 8 197.46 3.870 9:6998378 9 22.88 3.098 6:22247148 10 124.38 9.336 11:46881163 11 315.46 1.220 9:33377779 12 482.97 1.167 8:12441014 13 251.34 1.797 16:39123696 14 188.51 0.939 10:623367 15 4.82 23.865 4:70101069 16 15.58 0.934 [1] 4.080945 chr pos lod 12:45616154 1 246.70 4.92 11:24941941 3 29.43 4.30 6:22247148 10 124.38 9.34 10:623367 15 4.82 23.87 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 3410926 426365.72 42.80866 32.58363 0 0 Error 491 7057293 14373.31 Total 499 10468219 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 1@246.7 2 309415 4.659 2.956 10.76 0 2.66e-05 *** 3@36.4 2 253538 3.832 2.422 8.82 0 0.000173 *** 10@154.7 2 600350 8.864 5.735 20.88 0 1.97e-09 *** 15@4.8 2 2004564 27.145 19.149 69.73 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 225.956 5.740 39.362 1@246.7a -25.679 7.079 -3.628 1@246.7d -34.679 11.983 -2.894 3@36.4a -30.198 7.418 -4.071 3@36.4d -7.325 11.639 -0.629 10@154.7a -46.889 7.683 -6.103 10@154.7d -21.848 11.105 -1.968 15@4.8a -84.856 7.468 -11.362 15@4.8d 32.609 11.069 2.946 chr pos lod 11:50754971 1 239.2163 0.9274562 12:45616154 1 246.6996 4.6588201 11:50748322 1 257.0858 2.0795929 chr pos lod 3:3834184 3 0.00000 2.955623 11:42202822 3 36.43619 3.832143 3:7088917 3 50.97703 2.713685 chr pos lod 10:20404937 10 121.5803 7.281204 10:28013669 10 154.7321 8.864245 10:31402333 10 178.5914 7.713271 chr pos lod 10:460986 15 2.563844 24.61723 10:623367 15 4.817643 27.14476 15:1661776 15 17.418410 26.04353 [1] "###############################################################################################" [1] "GFL_SG_PC1_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.13 chr pos lod 12:45616154 1 246.70 4.67 2:1044968 2 8.92 2.17 11:24938813 3 25.33 5.12 4:63610774 4 173.13 3.11 13:11227907 5 70.86 1.41 1:55323534 6 251.88 2.15 1:27203774 7 203.17 4.20 15:890057 8 150.36 5.71 9:14658828 9 23.57 1.59 2:30462916 10 137.70 6.08 6:38852275 11 252.02 1.18 9:33490615 12 485.66 1.37 8:12441014 13 251.34 1.56 14:9865881 14 93.37 1.17 7:28140741 15 10.32 3.89 5:40219562 16 252.98 1.86 [1] 4.131431 chr pos lod 12:45616154 1 246.7 4.67 11:24938813 3 25.3 5.12 1:27203774 7 203.2 4.20 15:890057 8 150.4 5.71 2:30462916 10 137.7 6.08 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 + Q5 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 10 475.319 47.531905 23.58587 19.52582 0 0 Error 489 1958.991 4.006116 Total 499 2434.310 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 1@284.3 2 67.98 3.704 2.792 8.484 0 0.000239 *** 3@103.2 2 83.13 4.512 3.415 10.375 0 3.86e-05 *** 7@203.2 2 83.70 4.543 3.439 10.447 0 3.61e-05 *** 8@105.4 2 97.36 5.266 4.000 12.152 0 7.07e-06 *** 10@137.7 2 103.02 5.564 4.232 12.857 0 3.61e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.15832 0.09703 -1.632 1@284.3a -0.48535 0.12620 -3.846 1@284.3d -0.28517 0.18962 -1.504 3@103.2a -0.56998 0.12512 -4.555 3@103.2d 0.19415 0.20065 0.968 7@203.2a -0.56108 0.12400 -4.525 7@203.2d -0.07604 0.20881 -0.364 8@105.4a -0.52363 