Project measure / variable:   Wiltshire4   Bcells_Dox_B


  STRAIN COMPARISON PLOT
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Wiltshire4 - B cells, percent viability dose: 0.137 µM



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested35 strains
Mean of the strain means64.1   %
Median of the strain means61.1   %
SD of the strain means± 17.9
Coefficient of variation (CV)0.280
Min–max range of strain means23.6   –   104   %
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 34 40009.7022 1176.7559 4.1742 < 0.0001
Residuals 102 28754.935 281.9111


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 90.1 37.5   4 18.8 0.417 57.7, 130.0 1.45
129X1/SvJ m 62.2 7.01   4 3.51 0.113 52.6, 69.5 -0.1
A/J m 81.7 5.82   4 2.91 0.0713 76.8, 89.9 0.99
AKR/J m 60.7 12.7   4 6.35 0.209 49.1, 75.0 -0.19
BALB/cByJ m 92.1 6.52   4 3.26 0.0708 84.7, 98.1 1.57
BTBR T+ Itpr3tf/J m 76.4 13.6   4 6.82 0.179 61.9, 91.6 0.69
C3H/HeJ m 47.9 9.45   4 4.73 0.197 38.8, 60.3 -0.9
C57BL/6J m 62.1 12.6   4 6.28 0.202 47.8, 77.5 -0.11
C57BLKS/J m 53.3 14.6   4 7.32 0.274 39.9, 74.2 -0.6
C57BR/cdJ m 41.9 8.98   4 4.49 0.214 33.5, 54.3 -1.24
C58/J m 95.0 26.4   2   18.7 0.278 76.4, 114.0 1.73
CBA/J m 64.0 20.6   4 10.3 0.322 43.2, 87.5 0.0
CZECHII/EiJ m 53.2 6.87   4 3.43 0.129 46.2, 62.2 -0.61
DBA/2J m 39.9 7.16   4 3.58 0.179 30.4, 45.8 -1.35
FVB/NJ m 60.6 10.2   4 5.12 0.169 52.1, 74.3 -0.19
I/LnJ m 58.0 29.1   4 14.5 0.501 26.0, 88.9 -0.34
KK/HlJ m 78.6 3.12   4 1.56 0.0397 75.9, 82.7 0.81
LG/J m 74.8 8.96   4 4.48 0.12 66.2, 87.4 0.6
LP/J m 38.5 5.27   4 2.63 0.137 35.1, 46.3 -1.43
MA/MyJ m 74.4 12.4   4 6.19 0.167 57.8, 84.4 0.58
NOD/ShiLtJ m 69.3 20.5   4 10.2 0.296 54.0, 99.3 0.29
NON/ShiLtJ m 46.0 4.24   4 2.12 0.0922 40.8, 50.2 -1.01
NZB/BlNJ m 57.3 6.84   4 3.42 0.119 47.8, 64.0 -0.38
NZO/HlLtJ m 59.8 20.1   4 10.0 0.335 29.9, 72.4 -0.24
NZW/LacJ m 68.5 11.5   4 5.76 0.168 58.9, 81.9 0.25
PERA/EiJ m 65.9 21.9   4 11.0 0.333 43.8, 93.5 0.1
PL/J m 61.1 5.98   4 2.99 0.0978 55.9, 66.2 -0.16
PWD/PhJ m 57.6 12.9   4 6.46 0.224 45.6, 75.9 -0.36
PWK/PhJ m 90.4 6.13   4 3.07 0.0678 81.7, 95.8 1.47
RIIIS/J m 44.9 19.7   4 9.85 0.438 25.7, 72.5 -1.07
SEA/GnJ m 80.0 18.5   4 9.24 0.231 56.6, 97.0 0.89
SJL/J m 23.6 11.4   4 5.7 0.483 13.3, 38.0 -2.26
SM/J m 48.5 21.5   4 10.7 0.442 27.8, 78.7 -0.87
SWR/J m 59.6 45.4   4 22.7 0.762 30.9, 127.0 -0.25
WSB/EiJ m 104.0 9.75   3 5.63 0.0939 93.2, 112.0 2.23


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ m 90.0975 8.3951 106.7492 73.4458
129X1/SvJ m 62.19 8.3951 78.8417 45.5383
A/J m 81.675 8.3951 98.3267 65.0233
AKR/J m 60.7325 8.3951 77.3842 44.0808
BALB/cByJ m 92.13 8.3951 108.7817 75.4783
BTBR T+ Itpr3tf/J m 76.4425 8.3951 93.0942 59.7908
C3H/HeJ m 47.9325 8.3951 64.5842 31.2808
C57BL/6J m 62.1175 8.3951 78.7692 45.4658
C57BLKS/J m 53.3325 8.3951 69.9842 36.6808
C57BR/cdJ m 41.89 8.3951 58.5417 25.2383
C58/J m 95.04 11.8725 118.589 71.491
CBA/J m 63.9575 8.3951 80.6092 47.3058
CZECHII/EiJ m 53.2225 8.3951 69.8742 36.5708
DBA/2J m 39.9125 8.3951 56.5642 23.2608
FVB/NJ m 60.6325 8.3951 77.2842 43.9808
I/LnJ m 58.035 8.3951 74.6867 41.3833
KK/HlJ m 78.6475 8.3951 95.2992 61.9958
LG/J m 74.785 8.3951 91.4367 58.1333
LP/J m 38.45 8.3951 55.1017 21.7983
MA/MyJ m 74.365 8.3951 91.0167 57.7133
NOD/ShiLtJ m 69.2975 8.3951 85.9492 52.6458
NON/ShiLtJ m 46.0425 8.3951 62.6942 29.3908
NZB/BlNJ m 57.335 8.3951 73.9867 40.6833
NZO/HlLtJ m 59.8475 8.3951 76.4992 43.1958
NZW/LacJ m 68.4575 8.3951 85.1092 51.8058
PERA/EiJ m 65.895 8.3951 82.5467 49.2433
PL/J m 61.075 8.3951 77.7267 44.4233
PWD/PhJ m 57.6225 8.3951 74.2742 40.9708
PWK/PhJ m 90.4275 8.3951 107.0792 73.7758
RIIIS/J m 44.93 8.3951 61.5817 28.2783
SEA/GnJ m 79.955 8.3951 96.6067 63.3033
SJL/J m 23.6 8.3951 40.2517 6.9483
SM/J m 48.5425 8.3951 65.1942 31.8908
SWR/J m 59.575 8.3951 76.2267 42.9233
WSB/EiJ m 103.87 9.6938 123.0977 84.6423




  GWAS USING LINEAR MIXED MODELS