Project measure / variable:   Brown1   open_prop_EPM


  STRAIN COMPARISON PLOT
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Brown1 - open arms, proportion of total time



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested14 strains13 strains
Mean of the strain means0.383   ratio 0.465   ratio
Median of the strain means0.370   ratio 0.458   ratio
SD of the strain means± 0.164 ± 0.124
Coefficient of variation (CV)0.427 0.268
Min–max range of strain means0.0610   –   0.696   ratio 0.346   –   0.672   ratio
Mean sample size per strain11.4   mice 12.7   mice


  ANOVA, Q-Q NORMALITY ASSESSMENT
ANOVA summary      
FactorDFSum of squaresMean sum of squaresF valuep value (Pr>F)
sex 1 0.1506 0.1506 5.5969 0.0186
strain 12 5.1715 0.431 16.0203 < 0.0001
sex:strain 12 0.8078 0.0673 2.5025 0.0038
Residuals 302 8.124 0.0269


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 0.468 0.171   12 0.0493 0.365 0.261, 0.808 0.52
129S1/SvImJ m 0.357 0.219   12 0.0633 0.615 0.016, 0.837 -0.87
A/J f 0.327 0.283   12 0.0817 0.865 -0.34
A/J m 0.527 0.234   17 0.0567 0.444 0.052, 0.981 0.5
AKR/J f 0.158 0.0729   12 0.0211 0.463 -1.38
AKR/J m 0.346 0.141   19 0.0323 0.407 0.037, 0.59 -0.96
BALB/cByJ f 0.696 0.163   22 0.0348 0.235 0.441, 0.96 1.91
BALB/cByJ m 0.661 0.216   12 0.0625 0.327 0.17, 0.944 1.57
BALB/cJ f 0.438 0.265   13 0.0734 0.604 0.33
BALB/cJ m 0.672 0.181   12 0.0523 0.27 0.345, 0.975 1.66
C3H/HeJ f 0.551 0.144   15 0.0373 0.262 0.2, 0.75 1.02
C3H/HeJ m 0.594 0.143   16 0.0359 0.242 0.341, 0.87 1.03
C57BL/6J f 0.289 0.122   12 0.0351 0.42 0.108, 0.457 -0.58
C57BL/6J m 0.351 0.0926   12 0.0267 0.264 0.177, 0.491 -0.92
CAST/EiJ f 0.534 0.162   5 0.0723 0.303 0.346, 0.77 0.92
CAST/EiJ m 0.512 0.102   10 0.0324 0.2 0.332, 0.633 0.38
DBA/2J f 0.276 0.215   12 0.0619 0.777 -0.65
DBA/2J m 0.347 0.117   13 0.0324 0.337 0.174, 0.558 -0.95
FVB/NJ f 0.372 0.12   12 0.0348 0.324 0.205, 0.548 -0.07
FVB/NJ m 0.353 0.113   12 0.0326 0.32 0.23, 0.562 -0.9
MOLF/EiJ f 0.369 0.108   11 0.0327 0.294 0.204, 0.551 -0.09
MOLF/EiJ m 0.349 0.122   11 0.0368 0.35 0.113, 0.615 -0.93
SJL/J f 0.344 0.0857   13 0.0238 0.249 0.212, 0.468 -0.24
SJL/J m 0.458 0.108   12 0.0313 0.237 0.316, 0.656 -0.06
SM/J f 0.482 0.0998   8 0.0353 0.207 0.306, 0.665 0.6
SM/J m 0.521 0.156   11 0.0472 0.3 0.165, 0.706 0.45
SPRET/EiJ f 0.061 0.0   1   0.0 0.0 0.061, 0.061 -1.97


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 0.4684 0.0473 0.5616 0.3752
129S1/SvImJ m 0.357 0.0473 0.4502 0.2638
A/J f 0.3272 0.0473 0.4203 0.234
A/J m 0.527 0.0398 0.6053 0.4487
AKR/J f 0.1577 0.0473 0.2508 0.0645
AKR/J m 0.3459 0.0376 0.42 0.2719
BALB/cByJ f 0.6957 0.035 0.7645 0.6269
BALB/cByJ m 0.6613 0.0473 0.7545 0.5682
BALB/cJ f 0.4382 0.0455 0.5277 0.3487
BALB/cJ m 0.6716 0.0473 0.7648 0.5784
C3H/HeJ f 0.5507 0.0423 0.6341 0.4674
C3H/HeJ m 0.5938 0.041 0.6745 0.5131
C57BL/6J f 0.2893 0.0473 0.3825 0.1962
C57BL/6J m 0.3513 0.0473 0.4445 0.2582
CAST/EiJ f 0.5338 0.0733 0.6781 0.3895
CAST/EiJ m 0.5121 0.0519 0.6142 0.41
DBA/2J f 0.2759 0.0473 0.3691 0.1827
DBA/2J m 0.3465 0.0455 0.4361 0.257
FVB/NJ f 0.3718 0.0473 0.465 0.2787
FVB/NJ m 0.3533 0.0473 0.4465 0.2602
MOLF/EiJ f 0.3687 0.0495 0.466 0.2714
MOLF/EiJ m 0.3492 0.0495 0.4465 0.2519
SJL/J f 0.3439 0.0455 0.4334 0.2544
SJL/J m 0.4577 0.0473 0.5508 0.3645
SM/J f 0.4824 0.058 0.5965 0.3683
SM/J m 0.5214 0.0495 0.6187 0.424


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 0.4127 0.0335 0.4786 0.3468
A/J both 0.4271 0.0309 0.4879 0.3662
AKR/J both 0.2518 0.0302 0.3113 0.1923
BALB/cByJ both 0.6785 0.0294 0.7364 0.6206
BALB/cJ both 0.5549 0.0328 0.6195 0.4903
C3H/HeJ both 0.5723 0.0295 0.6303 0.5143
C57BL/6J both 0.3203 0.0335 0.3862 0.2545
CAST/EiJ both 0.5229 0.0449 0.6113 0.4346
DBA/2J both 0.3112 0.0328 0.3758 0.2466
FVB/NJ both 0.3626 0.0335 0.4285 0.2967
MOLF/EiJ both 0.359 0.035 0.4278 0.2901
SJL/J both 0.4008 0.0328 0.4654 0.3362
SM/J both 0.5019 0.0381 0.5769 0.4269




  GWAS USING LINEAR MIXED MODELS