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Project measure / variable:   Auwerx2   rer_day_HFD

ID, description, units MPD:114578   rer_day_HFD   respiratory exchange rate (VCO2:VO2), 24h test, day time average   [ratio]  HFD  
Data set, strains Auwerx2   inbred w/CC8   9 strains     sex: both     age: 14wks
Procedure monitoring system
Ontology mappings

  STRAIN COMPARISON PLOT
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Auwerx2 - respiratory exchange rate (VCO2:VO2), 24h test, day time average HFD



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested9 strains9 strains
Mean of the strain means0.75697   ratio 0.7393   ratio
Median of the strain means0.75961   ratio 0.74029   ratio
SD of the strain means± 0.01475 ± 0.02225
Coefficient of variation (CV)0.0195 0.0301
Min–max range of strain means0.73127   –   0.77867   ratio 0.693   –   0.76582   ratio
Mean sample size per strain4.4   mice 3.8   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 0.0027 0.0027 11.169 0.0015
strain 7 0.0056 0.0008 3.2914 0.0057
sex:strain 7 0.0068 0.001 4.0166 0.0014
Residuals 52 0.0126 0.0002


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 0.75961 0.01518   5 0.00678955 0.02 0.74403, 0.77616 0.18
129S1/SvImJ m 0.75012 0.00224153   2   0.001585 0.003 0.74854, 0.75171 0.49
A/J f 0.77867 0.0237   4 0.01185 0.0304 0.75094, 0.80744 1.47
A/J m 0.73071 0.01547   5 0.00691785 0.0212 0.70513, 0.74334 -0.39
C57BL/6J f 0.76964 0.01011   3 0.00583956 0.0131 0.75861, 0.77848 0.86
C57BL/6J m 0.74029 0.01554   4 0.00776936 0.021 0.71753, 0.75253 0.04
CAST/EiJ f 0.74957 0.01076   5 0.00481065 0.0144 0.738, 0.76404 -0.5
CAST/EiJ m 0.76582 0.02164   2   0.0153 0.0283 0.75052, 0.78113 1.19
DBA/2J f 0.76439 0.02828   5 0.01265 0.037 0.73206, 0.80381 0.5
DBA/2J m 0.76488 0.00855403   5 0.00382548 0.0112 0.755, 0.77496 1.15
NOD/ShiLtJ f 0.74284 0.01324   6 0.00540652 0.0178 0.73297, 0.7619 -0.96
NOD/ShiLtJ m 0.73373 0.0136   5 0.00608192 0.0185 0.71987, 0.75026 -0.25
NZO/HlLtJ f 0.76633 0.00850698   5 0.00380444 0.0111 0.75823, 0.77835 0.64
NZO/HlLtJ m 0.693 0.0   1   0.0 0.0 0.693, 0.693 -2.08
PWK/PhJ f 0.75038 0.00300254   4 0.00150127 0.004 0.74696, 0.75304 -0.45
PWK/PhJ m 0.72682 0.00988137   5 0.00441909 0.0136 0.71154, 0.73723 -0.56
WSB/EiJ f 0.73127 0.01122   3 0.00647659 0.0153 0.72154, 0.74354 -1.74
WSB/EiJ m 0.74834 0.01892   5 0.00845998 0.0253 0.72681, 0.77531 0.41


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 0.759606 0.0069722687 0.7735968808 0.7456151192
129S1/SvImJ m 0.750125 0.0110241248 0.7722465248 0.7280034752
A/J f 0.77867 0.0077952334 0.7943122802 0.7630277198
A/J m 0.730706 0.0069722687 0.7446968808 0.7167151192
C57BL/6J f 0.76964 0.0090011602 0.7877021494 0.7515778506
C57BL/6J m 0.7402925 0.0077952334 0.7559347802 0.7246502198
CAST/EiJ f 0.749566 0.0069722687 0.7635568808 0.7355751192
CAST/EiJ m 0.765825 0.0110241248 0.7879465248 0.7437034752
DBA/2J f 0.764388 0.0069722687 0.7783788808 0.7503971192
DBA/2J m 0.764884 0.0069722687 0.7788748808 0.7508931192
NOD/ShiLtJ f 0.74284 0.0063647814 0.7556118683 0.7300681317
NOD/ShiLtJ m 0.73373 0.0069722687 0.7477208808 0.7197391192
PWK/PhJ f 0.750375 0.0077952334 0.7660172802 0.7347327198
PWK/PhJ m 0.726822 0.0069722687 0.7408128808 0.7128311192
WSB/EiJ f 0.73127 0.0090011602 0.7493321494 0.7132078506
WSB/EiJ m 0.74834 0.0069722687 0.7623308808 0.7343491192


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 0.7548655 0.0065219602 0.7679527706 0.7417782294
A/J both 0.754688 0.0052292015 0.7651811606 0.7441948394
C57BL/6J both 0.75496625 0.0059537079 0.7669132389 0.7430192611
CAST/EiJ both 0.7576955 0.0065219602 0.7707827706 0.7446082294
DBA/2J both 0.764636 0.0049301385 0.7745290467 0.7547429533
NOD/ShiLtJ both 0.738285 0.0047202482 0.7477568711 0.7288131289
PWK/PhJ both 0.7385985 0.0052292015 0.7490916606 0.7281053394
WSB/EiJ both 0.739805 0.0056928336 0.7512285063 0.7283814937




  GWAS USING LINEAR MIXED MODELS