Project measure / variable:   Wiltshire4   monocytes_Sel_E


  STRAIN COMPARISON PLOT
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Wiltshire4 - monocytes, percent viability dose: 100 µM



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested34 strains
Mean of the strain means95.9   %
Median of the strain means96.3   %
SD of the strain means± 15.0
Coefficient of variation (CV)0.157
Min–max range of strain means66.0   –   145   %
Mean sample size per strain4.0   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 33 28794.6793 872.566 5.2834 < 0.0001
Residuals 99 16350.2269 165.1538


Q-Q normality assessment based on residuals

  


  STRAIN MEANS (UNADJUSTED)
  
Select table page:
Strain Sex Mean SD N mice SEM CV Min, Max Z score
129S1/SvImJ m 72.8 10.5   4 5.23 0.144 65.8, 88.3 -1.54
129X1/SvJ m 88.3 5.19   4 2.59 0.0588 84.6, 95.9 -0.51
A/J m 98.8 9.2   4 4.6 0.0931 92.6, 112.0 0.19
AKR/J m 102.0 2.46   4 1.23 0.0241 99.4, 105.0 0.41
BALB/cByJ m 107.0 2.44   4 1.22 0.0227 105.0, 110.0 0.74
BTBR T+ Itpr3tf/J m 66.0 20.8   4 10.4 0.315 48.8, 92.0 -1.99
BUB/BnJ m 76.0 21.5   4 10.7 0.283 51.7, 96.1 -1.32
C3H/HeJ m 96.3 4.38   4 2.19 0.0454 91.1, 100.0 0.03
C57BL/6J m 99.5 2.57   4 1.29 0.0258 95.7, 101.0 0.24
C57BLKS/J m 85.0 8.48   4 4.24 0.0998 76.9, 94.9 -0.73
C58/J m 74.6 4.84   2   3.42 0.0648 71.2, 78.0 -1.42
CBA/J m 96.3 13.2   4 6.59 0.137 83.8, 115.0 0.03
CZECHII/EiJ m 87.4 5.54   4 2.77 0.0634 81.5, 94.8 -0.57
DBA/2J m 95.6 20.6   4 10.3 0.216 79.7, 124.0 -0.02
FVB/NJ m 104.0 2.22   4 1.11 0.0214 101.0, 106.0 0.54
I/LnJ m 99.4 5.96   4 2.98 0.06 91.3, 106.0 0.23
KK/HlJ m 94.3 4.11   4 2.06 0.0436 89.7, 99.2 -0.11
LG/J m 99.9 11.4   4 5.72 0.114 86.7, 114.0 0.27
LP/J m 101.0 3.46   4 1.73 0.0343 96.2, 104.0 0.34
MA/MyJ m 90.6 4.23   4 2.12 0.0467 84.2, 92.8 -0.35
NOD/ShiLtJ m 89.1 7.72   4 3.86 0.0867 78.2, 95.1 -0.45
NON/ShiLtJ m 76.8 9.8   4 4.9 0.128 64.9, 87.8 -1.27
NZB/BlNJ m 101.0 2.0   4 1.0 0.0198 99.6, 104.0 0.34
NZO/HlLtJ m 92.6 8.4   4 4.2 0.0907 87.5, 105.0 -0.22
NZW/LacJ m 90.9 8.34   4 4.17 0.0917 82.8, 101.0 -0.33
PERA/EiJ m 125.0 10.3   4 5.16 0.0825 113.0, 136.0 1.94
PL/J m 102.0 3.56   4 1.78 0.035 96.3, 104.0 0.41
PWD/PhJ m 145.0 32.4   4 16.2 0.224 118.0, 189.0 3.27
PWK/PhJ m 109.0 5.52   4 2.76 0.0505 102.0, 114.0 0.87
RIIIS/J m 115.0 33.8   4 16.9 0.295 67.1, 139.0 1.27
SEA/GnJ m 81.0 7.73   4 3.86 0.0954 73.0, 90.9 -0.99
SJL/J m 101.0 6.97   4 3.48 0.0688 92.3, 108.0 0.34
SM/J m 102.0 2.74   4 1.37 0.0268 100.0, 106.0 0.41
WSB/EiJ m 95.4 30.3   3 17.5 0.318 74.7, 130.0 -0.03


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ m 72.7975 6.4256 85.5473 60.0477
129X1/SvJ m 88.2625 6.4256 101.0123 75.5127
A/J m 98.7575 6.4256 111.5073 86.0077
AKR/J m 102.2275 6.4256 114.9773 89.4777
BALB/cByJ m 107.375 6.4256 120.1248 94.6252
BTBR T+ Itpr3tf/J m 65.9975 6.4256 78.7473 53.2477
BUB/BnJ m 75.9575 6.4256 88.7073 63.2077
C3H/HeJ m 96.3275 6.4256 109.0773 83.5777
C57BL/6J m 99.4775 6.4256 112.2273 86.7277
C57BLKS/J m 84.97 6.4256 97.7198 72.2202
C58/J m 74.6 9.0872 92.6309 56.5691
CBA/J m 96.29 6.4256 109.0398 83.5402
CZECHII/EiJ m 87.3975 6.4256 100.1473 74.6477
DBA/2J m 95.59 6.4256 108.3398 82.8402
FVB/NJ m 103.635 6.4256 116.3848 90.8852
I/LnJ m 99.37 6.4256 112.1198 86.6202
KK/HlJ m 94.27 6.4256 107.0198 81.5202
LG/J m 99.94 6.4256 112.6898 87.1902
LP/J m 100.9375 6.4256 113.6873 88.1877
MA/MyJ m 90.5975 6.4256 103.3473 77.8477
NOD/ShiLtJ m 89.11 6.4256 101.8598 76.3602
NON/ShiLtJ m 76.765 6.4256 89.5148 64.0152
NZB/BlNJ m 101.4325 6.4256 114.1823 88.6827
NZO/HlLtJ m 92.6125 6.4256 105.3623 79.8627
NZW/LacJ m 90.9175 6.4256 103.6673 78.1677
PERA/EiJ m 124.96 6.4256 137.7098 112.2102
PL/J m 101.535 6.4256 114.2848 88.7852
PWD/PhJ m 144.715 6.4256 157.4648 131.9652
PWK/PhJ m 109.2675 6.4256 122.0173 96.5177
RIIIS/J m 114.785 6.4256 127.5348 102.0352
SEA/GnJ m 81.02 6.4256 93.7698 68.2702
SJL/J m 101.2125 6.4256 113.9623 88.4627
SM/J m 102.1775 6.4256 114.9273 89.4277
WSB/EiJ m 95.3633 7.4197 110.0855 80.6411




  GWAS USING LINEAR MIXED MODELS