0.12702 -4.122 8@105.4d 0.47123 0.18953 2.486 10@137.7a -0.52738 0.12259 -4.302 10@137.7d -0.49341 0.19539 -2.525 chr pos lod 11:50754971 1 239.2163 1.283088 1:76319396 1 284.3472 3.703626 1:91589300 1 360.1109 2.233492 chr pos lod 3:11537194 3 21.95168 2.833853 3:33906721 3 103.15469 4.512239 4:66745692 3 107.69047 3.609893 chr pos lod 1:27237165 7 190.7728 2.667109 1:27203774 7 203.1709 4.542761 1:27203774 7 203.1709 4.542761 chr pos lod 13:4316476 8 81.72252 3.550468 12:20254636 8 105.36713 5.266251 8:24860112 8 163.10293 2.744553 chr pos lod 4:83986428 10 117.9867 3.859472 2:30462916 10 137.7042 5.564433 1:83070572 10 143.6937 3.995124 [1] "###############################################################################################" [1] "GFL_SG_PC2_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.21 chr pos lod 1:27074107 1 122.5 2.812 2:30106255 2 149.8 1.820 3:3834184 3 0.0 0.461 12:23600190 4 43.7 1.752 5:4210583 5 104.1 1.011 6:18418652 6 276.0 3.113 16:18873980 7 54.2 1.002 14:2453406 8 347.1 1.750 14:7462787 9 222.6 2.543 10:31402333 10 178.6 4.305 12:44168709 11 173.3 1.113 4:1339075 12 32.2 1.909 9:33924138 13 104.3 1.663 14:12100109 14 126.5 2.360 2:22527385 15 25.7 39.513 14:20320328 16 84.4 2.934 [1] 4.208911 chr pos lod 10:31402333 10 178.6 4.3 2:22527385 15 25.7 39.5 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 409.4086 102.352157 46.71845 34.96814 0 0 Error 495 761.3962 1.538174 Total 499 1170.8048 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@173.5 2 52.25 7.206 4.462 16.98 0 7.35e-08 *** 15@25.7 2 368.94 42.899 31.512 119.93 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 0.03550 0.05686 0.624 10@173.5a -0.43335 0.07548 -5.741 10@173.5d -0.11943 0.12517 -0.954 15@25.7a -1.19136 0.07740 -15.393 15@25.7d 0.12544 0.11343 1.106 chr pos lod 12:11602903 10 161.9982 5.054030 10:31586103 10 173.5174 7.205790 10:33870530 10 179.4247 6.108043 chr pos lod 12:25588206 15 19.63532 40.29555 2:22527385 15 25.65274 42.89920 4:25497969 15 29.60658 38.97673 [1] "###############################################################################################" [1] "GFL_SG_PC3_raw" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.23 chr pos lod 5:16546555 1 62.8 1.47 2:46118547 2 226.1 1.20 3:23461389 3 82.1 3.15 8:29340250 4 0.0 1.26 3:51805359 5 132.3 1.65 16:22354126 6 190.0 2.39 6:36241387 7 41.2 1.67 6:4295572 8 117.3 3.01 15:28717267 9 197.9 2.18 10:10085064 10 229.7 2.29 11:54887331 11 386.0 1.23 4:36679550 12 285.2 3.34 6:20417112 13 77.4 1.50 14:29762950 14 236.0 2.69 14:638860 15 194.8 3.67 16:45067371 16 358.8 1.01 [1] 4.234652 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d9" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.36 chr pos lod 1:33306399 1 51.88 2.70 2:53721287 2 224.88 1.38 3:33906721 3 103.15 1.84 12:44548948 4 283.01 2.26 2:42590224 5 204.26 1.31 9:10577366 6 81.30 1.98 15:7550189 7 10.99 1.47 15:890057 8 150.36 2.54 15:28717267 9 197.90 4.10 3:52945560 10 9.17 1.26 11:37896145 11 242.89 