reading data
[1]  6 95
               MR.0 OMO.2.1 PU2.7 REN.11 RRS.7 TS.5 VAN.0 AG.0 BR.0 BIL.5 COL.0
3950           10.3    10.3  10.3   10.3  10.3 10.3  10.3 10.3 10.3  11.3  10.3
37359          12.3    10.3   9.3    9.3   9.3 10.3   9.3  9.3  9.3  11.3  10.3
43058          11.5    11.5  11.5   11.5  11.5 11.5  11.5 11.5 11.5  14.5  12.5
43970            12      12    12     12    15   12    12   12   15    11    15
65291          13.5     5.5   7.5   13.5  12.5 15.5  10.5 10.5 10.5   5.5  14.5
81421           8.5    11.5  12.5   17.5  11.5 11.5  18.5 10.5 20.5   9.5  15.5
snp.1.3895353     C       T     C      C     C    C     C    C    C     T     C
snp.2.9581605     C       G     G      G     G    G     G    G    G     C     G
snp.5.19508285    G       T     T      T     T    T     T    T    T     G     T
snp.5.25386559    G       G     G      A     G    G     G    G    G     G     G
               BIL.7 BOR.1 BOR.4 SQ.1 ULL2.3  C24 CIBC.5  N13 CT.1 EST.1 BUR.0
3950            11.3  10.3  10.3 10.3   10.3 10.3   10.3 10.3 10.3  10.3  10.3
37359           11.3   9.3   9.3  9.3    9.3  8.3    9.3 10.3  9.3  12.3  10.3
43058           14.5  11.5  11.5 11.5   11.5 12.5   11.5 13.5 11.5  11.5  11.5
43970             11    12    12   12     12   12     12   12   12    12    12
65291            6.5  13.5  13.5 10.5   14.5 10.5   15.5 24.5 14.5  14.5  13.5
81421            9.5  10.5  17.5 18.5   12.5 10.5   11.5 10.5 12.5  21.5  13.5
snp.1.3895353      T     C     C    C      T    C      C    C    C     C     T
snp.2.9581605      C     G     G    G      G    G      G    C    G     G     G
snp.5.19508285     G     T     T    T      T    T      T    T    T     T     G
snp.5.25386559     G     G     G    A      G    G      G    G    G     G     G
               EDEN.2 EDI.0 EI.2 FAB.2 FAB.4 GOT.7 GOT.22 GU.0 GY.0 HR.5
3950             11.3  10.3 10.3  11.3  11.3  10.3   10.3 10.3 10.3 10.3
37359             7.3   9.3  9.3   7.3   7.3   9.3    9.3  9.3  9.3  9.3
43058            14.5  11.5 11.5  14.5  14.5  11.5   11.5 11.5 11.5 11.5
43970              18    17   14    18    18    20     20   15   12   12
65291             6.5  15.5  6.5   7.5   6.5   6.5    6.5 14.5 10.5 13.5
81421             9.5  <NA> 11.5   9.5   9.5  13.5   13.5 18.5 11.5 11.5
snp.1.3895353       T     T    C     T     T     C      C    C    C    C
snp.2.9581605       C     G    G     C     C     C      C    G    G    G
snp.5.19508285      G     T    T     T     T     T      T    T    T    T
snp.5.25386559      G     G    G     G     G     A      A    G    A    G
               CIBC.17 KAS.2 KNO.18 KZ.1 KZ.9 LER.1 LL.0 LOV.1 LOV.5 SHAHDARA
3950              10.3  10.3   10.3 10.3 10.3  10.3 10.3  11.3  11.3     10.3
37359             10.3   9.3   10.3 10.3  9.3   9.3  9.3   7.3   7.3      9.3
43058             11.5  10.5   11.5 12.5 10.5  11.5 11.5  12.5  12.5     10.5
43970               12    12     12   12   12    12   12    18    18       12
65291             15.5  13.5   10.5 12.5 14.5  15.5 15.5   8.5   5.5     13.5
81421             11.5  10.5   10.5 12.5 12.5  18.5 18.5   9.5   9.5     10.5
snp.1.3895353        C     C      C    C    C     C    C     T     T        C
snp.2.9581605        G     C      G    C    C     G    G     C     C        C
snp.5.19508285       T     G      T    T    T     T    T     G     G        G
snp.5.25386559       G     G      G    G    G     G    G     G     G        G
               LP2.2 GA.0 LZ.0 MT.0 MZ.0 NFA.8 NFA.10 NOK.3 OMO.2.3 OY.0 PNA.17
3950            10.3 10.3 10.3 10.3 10.3  10.3   10.3  10.3    10.3 10.3   10.3
37359            9.3  9.3  9.3  9.3  9.3   9.3    9.3   9.3    10.3 10.3   10.3
43058           11.5 11.5 11.5 12.5 11.5  11.5   11.5  11.5    11.5 11.5   11.5
43970             12   12   12   12   12    12     12    12      11   12     12
65291           13.5 12.5 10.5 14.5 14.5  13.5   10.5  14.5    15.5 14.5   10.5
81421           21.5 13.5 10.5 <NA> 18.5  18.5   13.5  15.5    11.5 23.5   10.5
snp.1.3895353      C    C    C    C    C     C      C     C       C    C      C
snp.2.9581605      G    G    G    G    G     G      G     G       G    G      G
