Project measure / variable:   Auwerx2   rer_max_treadmill_HFD

ID, description, units MPD:114646   rer_max_treadmill_HFD   maximum respiratory exchange ratio (RER), treadmill test (VCO2:VO2)   [ratio]  HFD  
Data set, strains Auwerx2   inbred w/CC8   9 strains     sex: both     age: 19wks
Procedure monitoring system
Ontology mappings

  STRAIN COMPARISON PLOT
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Auwerx2 - maximum respiratory exchange ratio (RER), treadmill test (VCO2:VO2) HFD



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested9 strains9 strains
Mean of the strain means0.86892   ratio 0.85108   ratio
Median of the strain means0.86234   ratio 0.86138   ratio
SD of the strain means± 0.03182 ± 0.05603
Coefficient of variation (CV)0.0366 0.0658
Min–max range of strain means0.81605   –   0.90952   ratio 0.76473   –   0.94961   ratio
Mean sample size per strain4.4   mice 3.6   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 0.0002 0.0002 0.1542 0.6962
strain 7 0.0691 0.0099 7.1704 < 0.0001
sex:strain 7 0.0136 0.0019 1.4082 0.223
Residuals 50 0.0688 0.0014


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 0.89376 0.03201   5 0.01432 0.0358 0.85744, 0.93394 0.78
129S1/SvImJ m 0.86349 0.03352   2   0.0237 0.0388 0.83979, 0.88719 0.22
A/J f 0.90952 0.03926   4 0.01963 0.0432 0.87465, 0.96396 1.28
A/J m 0.94961 0.02555   5 0.01143 0.0269 0.92295, 0.98416 1.76
C57BL/6J f 0.86234 0.01591   3 0.00918835 0.0185 0.84556, 0.87722 -0.21
C57BL/6J m 0.88602 0.06803   3 0.03928 0.0768 0.81776, 0.95382 0.62
CAST/EiJ f 0.84367 0.04065   5 0.01818 0.0482 0.80786, 0.90441 -0.79
CAST/EiJ m 0.77571 0.00248194   2   0.001755 0.0032 0.77396, 0.77747 -1.35
DBA/2J f 0.88406 0.04403   5 0.01969 0.0498 0.83742, 0.9512 0.48
DBA/2J m 0.8721 0.04055   5 0.01814 0.0465 0.82604, 0.91042 0.38
NOD/ShiLtJ f 0.85562 0.0244   6 0.0099599 0.0285 0.8258, 0.88841 -0.42
NOD/ShiLtJ m 0.85411 0.02712   5 0.01213 0.0318 0.82802, 0.89856 0.05
NZO/HlLtJ f 0.90761 0.05497   5 0.02458 0.0606 0.82694, 0.96678 1.22
NZO/HlLtJ m 0.76473 0.0   1   0.0 0.0 0.76473, 0.76473 -1.54
PWK/PhJ f 0.84762 0.04642   4 0.02321 0.0548 0.79078, 0.88843 -0.67
PWK/PhJ m 0.86138 0.05171   5 0.02312 0.06 0.77676, 0.906 0.18
WSB/EiJ f 0.81605 0.02668   3 0.01541 0.0327 0.7924, 0.84498 -1.66
WSB/EiJ m 0.83259 0.01953   4 0.00976607 0.0235 0.81006, 0.85645 -0.33


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 0.893762 0.0165911516 0.9270863087 0.8604376913
129S1/SvImJ m 0.86349 0.026232914 0.9161803585 0.8107996415
A/J f 0.9095225 0.0185494714 0.9467802098 0.8722647902
A/J m 0.949614 0.0165911516 0.9829383087 0.9162896913
C57BL/6J f 0.8623366667 0.0214190846 0.9053581642 0.8193151691
C57BL/6J m 0.8860233333 0.0214190846 0.9290448309 0.8430018358
CAST/EiJ f 0.843668 0.0165911516 0.8769923087 0.8103436913
CAST/EiJ m 0.775715 0.026232914 0.8284053585 0.7230246415
DBA/2J f 0.88406 0.0165911516 0.9173843087 0.8507356913
DBA/2J m 0.872096 0.0165911516 0.9054203087 0.8387716913
NOD/ShiLtJ f 0.855615 0.01514558 0.8860357927 0.8251942073
NOD/ShiLtJ m 0.854114 0.0165911516 0.8874383087 0.8207896913
PWK/PhJ f 0.8476175 0.0185494714 0.8848752098 0.8103597902
PWK/PhJ m 0.86138 0.0165911516 0.8947043087 0.8280556913
WSB/EiJ f 0.8160533333 0.0214190846 0.8590748309 0.7730318358
WSB/EiJ m 0.832585 0.0185494714 0.8698427098 0.7953272902


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 0.878626 0.0155196012 0.9097980365 0.8474539635
A/J both 0.92956825 0.0124433637 0.9545614815 0.9045750185
C57BL/6J both 0.87418 0.01514558 0.9046007927 0.8437592073
CAST/EiJ both 0.8096915 0.0155196012 0.8408635365 0.7785194635
DBA/2J both 0.878078 0.0117317158 0.9016418447 0.8545141553
NOD/ShiLtJ both 0.8548645 0.0112322627 0.8774251636 0.8323038364
PWK/PhJ both 0.85449875 0.0124433637 0.8794919815 0.8295055185
WSB/EiJ both 0.8243191667 0.0141673928 0.8527752126 0.7958631208




  GWAS USING LINEAR MIXED MODELS