1.46 12:15749892 12 195.93 2.07 13:32574275 13 196.57 2.18 6:37248590 14 233.77 3.21 14:638860 15 194.82 4.18 5:40219562 16 252.98 3.28 [1] 4.357533 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d119" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.19 chr pos lod 1:83353562 1 307.2 2.516 10:31284492 2 180.6 1.954 1:33854431 3 102.2 1.541 4:32006035 4 23.4 1.826 5:24894211 5 200.5 1.634 6:2445294 6 101.8 3.193 15:7550189 7 11.0 0.625 15:890057 8 150.4 3.122 1:2402844 9 0.0 1.283 10:7507542 10 66.3 1.416 11:21014028 11 94.8 1.673 13:25521369 12 327.5 2.038 13:36450788 13 240.9 1.407 11:13221618 14 84.8 3.677 7:36845388 15 170.5 1.692 9:1910231 16 220.7 1.845 [1] 4.187882 There were no LOD peaks above the threshold. [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d200" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.14 chr pos lod 5:16546555 1 62.78 1.671 3:10236118 2 74.73 0.677 3:33906721 3 103.15 2.560 8:29340250 4 0.00 1.478 2:42590224 5 204.26 1.812 14:2854972 6 90.18 1.708 4:79719441 7 103.91 1.014 12:43462005 8 91.12 5.114 1:94024325 9 383.60 1.385 10:36025786 10 208.49 2.329 10:20730030 11 95.01 1.443 13:8187850 12 201.62 1.770 13:40111895 13 200.87 1.727 3:60017832 14 8.02 0.969 7:36845388 15 170.49 4.483 16:21820807 16 183.40 2.107 [1] 4.13789 chr pos lod 12:43462005 8 91.1 5.11 7:36845388 15 170.5 4.48 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 725.7648 181.44120 10.5463 9.25665 7.186925e-10 8.66459e-10 Error 495 7114.7044 14.37314 Total 499 7840.4692 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@91.1 2 408.6 6.063 5.211 14.21 0 9.95e-07 *** 15@170.5 2 365.1 5.433 4.656 12.70 0 4.18e-06 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 23.1128 0.1779 129.942 8@91.1a -0.6261 0.2243 -2.791 8@91.1d 1.7195 0.3803 4.521 15@170.5a 1.1400 0.2316 4.922 15@170.5d -0.5518 0.3613 -1.527 chr pos lod 12:43434052 8 86.40471 4.480948 12:43462005 8 91.11964 6.063002 12:20242993 8 106.07274 4.743492 chr pos lod 7:34111585 15 159.6288 4.259079 7:36845388 15 170.4877 5.432772 7:37527544 15 176.5903 4.309763 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d295" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.24 chr pos lod 1:71956399 1 119.5 1.813 2:26944744 2 140.7 1.322 3:11692564 3 26.1 4.900 4:81751122 4 334.8 0.943 4:45122679 5 285.3 2.999 8:49957656 6 134.1 0.490 7:46567025 7 167.4 2.080 12:20254636 8 105.4 4.514 9:16750327 9 46.0 1.537 2:30462916 10 137.7 1.712 6:38852275 11 252.0 1.524 4:39758917 12 297.9 2.144 5:44841923 13 341.4 0.842 14:12100109 14 126.5 1.011 15:3511683 15 26.8 7.823 13:18450638 16 125.3 2.558 [1] 4.243113 chr pos lod 3:11692564 3 26.1 4.90 12:20254636 8 105.4 4.51 15:3511683 15 26.8 7.82 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 127.0386 21.173094 19.2254 16.22809 1.110223e-16 1.110223e-16 Error 493 655.7925 1.330208 Total 499 782.8311 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 3@25.3 2 38.98 6.268 4.979 14.65 0 6.60e-07 *** 8@105.4 2 33.21 5.363 4.242 12.48 