Project measure / variable:   Wiltshire4   Tcells_Ida_C


  STRAIN COMPARISON PLOT
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Wiltshire4 - T cells, percent viability dose: 1.235 µM



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested35 strains
Mean of the strain means79.0   %
Median of the strain means87.7   %
SD of the strain means± 23.4
Coefficient of variation (CV)0.297
Min–max range of strain means20.7   –   103   %
Mean sample size per strain3.9   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 34 73494.6743 2161.6081 20.8744 < 0.0001
Residuals 101 10458.8437 103.5529


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 103.0 3.93   4 1.97 0.0382 99.5, 108.0 1.03
129X1/SvJ m 82.9 5.27   4 2.63 0.0635 77.9, 90.2 0.17
A/J m 85.0 4.28   4 2.14 0.0504 80.2, 88.8 0.26
AKR/J m 97.3 1.95   4 0.975 0.02 95.1, 99.4 0.78
BALB/cByJ m 97.6 1.66   4 0.83 0.017 95.7, 99.7 0.79
BTBR T+ Itpr3tf/J m 94.0 2.83   3 1.63 0.0301 91.2, 96.8 0.64
C3H/HeJ m 83.9 5.93   4 2.97 0.0707 77.1, 91.4 0.21
C57BL/6J m 94.3 2.07   4 1.04 0.022 92.4, 97.2 0.65
C57BLKS/J m 20.7 19.9   4 9.93 0.959 9.33, 50.5 -2.49
C57BR/cdJ m 82.0 7.3   4 3.65 0.089 72.7, 89.3 0.13
C58/J m 61.4 8.3   2   5.87 0.135 55.5, 67.2 -0.75
CBA/J m 30.9 8.26   4 4.13 0.267 21.9, 40.9 -2.05
CZECHII/EiJ m 78.2 6.56   4 3.28 0.0839 71.1, 85.2 -0.03
DBA/2J m 87.7 6.38   4 3.19 0.0727 78.3, 92.4 0.37
FVB/NJ m 89.5 2.25   4 1.13 0.0252 86.3, 91.2 0.45
I/LnJ m 40.8 27.6   4 13.8 0.676 20.4, 80.9 -1.63
KK/HlJ m 101.0 2.26   4 1.13 0.0224 98.8, 104.0 0.94
LG/J m 44.2 23.6   4 11.8 0.534 23.1, 71.5 -1.48
LP/J m 85.6 1.46   4 0.728 0.017 84.2, 87.6 0.28
MA/MyJ m 53.1 24.7   4 12.4 0.466 27.7, 77.0 -1.1
NOD/ShiLtJ m 86.6 5.55   4 2.77 0.0641 82.6, 94.8 0.33
NON/ShiLtJ m 89.1 4.07   4 2.03 0.0457 83.0, 91.5 0.43
NZB/BlNJ m 89.2 4.48   4 2.24 0.0502 85.0, 95.5 0.44
NZO/HlLtJ m 36.0 9.93   4 4.97 0.276 26.0, 49.0 -1.83
NZW/LacJ m 86.0 2.47   4 1.24 0.0287 84.2, 89.7 0.3
PERA/EiJ m 28.7 15.7   4 7.87 0.548 12.3, 46.5 -2.14
PL/J m 92.0 5.79   4 2.89 0.0629 84.2, 98.2 0.56
PWD/PhJ m 102.0 2.95   4 1.47 0.0288 99.7, 105.0 0.98
PWK/PhJ m 89.1 13.1   4 6.56 0.147 72.7, 103.0 0.43
RIIIS/J m 101.0 3.23   4 1.62 0.0321 98.2, 105.0 0.94
SEA/GnJ m 93.9 0.873   4 0.436 0.00929 93.2, 95.2 0.64
SJL/J m 88.5 2.41   4 1.2 0.0272 85.3, 90.4 0.41
SM/J m 79.6 11.2   4 5.62 0.141 63.9, 90.6 0.03
SWR/J m 91.0 2.48   4 1.24 0.0273 89.2, 94.7 0.51
WSB/EiJ m 98.2 6.31   3 3.65 0.0643 91.1, 103.0 0.82


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ m 103.02 5.088 113.1133 92.9267
129X1/SvJ m 82.895 5.088 92.9883 72.8017
A/J m 84.9525 5.088 95.0458 74.8592
AKR/J m 97.305 5.088 107.3983 87.2117
BALB/cByJ m 97.635 5.088 107.7283 87.5417
BTBR T+ Itpr3tf/J m 94.0267 5.8752 105.6814 82.3719
C3H/HeJ m 83.8725 5.088 93.9658 73.7792
C57BL/6J m 94.3025 5.088 104.3958 84.2092
C57BLKS/J m 20.7125 5.088 30.8058 10.6192
C57BR/cdJ m 82.045 5.088 92.1383 71.9517
C58/J m 61.38 7.1956 75.6541 47.1059
CBA/J m 30.9025 5.088 40.9958 20.8092
CZECHII/EiJ m 78.2225 5.088 88.3158 68.1292
DBA/2J m 87.7025 5.088 97.7958 77.6092
FVB/NJ m 89.47 5.088 99.5633 79.3767
I/LnJ m 40.775 5.088 50.8683 30.6817
KK/HlJ m 100.69 5.088 110.7833 90.5967
LG/J m 44.2075 5.088 54.3008 34.1142
LP/J m 85.6175 5.088 95.7108 75.5242
MA/MyJ m 53.1225 5.088 63.2158 43.0292
NOD/ShiLtJ m 86.565 5.088 96.6583 76.4717
NON/ShiLtJ m 89.075 5.088 99.1683 78.9817
NZB/BlNJ m 89.23 5.088 99.3233 79.1367
NZO/HlLtJ m 35.9925 5.088 46.0858 25.8992
NZW/LacJ m 85.9975 5.088 96.0908 75.9042
PERA/EiJ m 28.74 5.088 38.8333 18.6467
PL/J m 92.0125 5.088 102.1058 81.9192
PWD/PhJ m 102.425 5.088 112.5183 92.3317
PWK/PhJ m 89.09 5.088 99.1833 78.9967
RIIIS/J m 100.8375 5.088 110.9308 90.7442
SEA/GnJ m 93.94 5.088 104.0333 83.8467
SJL/J m 88.5 5.088 98.5933 78.4067
SM/J m 79.5675 5.088 89.6608 69.4742
SWR/J m 90.9825 5.088 101.0758 80.8892
WSB/EiJ m 98.2367 5.8752 109.8914 86.5819




  GWAS USING LINEAR MIXED MODELS