Project measure / variable:   Schoonjans1   MCA_plasma_t0_HFD

ID, description, units MPD:112663   MCA_plasma_t0_HFD   plasma bile acid γ-muricholic acid, glucose kinetic test, at 20 wks of age, at 0 min   [ng/mL]  HFD  
high-fat diet study
Data set, strains Schoonjans1   BXD w/par   10 strains     sex: m     age: 20wks
Procedure biomarker quantification
Ontology mappings

  •   Or, add this measure to your collection.
       
  •     no folder
  •     put it in new folder  

  STRAIN COMPARISON PLOT
Dimensions Width:   px    Height:   px
Download Plot   
Visualization Options

Schoonjans1 - plasma bile acid γ-muricholic acid, glucose kinetic test, at 20 wks of age, at 0 min HFD



  MEASURE SUMMARY
Measure Summary Male
Number of strains tested10 strains
Mean of the strain means1.8611   ng/mL
Median of the strain means1.897   ng/mL
SD of the strain means± 0.46449
Coefficient of variation (CV)0.2496
Min–max range of strain means1.212   –   2.6303   ng/mL
Mean sample size per strain1.2   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
strain 1 1.531 1.531 2.0803 0.286
Residuals 2 1.4719 0.736


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
BXD11 m 2.248 0.0   1   0.0 0.0 2.248, 2.248 0.83
BXD12 m 2.146 0.0   1   0.0 0.0 2.146, 2.146 0.61
BXD27 m 1.386 0.0   1   0.0 0.0 1.386, 1.386 -1.02
BXD40 m 1.393 0.27011   2   0.191 0.1939 1.202, 1.584 -1.01
BXD45 m 1.212 0.0   1   0.0 0.0 1.212, 1.212 -1.4
BXD49 m 1.94 0.0   1   0.0 0.0 1.94, 1.94 0.17
BXD6 m 2.6303 1.1828   2   0.83635 0.4497 1.794, 3.4667 1.66
BXD66 m 1.854 0.0   1   0.0 0.0 1.854, 1.854 -0.02
BXD77 m 1.552 0.0   1   0.0 0.0 1.552, 1.552 -0.67
BXD89 m 2.25 0.0   1   0.0 0.0 2.25, 2.25 0.84


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
BXD40 m 1.393 0.6066145079 4.0030515685 -1.2170515685
BXD6 m 2.63035 0.6066145079 5.2404015685 0.0202984315




  GWAS USING LINEAR MIXED MODELS