0 5.15e-06 *** 15@26.8 2 61.46 9.727 7.852 23.10 0 2.56e-10 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 3.882458 0.052408 74.081 3@25.3a -0.386448 0.071748 -5.386 3@25.3d -0.005242 0.105902 -0.049 8@105.4a -0.318030 0.072423 -4.391 8@105.4d 0.235004 0.109477 2.147 15@26.8a 0.481133 0.071548 6.725 15@26.8d 0.129955 0.108298 1.200 chr pos lod 3:11537194 3 21.95168 4.772289 11:24938813 3 25.32617 6.268443 3:22133547 3 45.96493 4.124066 chr pos lod 13:24987411 8 98.65308 4.102165 12:20254636 8 105.36713 5.363371 12:20137997 8 109.59131 3.034429 chr pos lod 12:25588206 15 19.63532 7.593103 15:3511683 15 26.78866 9.727145 4:25497969 15 29.60658 7.660000 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d354" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.22 chr pos lod 1:19584973 1 40.26 2.02 4:72987262 2 4.79 2.17 3:3834184 3 0.00 4.03 4:63610774 4 173.13 1.24 13:40268467 5 296.69 1.77 6:29900544 6 421.08 0.62 7:46567025 7 167.39 1.90 12:20254636 8 105.37 2.83 9:16750327 9 46.05 1.43 2:30462916 10 137.70 1.85 11:17787306 11 55.37 1.47 4:39758917 12 297.89 2.71 5:797440 13 124.34 1.27 14:28966249 14 209.22 1.35 15:3511683 15 26.79 7.14 14:20320328 16 84.39 2.28 [1] 4.218853 chr pos lod 15:3511683 15 26.8 7.14 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 24.82015 12.410077 7.143867 6.36795 7.180136e-08 7.924938e-08 Error 497 364.94663 0.734299 Total 499 389.76678 Estimated effects: ----------------- est SE t Intercept 2.26492 0.03851 58.821 15@26.8a 0.29026 0.05305 5.472 15@26.8d 0.17132 0.08038 2.131 chr pos lod 12:25588206 15 19.63532 5.287555 15:3511683 15 26.78866 7.143867 4:25497969 15 29.60658 5.546613 [1] "###############################################################################################" [1] "GFL_sqrt_VegArea_d452" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.14 chr pos lod 1:71956399 1 119.51 1.721 4:72987262 2 4.79 1.124 3:3834184 3 0.00 4.067 2:42995823 4 293.64 1.998 13:40268467 5 296.69 1.580 6:34038926 6 381.56 0.909 1:27203774 7 203.17 2.891 15:4312433 8 143.94 2.715 9:16750327 9 46.05 1.544 2:30462916 10 137.70 1.233 6:38852275 11 252.02 1.925 4:39758917 12 297.89 1.645 1:13104150 13 68.53 0.722 12:12174773 14 98.66 1.573 15:3511683 15 26.79 6.132 14:20320328 16 84.39 3.400 [1] 4.141139 chr pos lod 15:3511683 15 26.8 6.13 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 2 75.67317 37.836583 6.13236 5.491568 7.37292e-07 8.02479e-07 Error 497 1302.31516 2.620352 Total 499 1377.98833 Estimated effects: ----------------- est SE t Intercept 3.24255 0.07274 44.578 15@26.8a 0.50663 0.10021 5.056 15@26.8d 0.29997 0.15184 1.976 chr pos lod 12:25588206 15 19.63532 4.411675 15:3511683 15 26.78866 6.132360 4:36792913 15 32.31164 4.777819 [1] "###############################################################################################" [1] "GFL_sqrt_Lifespan" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.21 chr pos lod 1:14958330 1 29.28 1.474 2:1044968 2 8.92 0.807 3:33906721 3 103.15 3.080 