Project measure / variable:   Bodnar1   chow6

ID, description, units MPD:22603   chow6   daily chow intake with sucrose in drinking water   [g]  2.5% sucrose  
sucrose study
Data set, strains Bodnar1   inbred   11 strains     sex: m     age: 13-17wks
Procedure intake monitoring
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  STRAIN COMPARISON PLOT
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Bodnar1 - daily chow intake with sucrose in drinking water 2.5% sucrose



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested11 strains
Mean of the strain means4.48   g
Median of the strain means4.66   g
SD of the strain means± 1.13
Coefficient of variation (CV)0.253
Min–max range of strain means2.72   –   6.71   g
Mean sample size per strain10.0   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 10 126.5523 12.6552 7.1226 < 0.0001
Residuals 108 191.8921 1.7768


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
A/J m 4.34 1.0   10 0.317 0.231 2.5, 5.9 -0.12
AKR/J m 4.66 0.629   10 0.199 0.135 3.3, 5.5 0.16
BALB/cJ m 6.71 0.877   10 0.277 0.131 5.6, 8.4 1.96
C3H/HeJ m 5.07 0.685   10 0.217 0.135 4.2, 6.6 0.52
C57BL/10J m 3.22 1.59   10 0.503 0.494 -1.11
C57BL/6J m 4.97 1.9   10 0.6 0.382 3.6, 10.2 0.43
CBA/J m 3.16 0.811   10 0.257 0.257 1.8, 4.2 -1.16
Crl:CD-1(ICR) m 4.81 2.29   20 0.511 0.475 0.4, 10.8 0.29
DBA/2J m 5.32 0.63   10 0.199 0.118 4.5, 6.5 0.74
SJL/J m 2.72 0.319   9 0.106 0.117 2.4, 3.2 -1.55
SWR/J m 4.32 0.614   10 0.194 0.142 3.4, 5.1 -0.14


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
A/J m 4.34 0.4215 5.1755 3.5045
AKR/J m 4.66 0.4215 5.4955 3.8245
BALB/cJ m 6.71 0.4215 7.5455 5.8745
C3H/HeJ m 5.07 0.4215 5.9055 4.2345
C57BL/10J m 3.22 0.4215 4.0555 2.3845
C57BL/6J m 4.97 0.4215 5.8055 4.1345
CBA/J m 3.16 0.4215 3.9955 2.3245
Crl:CD-1(ICR) m 4.815 0.2981 5.4058 4.2242
DBA/2J m 5.32 0.4215 6.1555 4.4845
SJL/J m 2.7222 0.4443 3.6029 1.8415
SWR/J m 4.32 0.4215 5.1555 3.4845




  GWAS USING LINEAR MIXED MODELS