snp.5.19508285     T    T    T    T    T     T      T     T       T    T      T
snp.5.25386559     G    G    G    G    G     G      G     G       G    A      G
               HR.10 PRO.0 PU2.23 RA.0 REN.1 ZDR.6 AN.1 LP2.6 EDEN.1 SE.0 KIN.0
3950            10.3  10.3   10.3 10.3  10.3  10.3 10.3  10.3   11.3 10.3  10.3
37359            9.3  10.3    9.3  9.3   9.3   9.3  9.3   9.3    7.3  9.3   9.3
43058           11.5  11.5   11.5 11.5  11.5  11.5 11.5  11.5   14.5 11.5  11.5
43970             12    12     12   12    12    12   12    12     18   12    19
65291           10.5  10.5   10.5 14.5  13.5  14.5 10.5  13.5    8.5 13.5  13.5
81421           18.5  17.5   22.5 10.5  17.5  10.5 15.5  18.5    9.5 11.5  18.5
snp.1.3895353      C     C      C    C     C     C    C     C      T    C     C
snp.2.9581605      G     C      G    G     G     G    G     G      C    G     G
snp.5.19508285     T     T      T    T     T     T    T     T      T    T     T
snp.5.25386559     G     G      G    G     G     G    G     G      G    G     G
               MRK.0 KNO.10 KONDARA ND.1 RMX.A02 RMX.A180 RRS.10 SORBO SPR1.2
3950            10.3   10.3    10.3 10.3    10.3     10.3   10.3  10.3   10.3
37359           10.3   10.3     9.3 10.3    10.3      9.3   10.3   9.3   10.3
43058           11.5   11.5    11.5 11.5    11.5     11.5   11.5  11.5   11.5
43970             11     12      12   12      12       12     12    12     15
65291           10.5   10.5    13.5 14.5    10.5     10.5   10.5  13.5    5.5
81421           10.5   15.5    10.5 15.5    10.5     10.5   15.5  10.5   10.5
snp.1.3895353      C      C       C    C       C        C      C     C      C
snp.2.9581605      G      G       C    G       G        G      G     C      G
snp.5.19508285     T      T       T    T       T        T      T     T      T
snp.5.25386559     G      G       G    G       G        G      G     G      G
               SPR1.6 SQ.8 PNA.10 TAMM.2 TAMM.27 TS.1 TSU.1 ULL2.5 UOD.1 UOD.7
3950             10.3 10.3   10.3   11.3    11.3 10.3  10.3   10.3  10.3  10.3
37359             9.3 10.3   10.3    7.3     7.3 10.3  10.3    9.3   9.3   9.3
43058            11.5 11.5   11.5   14.5    14.5 11.5  11.5   11.5  11.5  11.5
43970              12   12     12     18      18   12    12     11    12    15
65291            13.5 13.5   10.5   13.5    13.5 15.5  14.5   13.5  15.5   8.5
81421            10.5 11.5   15.5   16.5    16.5 11.5  17.5   10.5  10.5  11.5
snp.1.3895353       T    C      C      T       T    C     C      C     C     C
snp.2.9581605       C    G      G      C       C    G     G      C     G     G
snp.5.19508285      G    T      T      G       G    T     T      G     T     T
snp.5.25386559      A    G      G      G       G    G     A      A     G     G
               VAR.2.6 WA.1 WEI.0 VAR.2.1 WS.0 WS.2 WT.5 YO.0 ZDR.1 BAY.0 CVI.0
3950              11.3 10.3  10.3    10.3 10.3 10.3 10.3 10.3  10.3  10.3  11.3
37359             11.3 13.3   9.3    11.3  9.3 10.3 10.3 10.3   9.3   9.3  12.3
43058              8.5 11.5  11.5     8.5 11.5 11.5 11.5 11.5  11.5  11.5  12.5
43970               12   12    12      12   12   15   14   12    12    12    13
65291              5.5 14.5  14.5    13.5  8.5 14.5 10.5 10.5  14.5  14.5  10.5
81421             16.5 17.5  <NA>    17.5 10.5 11.5 15.5 17.5  10.5  21.5  10.5
snp.1.3895353        T    C     C       T    C    C    C    C     C     C     C
snp.2.9581605        C    G     G       C    G    G    G    G     G     G     G
snp.5.19508285       T    T     T       T    T    T    T    T     G     T     T
snp.5.25386559       G    G     G       G    G    G    G    G     G     G     G
               FEI.0
3950            10.3
37359            9.3
43058           11.5
43970             16
65291           10.5
81421           11.5
snp.1.3895353      C
snp.2.9581605      G
snp.5.19508285     T
snp.5.25386559     G
[1] "3950"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
3950 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -75.5995 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                        Value  Std Error     z       p
(Intercept)          3.774740 0.05888696 64.10 0.0e+00
as.factor(genos)11.3 1.373584 0.16561414  8.29 1.1e-16