4:59533350 4 284.16 1.626 4:41932007 5 266.65 1.784 6:24138281 6 338.22 1.805 1:27203774 7 203.17 1.581 12:20254636 8 105.37 5.885 16:18321243 9 189.44 0.925 1:76724390 10 64.49 1.800 5:30307058 11 60.12 1.829 16:27696464 12 45.84 1.411 13:32574275 13 196.57 2.056 14:9865881 14 93.37 2.093 15:3511683 15 26.79 4.448 14:20320328 16 84.39 3.017 [1] 4.208598 chr pos lod 12:20254636 8 105.4 5.89 15:3511683 15 26.8 4.45 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 3.586852 0.89671293 10.80508 9.472677 4.053943e-10 4.910869e-10 Error 495 34.278388 0.06924927 Total 499 37.865239 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@105.4 2 2.067 6.357 5.459 14.92 0 5.09e-07 *** 15@26.8 2 1.589 4.920 4.196 11.47 0 1.35e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 3.50655 0.01187 295.378 8@105.4a -0.07974 0.01651 -4.828 8@105.4d 0.05657 0.02483 2.279 15@26.8a 0.07567 0.01629 4.644 15@26.8d 0.03245 0.02470 1.314 chr pos lod 2:43577988 8 63.38158 4.115262 12:20254636 8 105.36713 6.357166 12:20137997 8 109.59131 4.464845 chr pos lod 12:25588206 15 19.63532 3.730607 15:3511683 15 26.78866 4.919837 8:21046214 15 83.97001 3.029322 [1] "###############################################################################################" [1] "GFL_sqrt_Y1_FloweringDur" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.1 chr pos lod 1:81847508 1 355.38 2.57 2:34009301 2 151.57 2.06 3:15498840 3 41.77 2.84 4:69317182 4 159.91 2.58 11:32095183 5 64.41 1.84 1:55323534 6 251.88 4.10 1:27623384 7 196.86 3.46 6:4290974 8 101.55 4.31 1:15297495 9 22.11 2.09 10:28013669 10 154.73 5.98 3:57548673 11 344.30 1.78 4:12209794 12 126.75 1.19 11:31364224 13 27.88 2.47 14:30766050 14 294.89 1.53 10:725661 15 8.43 24.79 10:36469603 16 69.00 1.62 [1] 4.097889 chr pos lod 6:4290974 8 101.55 4.31 10:28013669 10 154.73 5.98 10:725661 15 8.43 24.79 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 725.6797 120.946613 36.61905 28.62867 0 0 Error 493 1809.1210 3.669617 Total 499 2534.8007 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 8@105.4 2 78.46 4.610 3.095 10.69 0 2.85e-05 *** 10@154.7 2 144.06 8.319 5.683 19.63 0 6.28e-09 *** 15@16.2 2 503.98 26.682 19.882 68.67 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 9.54497 0.08653 110.308 8@105.4a -0.48508 0.12027 -4.033 8@105.4d 0.36659 0.18076 2.028 10@154.7a -0.76641 0.12232 -6.265 10@154.7d 0.02942 0.17662 0.167 15@16.2a -1.31935 0.11722 -11.256 15@16.2d 0.54289 0.17814 3.048 chr pos lod 8:12911127 8 54.99335 3.112664 12:20254636 8 105.36713 4.609720 16:19901643 8 199.51890 3.408332 chr pos lod 1:6509721 10 151.1119 7.270486 10:28013669 10 154.7321 8.318690 10:18114315 10 176.6428 6.697297 chr pos lod 10:1635691 15 6.132949 24.19654 15:1508578 15 16.165883 26.68162 15:1661776 15 17.418410 25.10757 [1] "###############################################################################################" [1] "GFL_sqrt_FloweringDuration" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.13 chr pos lod 12:45616154 