Project measure / variable:   Seburn1   cal

ID, description, units MPD:9234   cal   caloric intake   [kcal/d]  daily  
Data set, strains Seburn1   inbred   16 strains     sex: both     age: 7-9wks
Procedure intake monitoring
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  STRAIN COMPARISON PLOT
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Seburn1 - caloric intake daily



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested15 strains13 strains
Mean of the strain means9.95   kcal/d 10.4   kcal/d
Median of the strain means9.34   kcal/d 10.9   kcal/d
SD of the strain means± 1.39 ± 2.17
Coefficient of variation (CV)0.140 0.208
Min–max range of strain means7.99   –   13.3   kcal/d 5.51   –   13.5   kcal/d
Mean sample size per strain7.8   mice 7.9   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 10.3756 10.3756 3.086 0.0808
strain 11 377.2831 34.2985 10.2014 < 0.0001
sex:strain 11 196.7851 17.8896 5.3209 < 0.0001
Residuals 166 558.1129 3.3621


Q-Q normality assessment based on residuals

  


  STRAIN MEANS (UNADJUSTED)
  
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Strain Sex Mean SD N mice SEM CV Min, Max Z score
129S1/SvImJ f 9.33 1.2   8 0.425 0.129 8.0, 11.4 -0.45
A/J f 9.19 1.24   8 0.438 0.135 7.3, 11.3 -0.55
A/J m 5.51 0.858   8 0.303 0.156 4.2, 6.7 -2.26
AKR/J f 8.71 2.72   7 1.03 0.312 6.0, 13.0 -0.89
AKR/J m 9.11 1.97   8 0.696 0.216 5.3, 11.5 -0.6
BALB/cJ f 9.95 1.51   8 0.535 0.152 7.3, 11.8 0.0
BALB/cJ m 12.8 1.01   8 0.357 0.0789 11.3, 14.3 1.1
BTBR T+ Itpr3tf/J f 12.2 1.03   6 0.42 0.0844 11.0, 13.8 1.62
C3H/HeJ f 9.24 0.625   8 0.221 0.0677 8.5, 10.4 -0.51
C3H/HeJ m 10.9 0.769   8 0.272 0.0707 9.9, 12.0 0.22
C57BL/6J f 9.34 0.661   8 0.234 0.0708 8.5, 10.3 -0.44
C57BL/6J m 8.33 0.676   8 0.239 0.0812 7.2, 9.4 -0.96
CAST/EiJ f 7.99 1.29   8 0.457 0.162 6.7, 10.4 -1.41
CAST/EiJ m 9.61 1.37   8 0.483 0.142 7.9, 11.7 -0.37
CBA/J f 11.3 0.663   8 0.234 0.0588 10.3, 12.0 0.97
CBA/J m 10.2 1.08   7 0.407 0.106 8.7, 11.5 -0.1
FVB/NJ f 9.56 1.12   8 0.395 0.117 7.1, 10.6 -0.28
FVB/NJ m 13.5 3.12   8 1.1 0.23 6.8, 16.9 1.42
LP/J f 9.18 1.41   8 0.499 0.154 7.0, 10.9 -0.55
LP/J m 8.8 0.595   8 0.21 0.0676 7.9, 9.5 -0.74
NOD/ShiLtJ f 10.7 0.991   6 0.405 0.0929 8.8, 11.6 0.54
NZB/BlNJ f 10.0 0.4   8 0.141 0.0398 9.5, 10.7 0.04
NZB/BlNJ m 11.0 1.85   8 0.655 0.169 9.3, 15.3 0.27
PL/J f 9.26 2.52   8 0.891 0.272 3.9, 11.7 -0.5
PL/J m 11.2 0.834   8 0.295 0.0744 10.0, 12.7 0.36
SJL/J m 12.6 0.858   7 0.324 0.0679 11.8, 14.3 1.01
SWR/J f 13.3 5.6   8 1.98 0.422 9.4, 26.9 2.41
SWR/J m 11.8 1.34   8 0.475 0.114 9.9, 13.7 0.64


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
A/J f 9.1875 0.6483 10.4674 7.9076
A/J m 5.5125 0.6483 6.7924 4.2326
AKR/J f 8.7143 0.693 10.0826 7.346
AKR/J m 9.1125 0.6483 10.3924 7.8326
BALB/cJ f 9.95 0.6483 11.2299 8.6701
BALB/cJ m 12.7875 0.6483 14.0674 11.5076
C3H/HeJ f 9.2375 0.6483 10.5174 7.9576
C3H/HeJ m 10.875 0.6483 12.1549 9.5951
C57BL/6J f 9.3375 0.6483 10.6174 8.0576
C57BL/6J m 8.325 0.6483 9.6049 7.0451
CAST/EiJ f 7.9875 0.6483 9.2674 6.7076
CAST/EiJ m 9.6125 0.6483 10.8924 8.3326
CBA/J f 11.275 0.6483 12.5549 9.9951
CBA/J m 10.1714 0.693 11.5397 8.8031
FVB/NJ f 9.5625 0.6483 10.8424 8.2826
FVB/NJ m 13.5375 0.6483 14.8174 12.2576
LP/J f 9.175 0.6483 10.4549 7.8951
LP/J m 8.8 0.6483 10.0799 7.5201
NZB/BlNJ f 10.05 0.6483 11.3299 8.7701
NZB/BlNJ m 11.0 0.6483 12.2799 9.7201
PL/J f 9.2625 0.6483 10.5424 7.9826
PL/J m 11.2125 0.6483 12.4924 9.9326
SWR/J f 13.275 0.6483 14.5549 11.9951
SWR/J m 11.8 0.6483 13.0799 10.5201


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
A/J both 7.35 0.4584 8.2551 6.4449
AKR/J both 8.9134 0.4745 9.8502 7.9766
BALB/cJ both 11.3687 0.4584 12.2738 10.4637
C3H/HeJ both 10.0562 0.4584 10.9613 9.1512
C57BL/6J both 8.8312 0.4584 9.7363 7.9262
CAST/EiJ both 8.8 0.4584 9.7051 7.8949
CBA/J both 10.7232 0.4745 11.66 9.7864
FVB/NJ both 11.55 0.4584 12.4551 10.6449
LP/J both 8.9875 0.4584 9.8926 8.0824
NZB/BlNJ both 10.525 0.4584 11.4301 9.6199
PL/J both 10.2375 0.4584 11.1426 9.3324
SWR/J both 12.5375 0.4584 13.4426 11.6324




  GWAS USING LINEAR MIXED MODELS