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   2.148726e-03 4.617022e-06
Residual error= 0.536246 
[1] "37359"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
37359 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -63.87125 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                           Value  Std Error     z       p
(Intercept)           3.82066350 0.09480617 40.30 0.0e+00
as.factor(genos)11.3  1.48015172 0.25523969  5.80 6.7e-09
as.factor(genos)12.3 -0.19166564 0.28959942 -0.66 5.1e-01
as.factor(genos)13.3 -0.63568701 0.48335465 -1.32 1.9e-01
as.factor(genos)7.3   1.48014922 0.19252691  7.69 1.5e-14
as.factor(genos)8.3  -0.44763229 0.48335465 -0.93 3.5e-01
as.factor(genos)9.3  -0.07515544 0.11499755 -0.65 5.1e-01

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   1.898576e-03 3.604591e-06
Residual error= 0.473967 
[1] "43058"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
43058 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -71.42269 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                         Value Std Error    z       p
(Intercept)          3.4167798 0.5217943 6.55 5.8e-11
as.factor(genos)11.5 0.3966213 0.2749597 1.44 1.5e-01
as.factor(genos)12.5 0.4467343 0.3310665 1.35 1.8e-01
as.factor(genos)13.5 1.0311006 0.5706424 1.81 7.1e-02
as.factor(genos)14.5 1.8805695 0.3161114 5.95 2.7e-09
as.factor(genos)8.5  1.9277793 0.4474332 4.31 1.6e-05

Random effects
 Group Variable Std Dev   Variance 
 id    Vmat.1   0.5521121 0.3048278
Residual error= 0.3989526 
[1] "43970"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
43970 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -61.82747 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                        Value Std Error     z       p
(Intercept)         4.8329150 0.2074593 23.30 0.0e+00
as.factor(genos)12 -1.1075406 0.2150552 -5.15 2.6e-07
as.factor(genos)13 -1.3619843 0.5081555 -2.68 7.4e-03
as.factor(genos)14 -1.2782842 0.3881103 -3.29 9.9e-04
as.factor(genos)15 -1.0865657 0.2716206 -4.00 6.3e-05
as.factor(genos)16 -1.3016637 0.5081556 -2.56 1.0e-02
as.factor(genos)17  0.1148075 0.5081557  0.23 8.2e-01
as.factor(genos)18  0.4678989 0.2644527  1.77 7.7e-02
as.factor(genos)19 -1.3619829 0.5081555 -2.68 7.4e-03
as.factor(genos)20  0.2458716 0.3881102  0.63 5.3e-01

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   1.861048e-03 3.463501e-06
Residual error= 0.4638792 
[1] "65291"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
65291 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -65.89625 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                           Value  Std Error     z       p
(Intercept)           3.69358642 0.09884547 37.37 0.0e+00
as.factor(genos)12.5 -0.06196797 0.29649822 -0.21 8.3e-01
as.factor(genos)13.5  0.31002624 0.14291202  2.17 3.0e-02
as.factor(genos)14.5 -0.33294229 0.14868195 -2.24 2.5e-02
as.factor(genos)15.5  0.26960290 0.18925050  1.42 1.5e-01
as.factor(genos)24.5  0.75922519 0.49416374  1.54 1.2e-01
as.factor(genos)5.5   1.35517095 0.23802080  5.69 1.2e-08
as.factor(genos)6.5   1.27150514 0.22099675  5.75 8.7e-09
as.factor(genos)7.5   0.92962859 0.35634665  2.61 9.1e-03
as.factor(genos)8.5   1.10851021 0.26148698  4.24 2.2e-05