1 246.70 2.62 2:34009301 2 151.57 2.05 3:15492288 3 38.87 3.63 13:4690147 4 280.28 2.41 11:32095183 5 64.41 2.20 1:55323534 6 251.88 4.26 7:46567025 7 167.39 3.31 6:4290974 8 101.55 5.00 1:15297495 9 22.11 2.20 10:28013669 10 154.73 8.06 3:57548673 11 344.30 2.11 13:25521369 12 327.48 1.02 11:31364224 13 27.88 2.18 14:30766050 14 294.89 1.25 10:725661 15 8.43 17.97 10:30071638 16 244.48 1.68 [1] 4.128005 chr pos lod 1:55323534 6 251.88 4.26 6:4290974 8 101.55 5.00 10:28013669 10 154.73 8.06 10:725661 15 8.43 17.97 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 863.7153 107.964415 36.0604 28.26049 0 0 Error 491 2192.5489 4.465476 Total 499 3056.2642 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 6@190.0 2 85.42 4.150 2.795 9.564 0 8.42e-05 *** 8@105.4 2 126.95 6.111 4.154 14.215 0 9.97e-07 *** 10@152.6 2 201.20 9.532 6.583 22.528 0 4.36e-10 *** 15@8.4 2 425.18 19.244 13.912 47.607 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 10.1290 0.0980 103.352 6@190.0a -0.3592 0.1276 -2.816 6@190.0d -0.7204 0.2075 -3.471 8@105.4a -0.6137 0.1328 -4.623 8@105.4d 0.4788 0.2000 2.394 10@152.6a -0.8984 0.1352 -6.645 10@152.6d -0.1669 0.1934 -0.863 15@8.4a -1.2037 0.1301 -9.250 15@8.4d 0.6103 0.2023 3.017 chr pos lod 16:39243215 6 179.3731 2.343477 16:22354126 6 190.0351 4.149611 16:29185371 6 254.3963 2.242097 chr pos lod 5:32180397 8 71.00267 5.003722 12:20254636 8 105.36713 6.111363 8:24860112 8 163.10293 3.711586 chr pos lod 11:48857563 10 148.8921 7.866810 2:32704639 10 152.6118 9.532310 10:18114315 10 176.6428 8.090792 chr pos lod 10:460986 15 2.563844 17.78873 10:725661 15 8.430199 19.24381 15:1661776 15 17.418410 17.81675 [1] "###############################################################################################" [1] "GFL_sqrt_Y1_FloralCount" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.18 chr pos lod 12:45616154 1 246.70 3.548 2:2422437 2 7.79 2.130 11:24941941 3 29.43 3.244 4:69317182 4 159.91 2.647 13:10519969 5 62.80 1.511 1:55323534 6 251.88 3.974 1:27623384 7 196.86 2.047 8:23184561 8 197.46 3.326 9:6998378 9 22.88 3.286 6:22247148 10 124.38 7.708 3:57548673 11 344.30 0.800 9:33490615 12 485.66 1.497 11:31364224 13 27.88 1.656 14:12107518 14 118.50 0.931 10:623367 15 4.82 41.724 4:70101069 16 15.58 1.415 [1] 4.179052 chr pos lod 6:22247148 10 124.38 7.71 10:623367 15 4.82 41.72 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 4970.318 1242.57955 50.94521 37.45118 0 0 Error 495 8301.143 16.76999 Total 499 13271.461 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@173.5 2 735.8 9.221 5.545 21.94 0 7.43e-10 *** 15@4.8 2 4340.4 45.666 32.705 129.41 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 12.4985 0.1878 66.560 10@173.5a -1.5768 0.2487 -6.341 10@173.5d -0.7805 0.4128 -1.891 15@4.8a -3.9230 0.2548 -15.394 15@4.8d 1.6136 0.3766 4.285 chr pos lod 10:20404937 10 121.5803 6.952913 10:31586103 10 173.5174 9.221381 10:18114315 10 176.6428 8.110162 chr pos lod 10:460986 15 2.563844 41.95456 10:623367 15 4.817643 