Project measure / variable:   Jaxpheno6   pct_NKT_8

ID, description, units MPD:23105   pct_NKT_8   splenic NK T cells (percentage of total viable cells)   [%]  at age age 8wks  
Data set, strains Jaxpheno6   inbred   11 strains     sex: both     age: 8wks
Procedure immune cell quantification
Ontology mappings

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

Jaxpheno6 - splenic NK T cells (percentage of total viable cells) at age age 8wks



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested11 strains11 strains
Mean of the strain means0.922   % 0.774   %
Median of the strain means0.944   % 0.706   %
SD of the strain means± 0.314 ± 0.325
Coefficient of variation (CV)0.340 0.420
Min–max range of strain means0.560   –   1.50   % 0.108   –   1.28   %
Mean sample size per strain8.9   mice 10.0   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 1.5264 1.5264 36.7033 < 0.0001
strain 10 13.3889 1.3389 32.1947 < 0.0001
sex:strain 10 4.2024 0.4202 10.1049 < 0.0001
Residuals 207 8.6086 0.0416


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
B6.129P2-Apoetm1Unc/J f 1.5 0.2   4 0.1 0.133 1.39, 1.8 1.84
B6.129P2-Apoetm1Unc/J m 1.28 0.159   5 0.071 0.124 1.06, 1.45 1.56
B6D2F1/J f 0.574 0.0902   10 0.0285 0.157 0.46, 0.7 -1.11
B6D2F1/J m 0.736 0.0802   5 0.0359 0.109 0.65, 0.82 -0.12
BALB/cByJ f 1.26 0.392   10 0.124 0.312 0.79, 1.77 1.08
BALB/cByJ m 0.897 0.316   10 0.0999 0.352 0.58, 1.61 0.38
BALB/cJ f 0.565 0.069   10 0.0218 0.122 0.45, 0.69 -1.14
BALB/cJ m 0.706 0.259   10 0.0818 0.366 0.4, 1.04 -0.21
C3H/HeJ f 0.56 0.121   5 0.0539 0.215 0.4, 0.65 -1.15
C3H/HeJ m 0.656 0.0856   5 0.0383 0.131 0.58, 0.77 -0.36
C57BL/6J f 0.977 0.249   30 0.0454 0.255 0.62, 1.53 0.17
C57BL/6J m 1.12 0.156   15 0.0402 0.139 0.9, 1.43 1.06
CBA/J f 0.883 0.249   10 0.0786 0.282 0.63, 1.4 -0.12
CBA/J m 0.704 0.141   20 0.0315 0.2 0.47, 0.94 -0.22
DBA/2J f 0.651 0.18   10 0.0568 0.276 0.43, 0.95 -0.86
DBA/2J m 0.51 0.16   15 0.0413 0.314 0.28, 0.78 -0.81
FVB/NJ f 0.944 0.125   5 0.0558 0.132 0.8, 1.09 0.07
FVB/NJ m 0.679 0.125   10 0.0396 0.185 0.46, 0.94 -0.29
NOD.CB17-Prkdcscid/J f 1.07 0.294   5 0.132 0.276 0.81, 1.53 0.47
NOD.CB17-Prkdcscid/J m 0.108 0.0618   10 0.0195 0.571 0.036, 0.23 -2.05
NOD/ShiLtJ f 1.16 0.205   15 0.053 0.177 0.69, 1.43 0.76
NOD/ShiLtJ m 1.12 0.206   10 0.0653 0.184 0.75, 1.38 1.06


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
B6.129P2-Apoetm1Unc/J f 1.5 0.102 1.701 1.299
B6.129P2-Apoetm1Unc/J m 1.276 0.0912 1.4558 1.0962
B6D2F1/J f 0.574 0.0645 0.7011 0.4469
B6D2F1/J m 0.736 0.0912 0.9158 0.5562
BALB/cByJ f 1.255 0.0645 1.3821 1.1279
BALB/cByJ m 0.897 0.0645 1.0241 0.7699
BALB/cJ f 0.565 0.0645 0.6921 0.4379
BALB/cJ m 0.706 0.0645 0.8331 0.5789
C3H/HeJ f 0.56 0.0912 0.7398 0.3802
C3H/HeJ m 0.656 0.0912 0.8358 0.4762
C57BL/6J f 0.977 0.0372 1.0504 0.9036
C57BL/6J m 1.1233 0.0527 1.2271 1.0195
CBA/J f 0.883 0.0645 1.0101 0.7559
CBA/J m 0.7035 0.0456 0.7934 0.6136
DBA/2J f 0.651 0.0645 0.7781 0.5239
DBA/2J m 0.51 0.0527 0.6138 0.4062
FVB/NJ f 0.944 0.0912 1.1238 0.7642
FVB/NJ m 0.679 0.0645 0.8061 0.5519
NOD.CB17-Prkdcscid/J f 1.066 0.0912 1.2458 0.8862
NOD.CB17-Prkdcscid/J m 0.1082 0.0645 0.2353 0.0
NOD/ShiLtJ f 1.162 0.0527 1.2658 1.0582
NOD/ShiLtJ m 1.12 0.0645 1.2471 0.9929


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
B6.129P2-Apoetm1Unc/J both 1.388 0.0684 1.5229 1.2531
B6D2F1/J both 0.655 0.0558 0.7651 0.5449
BALB/cByJ both 1.076 0.0456 1.1659 0.9861
BALB/cJ both 0.6355 0.0456 0.7254 0.5456
C3H/HeJ both 0.608 0.0645 0.7351 0.4809
C57BL/6J both 1.0502 0.0322 1.1137 0.9866
CBA/J both 0.7932 0.0395 0.8711 0.7154
DBA/2J both 0.5805 0.0416 0.6626 0.4984
FVB/NJ both 0.8115 0.0558 0.9216 0.7014
NOD.CB17-Prkdcscid/J both 0.5871 0.0558 0.6972 0.477
NOD/ShiLtJ both 1.141 0.0416 1.2231 1.0589




  GWAS USING LINEAR MIXED MODELS