Project measure / variable:   Harrill1   liver_CHOL_trt

ID, description, units MPD:39527   liver_CHOL_trt   hepatic cholesterol (CHOL)   [mg/dL]  isoniazid  
isoniazid study
Data set, strains Harrill1   inbred   34 strains     sex: f     age: 8-10wks
Procedure lipid profile
Ontology mappings

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  STRAIN COMPARISON PLOT
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Harrill1 - hepatic cholesterol (CHOL) isoniazid



  MEASURE SUMMARY
Measure Summary Female
Number of strains tested34 strains
Mean of the strain means27.9   mg/dL
Median of the strain means27.1   mg/dL
SD of the strain means± 9.49
Coefficient of variation (CV)0.339
Min–max range of strain means8.75   –   55.0   mg/dL
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 33 11143.1231 337.6704 3.9011 < 0.0001
Residuals 100 8655.75 86.5575


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 41.8 14.2   4 7.11 0.341 21.0, 51.0 1.46
A/J f 32.5 8.19   4 4.09 0.252 21.0, 40.0 0.48
AKR/J f 31.0 7.96   4 3.98 0.257 20.0, 39.0 0.32
BALB/cJ f 35.8 4.57   4 2.29 0.128 29.0, 39.0 0.83
BTBR T+ Itpr3tf/J f 38.5 22.2   4 11.1 0.576 11.0, 57.0 1.11
BUB/BnJ f 30.2 4.03   4 2.02 0.133 26.0, 35.0 0.24
C3H/HeJ f 15.5 2.65   4 1.32 0.171 13.0, 19.0 -1.31
C57BL/6J f 18.2 2.06   4 1.03 0.113 16.0, 21.0 -1.03
C57BLKS/J f 38.0 5.48   4 2.74 0.144 30.0, 42.0 1.06
C57BR/cdJ f 19.8 9.07   4 4.53 0.459 9.0, 31.0 -0.86
C58/J f 21.8 7.41   4 3.71 0.341 12.0, 30.0 -0.65
CBA/J f 13.8 5.32   4 2.66 0.387 6.0, 18.0 -1.49
CE/J f 34.5 2.38   4 1.19 0.069 32.0, 37.0 0.69
DBA/2J f 31.2 3.69   4 1.84 0.118 27.0, 36.0 0.34
FVB/NJ f 31.5 10.3   4 5.14 0.326 19.0, 44.0 0.37
I/LnJ f 17.8 3.1   4 1.55 0.174 15.0, 22.0 -1.07
KK/HlJ f 26.0 5.77   4 2.89 0.222 19.0, 33.0 -0.21
LG/J f 55.0 17.7   3 10.2 0.322 39.0, 74.0 2.85
LP/J f 21.2 7.27   4 3.64 0.342 16.0, 32.0 -0.71
MA/MyJ f 42.2 24.1   4 12.0 0.569 14.0, 66.0 1.5
MRL/MpJ f 27.2 1.26   4 0.629 0.0462 26.0, 29.0 -0.08
NOD/ShiLtJ f 30.8 5.5   4 2.75 0.179 26.0, 38.0 0.3
NON/ShiLtJ f 8.75 9.74   4 4.87 1.11 2.0, 23.0 -2.02
NOR/LtJ f 30.8 5.91   4 2.95 0.192 25.0, 38.0 0.3
NZW/LacJ f 36.5 3.0   4 1.5 0.0822 34.0, 40.0 0.9
P/J f 26.5 3.32   4 1.66 0.125 23.0, 31.0 -0.15
PL/J f 26.0 18.1   4 9.04 0.695 5.0, 49.0 -0.21
PWK/PhJ f 26.2 7.59   4 3.79 0.289 16.0, 34.0 -0.18
RIIIS/J f 14.2 10.1   4 5.04 0.707 4.0, 28.0 -1.45
SEA/GnJ f 24.0 4.24   4 2.12 0.177 20.0, 29.0 -0.42
SJL/J f 30.5 2.65   4 1.32 0.0867 28.0, 34.0 0.27
SM/J f 26.5 4.65   4 2.33 0.176 22.0, 31.0 -0.15
SWR/J f 19.0 2.83   4 1.41 0.149 15.0, 21.0 -0.94
WSB/EiJ f 27.0 11.4   3 6.56 0.421 19.0, 40.0 -0.1


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 41.75 4.6518 50.9791 32.5209
A/J f 32.5 4.6518 41.7291 23.2709
AKR/J f 31.0 4.6518 40.2291 21.7709
BALB/cJ f 35.75 4.6518 44.9791 26.5209
BTBR T+ Itpr3tf/J f 38.5 4.6518 47.7291 29.2709
BUB/BnJ f 30.25 4.6518 39.4791 21.0209
C3H/HeJ f 15.5 4.6518 24.7291 6.2709
C57BL/6J f 18.25 4.6518 27.4791 9.0209
C57BLKS/J f 38.0 4.6518 47.2291 28.7709
C57BR/cdJ f 19.75 4.6518 28.9791 10.5209
C58/J f 21.75 4.6518 30.9791 12.5209
CBA/J f 13.75 4.6518 22.9791 4.5209
CE/J f 34.5 4.6518 43.7291 25.2709
DBA/2J f 31.25 4.6518 40.4791 22.0209
FVB/NJ f 31.5 4.6518 40.7291 22.2709
I/LnJ f 17.75 4.6518 26.9791 8.5209
KK/HlJ f 26.0 4.6518 35.2291 16.7709
LG/J f 55.0 5.3715 65.6568 44.3432
LP/J f 21.25 4.6518 30.4791 12.0209
MA/MyJ f 42.25 4.6518 51.4791 33.0209
MRL/MpJ f 27.25 4.6518 36.4791 18.0209
NOD/ShiLtJ f 30.75 4.6518 39.9791 21.5209
NON/ShiLtJ f 8.75 4.6518 17.9791 0.0
NOR/LtJ f 30.75 4.6518 39.9791 21.5209
NZW/LacJ f 36.5 4.6518 45.7291 27.2709
P/J f 26.5 4.6518 35.7291 17.2709
PL/J f 26.0 4.6518 35.2291 16.7709
PWK/PhJ f 26.25 4.6518 35.4791 17.0209
RIIIS/J f 14.25 4.6518 23.4791 5.0209
SEA/GnJ f 24.0 4.6518 33.2291 14.7709
SJL/J f 30.5 4.6518 39.7291 21.2709
SM/J f 26.5 4.6518 35.7291 17.2709
SWR/J f 19.0 4.6518 28.2291 9.7709
WSB/EiJ f 27.0 5.3715 37.6568 16.3432




  GWAS USING LINEAR MIXED MODELS