45.66589 7:28140741 15 10.321470 41.62769 [1] "###############################################################################################" [1] "GFL_sqrt_TotalFloral" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.15 chr pos lod 12:45616154 1 246.70 4.105 2:2422437 2 7.79 2.438 11:24941941 3 29.43 3.922 4:67820241 4 155.46 2.677 13:18363562 5 80.12 1.821 1:55323534 6 251.88 4.168 1:27623384 7 196.86 2.624 8:23184561 8 197.46 4.260 9:6998378 9 22.88 3.325 6:22247148 10 124.38 8.803 3:57548673 11 344.30 1.058 9:33490615 12 485.66 1.134 8:12441014 13 251.34 1.679 3:60017832 14 8.02 0.828 10:623367 15 4.82 35.372 4:70101069 16 15.58 1.031 [1] 4.152089 chr pos lod 1:55323534 6 251.88 4.17 8:23184561 8 197.46 4.26 6:22247148 10 124.38 8.80 10:623367 15 4.82 35.37 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 + Q4 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 8 5789.272 723.65900 53.72425 39.03185 0 0 Error 491 9042.902 18.41732 Total 499 14832.174 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 6@195.5 2 333.2 3.929 2.246 9.046 0 0.000139 *** 8@150.4 2 422.6 4.959 2.849 11.472 0 1.35e-05 *** 10@173.5 2 894.9 10.246 6.033 24.295 0 8.69e-11 *** 15@4.8 2 4035.5 40.062 27.208 109.558 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 13.2188 0.2023 65.329 6@195.5a -0.8932 0.2556 -3.494 6@195.5d -1.1211 0.4199 -2.670 8@150.4a -1.2142 0.2732 -4.444 8@150.4d 0.7058 0.3981 1.773 10@173.5a -1.7269 0.2608 -6.622 10@173.5d -0.9362 0.4339 -2.158 15@4.8a -3.7508 0.2678 -14.006 15@4.8d 1.7446 0.3995 4.367 chr pos lod 1:74225488 6 186.5344 2.878010 8:42318675 6 195.4867 3.928639 6:19481412 6 284.4438 2.482954 chr pos lod 5:32180397 8 71.00267 3.511352 15:890057 8 150.36420 4.958696 8:32357951 8 235.44874 2.962199 chr pos lod 2:32704639 10 152.6118 9.167357 10:31586103 10 173.5174 10.245598 10:33914528 10 177.6154 9.025872 chr pos lod 10:460986 15 2.563844 36.27429 10:623367 15 4.817643 40.06203 7:28140741 15 10.321470 35.89690 [1] "###############################################################################################" [1] "GFL_SG_PC1_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.12 chr pos lod 12:45616154 1 246.70 3.42 2:1044968 2 8.92 1.50 11:24938813 3 25.33 4.47 4:63610774 4 173.13 3.02 4:45122679 5 285.29 1.32 6:26303925 6 335.81 1.90 1:27203774 7 203.17 3.09 15:890057 8 150.36 6.82 9:14658828 9 23.57 1.50 2:30462916 10 137.70 5.07 6:38852275 11 252.02 1.22 9:33490615 12 485.66 1.38 13:32574275 13 196.57 1.88 14:9865881 14 93.37 1.49 7:28140741 15 10.32 4.03 5:40219562 16 252.98 2.27 [1] 4.115621 chr pos lod 11:24938813 3 25.3 4.47 15:890057 8 150.4 6.82 2:30462916 10 137.7 5.07 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 + Q3 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 6 360.7279 60.121320 15.72962 13.48697 1.2923e-13 1.822986e-13 Error 493 2313.9125 4.693534 Total 499 2674.6404 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 3@103.2 2 97.03 4.460 3.628 10.34 0 4.01e-05 *** 8@150.4 2 147.24 