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   1.943135e-03 3.775774e-06
Residual error= 0.4841784 
[1] "81421"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 3.730535
[25] 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723 3.857949
[33] 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814 5.300814
[41] 3.521652 3.620073 3.560100 3.882423 3.308106 3.349904 3.470932 3.706262
[49] 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426 3.320230 3.651198
[57] 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932 3.633557 4.059437
[65] 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799 4.116460 5.300814
[73] 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411 5.300814 3.449988
[81] 4.006273 5.300814 3.184976 5.300814 4.600492 3.164069 3.378723 4.099194
[89] 3.344038 3.332205 3.470932 3.531251
81421 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -57.01004 
  n= 92 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                          Value  Std Error     z       p
(Intercept)           3.8979610 0.09377163 41.57 0.0e+00
as.factor(genos)11.5 -0.0508869 0.14923275 -0.34 7.3e-01
as.factor(genos)12.5 -0.3586125 0.22187678 -1.62 1.1e-01
as.factor(genos)13.5  0.2360096 0.22187676  1.06 2.9e-01
as.factor(genos)15.5 -0.2860291 0.18456675 -1.55 1.2e-01
as.factor(genos)16.5  1.4028552 0.27602197  5.08 3.7e-07
as.factor(genos)17.5 -0.1555770 0.18456676 -0.84 4.0e-01
as.factor(genos)18.5 -0.4390963 0.17032359 -2.58 9.9e-03
as.factor(genos)20.5  0.6350114 0.45932852  1.38 1.7e-01
as.factor(genos)21.5 -0.4945015 0.27602199 -1.79 7.3e-02
as.factor(genos)22.5 -0.1015383 0.45932842 -0.22 8.3e-01
as.factor(genos)23.5 -0.3911930 0.45932843 -0.85 3.9e-01
as.factor(genos)8.5   0.2600077 0.45932842  0.57 5.7e-01
as.factor(genos)9.5   1.4028513 0.18456696  7.60 2.9e-14

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   1.803330e-03 3.251999e-06
Residual error= 0.4496561 
[1] "snp.1.3895353"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
snp.1.3895353 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -64.54401 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                     Value  Std Error     z p
(Intercept)       3.706595 0.05407035 68.55 0
as.factor(genos)T 1.350403 0.12776590 10.57 0

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   1.914547e-03 3.665491e-06
Residual error= 0.4773354 
[1] "snp.2.9581605"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
snp.2.9581605 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -73.64175 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                      Value Std Error     z p
(Intercept)        4.732801 0.1050761 45.04 0
as.factor(genos)G -1.064754 0.1223935 -8.70 0

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   2.107360e-03 4.440967e-06
Residual error= 0.5253081 
[1] "snp.5.19508285"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
snp.5.19508285 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -90.57296 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                       Value Std Error     z       p
(Intercept)        4.7151587 0.1677974 28.10 0.0e+00
as.factor(genos)T -0.8994665 0.1817071 -4.95 7.4e-07

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   2.516654e-03 6.333549e-06
Residual error= 0.6277916 
[1] "snp.5.25386559"
[1] "X1_LD"
 [1] 4.157972 5.224886 3.945618 3.225522 3.746230 4.274928 3.361531 3.822280
 [9] 4.532973 5.300814 3.326233 5.300814 3.746559 3.664274 3.765711 3.404525
[17] 3.373028 3.583711 4.452812 3.308106 3.258097 3.481240 5.300814 4.947724
[25] 3.730535 5.300814 5.300814 5.093836 5.063740 3.332205 3.642328 3.378723
[33] 3.857949 3.800005 3.664095 3.588523 3.449988 3.308106 3.840198 5.300814
[41] 5.300814 3.521652 3.620073 3.560100 3.882423 3.301992 3.308106 3.349904
[49] 3.470932 3.706262 4.628574 3.506767 4.164208 3.245194 3.238678 3.796426
[57] 3.320230 3.651198 3.620258 3.289904 3.606780 5.300814 3.851034 3.470932
[65] 3.633557 4.059437 3.818628 3.238678 3.861315 3.465736 3.934600 3.922799
[73] 4.116460 5.300814 3.308106 3.961607 5.300814 5.300814 3.777538 3.574411
[81] 5.300814 3.449988 4.006273 5.300814 3.184976 3.171084 5.300814 4.600492
[89] 3.164069 3.378723 4.099194 3.344038 3.332205 3.470932 3.531251
snp.5.25386559 X1_LD 
Linear mixed-effects kinship model fit by maximum likelihood
  Data: data 
  Log-likelihood = -100.3907 
  n= 95 


Model:  as.numeric(phenos) ~ as.factor(genos) + (1 | id) 
Fixed coefficients
                       Value Std Error     z    p
(Intercept)        4.2748827 0.2320590 18.42 0.00
as.factor(genos)G -0.3608204 0.2438877 -1.48 0.14

Random effects
 Group Variable Std Dev      Variance    
 id    Vmat.1   2.789112e-03 7.779146e-06
Residual error= 0.6961416 