6.698 5.505 15.69 0 2.49e-07 *** 10@137.7 2 88.90 4.093 3.324 9.47 0 9.21e-05 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept -0.1289 0.1027 -1.256 3@103.2a -0.6160 0.1355 -4.547 3@103.2d 0.2111 0.2153 0.981 8@150.4a -0.7301 0.1384 -5.276 8@150.4d 0.3700 0.2012 1.839 10@137.7a -0.5015 0.1328 -3.777 10@137.7d -0.4252 0.2083 -2.041 chr pos lod 3:11537194 3 21.95168 3.111830 3:33906721 3 103.15469 4.459760 4:66745692 3 107.69047 3.272345 chr pos lod 13:4316476 8 81.72252 5.149623 15:890057 8 150.36420 6.698008 16:19901643 8 199.51890 5.597593 chr pos lod 10:2779124 10 108.6637 2.954419 2:30462916 10 137.7042 4.093104 1:83070572 10 143.6937 2.737777 [1] "###############################################################################################" [1] "GFL_SG_PC2_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.29 chr pos lod 1:27074107 1 122.5 2.210 2:30106255 2 149.8 1.966 1:33854431 3 102.2 0.251 1:65620202 4 28.0 1.759 13:18363562 5 80.1 1.149 6:18418652 6 276.0 2.418 7:23872121 7 0.0 0.794 14:2453406 8 347.1 1.586 14:7462787 9 222.6 2.515 10:31402333 10 178.6 4.409 12:44168709 11 173.3 1.270 4:1339075 12 32.2 2.024 11:31364224 13 27.9 1.490 14:12100109 14 126.5 2.522 2:22467490 15 23.9 50.504 14:20320328 16 84.4 2.480 [1] 4.292978 chr pos lod 10:31402333 10 178.6 4.41 2:22467490 15 23.9 50.50 fitqtl summary Method: Haley-Knott regression Model: normal phenotype Number of observations : 500 Full model result ---------------------------------- Model formula: y ~ Q1 + Q2 df SS MS LOD %var Pvalue(Chi2) Pvalue(F) Model 4 526.7666 131.69165 58.49818 41.65451 0 0 Error 495 737.8421 1.49059 Total 499 1264.6087 Drop one QTL at a time ANOVA table: ---------------------------------- df Type III SS LOD %var F value Pvalue(Chi2) Pvalue(F) 10@173.5 2 56.38 7.994 4.458 18.91 0 1.22e-08 *** 15@23.9 2 483.22 54.693 38.211 162.09 0 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Estimated effects: ----------------- est SE t Intercept 0.05020 0.05617 0.894 10@173.5a -0.45679 0.07430 -6.148 10@173.5d -0.01239 0.12336 -0.100 15@23.9a -1.33092 0.07486 -17.779 15@23.9d 0.27650 0.11583 2.387 chr pos lod 12:11602903 10 161.9982 6.424775 10:31586103 10 173.5174 7.993990 10:33870530 10 179.4247 6.672059 chr pos lod 15:4745808 15 13.47078 49.87310 2:22467490 15 23.85890 54.69329 2:22558868 15 25.89613 53.65259 [1] "###############################################################################################" [1] "GFL_SG_PC3_trans" Doing permutation in batch mode ... LOD thresholds (1000 permutations) lod 5% 4.23 chr pos lod 5:16546555 1 62.8 1.25 2:46118547 2 226.1 1.53 3:3834184 3 0.0 2.54 4:32006035 4 23.4 1.63 3:51805359 5 132.3 1.81 16:22354126 6 190.0 2.87 6:36241387 7 41.2 1.91 6:4295572 8 117.3 2.58 1:61323471 9 181.7 2.34 6:17008073 10 159.0 2.53 11:6575573 11 25.7 0.92 4:36679550 12 285.2 3.26 6:20417112 13 77.4 1.71 14:29762950 14 236.0 2.78 14:638860 15 194.8 3.57 16:45067371 16 358.8 1.00 [1] 4.234084 There were no LOD peaks above the threshold.