Project measure / variable:   Brown1   close_prop_EPM


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



  MEASURE SUMMARY
Measure Summary FemaleMale
Number of strains tested14 strains13 strains
Mean of the strain means0.412   ratio 0.322   ratio
Median of the strain means0.391   ratio 0.350   ratio
SD of the strain means± 0.204 ± 0.118
Coefficient of variation (CV)0.497 0.368
Min–max range of strain means0.143   –   0.872   ratio 0.127   –   0.470   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 0.1525 0.1525 6.5298 0.0111
strain 12 5.3298 0.4442 19.0211 < 0.0001
sex:strain 12 1.0567 0.0881 3.7713 < 0.0001
Residuals 302 7.0518 0.0234


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 0.244 0.128   12 0.0369 0.524 0.008, 0.419 -0.82
129S1/SvImJ m 0.35 0.177   12 0.051 0.506 0.019, 0.506 0.24
A/J f 0.424 0.241   12 0.0697 0.57 0.06
A/J m 0.247 0.188   17 0.0457 0.763 -0.63
AKR/J f 0.732 0.121   12 0.0349 0.165 0.541, 0.971 1.57
AKR/J m 0.47 0.178   19 0.0408 0.379 0.224, 0.838 1.25
BALB/cByJ f 0.143 0.143   22 0.0305 1.0 -1.31
BALB/cByJ m 0.181 0.214   12 0.0617 1.18 -1.19
BALB/cJ f 0.385 0.249   13 0.069 0.647 0.048, 0.847 -0.13
BALB/cJ m 0.127 0.135   12 0.0389 1.06 -1.65
C3H/HeJ f 0.243 0.112   15 0.029 0.462 0.11, 0.51 -0.82
C3H/HeJ m 0.226 0.114   16 0.0285 0.505 0.01, 0.465 -0.81
C57BL/6J f 0.47 0.135   12 0.0388 0.286 0.24, 0.695 0.29
C57BL/6J m 0.431 0.0866   12 0.025 0.201 0.321, 0.601 0.92
CAST/EiJ f 0.273 0.147   5 0.0658 0.54 0.098, 0.482 -0.68
CAST/EiJ m 0.263 0.0643   10 0.0203 0.244 0.184, 0.367 -0.5
DBA/2J f 0.576 0.257   12 0.0743 0.447 0.06, 0.933 0.81
DBA/2J m 0.46 0.131   13 0.0364 0.285 0.194, 0.609 1.17
FVB/NJ f 0.397 0.107   12 0.0309 0.27 0.212, 0.544 -0.07
FVB/NJ m 0.412 0.0789   12 0.0228 0.192 0.264, 0.507 0.76
MOLF/EiJ f 0.383 0.143   11 0.0431 0.373 0.193, 0.607 -0.14
MOLF/EiJ m 0.437 0.117   11 0.0353 0.268 0.256, 0.725 0.97
SJL/J f 0.426 0.111   13 0.0306 0.259 0.265, 0.635 0.07
SJL/J m 0.378 0.0822   12 0.0237 0.218 0.226, 0.501 0.47
SM/J f 0.193 0.102   8 0.0359 0.526 0.058, 0.358 -1.07
SM/J m 0.203 0.131   11 0.0395 0.645 0.034, 0.431 -1.0
SPRET/EiJ f 0.872 0.0   1   0.0 0.0 0.872, 0.872 2.25


  LEAST SQUARES MEANS (MODEL-ADJUSTED)
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ f 0.2439 0.0441 0.3307 0.1571
129S1/SvImJ m 0.3496 0.0441 0.4364 0.2628
A/J f 0.4239 0.0441 0.5107 0.3371
A/J m 0.247 0.0371 0.3199 0.1741
AKR/J f 0.7324 0.0441 0.8192 0.6456
AKR/J m 0.4703 0.0351 0.5393 0.4013
BALB/cByJ f 0.1425 0.0326 0.2067 0.0784
BALB/cByJ m 0.1813 0.0441 0.2681 0.0945
BALB/cJ f 0.3846 0.0424 0.468 0.3012
BALB/cJ m 0.1265 0.0441 0.2133 0.0397
C3H/HeJ f 0.2433 0.0395 0.3209 0.1656
C3H/HeJ m 0.2262 0.0382 0.3014 0.1511
C57BL/6J f 0.4701 0.0441 0.5569 0.3833
C57BL/6J m 0.4313 0.0441 0.5181 0.3445
CAST/EiJ f 0.2726 0.0683 0.4071 0.1381
CAST/EiJ m 0.2634 0.0483 0.3585 0.1683
DBA/2J f 0.5762 0.0441 0.6631 0.4894
DBA/2J m 0.4601 0.0424 0.5435 0.3767
FVB/NJ f 0.3965 0.0441 0.4833 0.3097
FVB/NJ m 0.4117 0.0441 0.4985 0.3249
MOLF/EiJ f 0.3826 0.0461 0.4733 0.292
MOLF/EiJ m 0.4371 0.0461 0.5278 0.3464
SJL/J f 0.426 0.0424 0.5094 0.3426
SJL/J m 0.3776 0.0441 0.4644 0.2908
SM/J f 0.1931 0.054 0.2994 0.0868
SM/J m 0.2032 0.0461 0.2938 0.1125


  LEAST SQUARES MEANS (MODEL-ADJUSTED), SEXES COMBINED
Strain Sex Mean SEM UpperCL LowerCL
129S1/SvImJ both 0.2968 0.0312 0.3581 0.2354
A/J both 0.3355 0.0288 0.3921 0.2788
AKR/J both 0.6014 0.0282 0.6568 0.5459
BALB/cByJ both 0.1619 0.0274 0.2159 0.108
BALB/cJ both 0.2556 0.0306 0.3157 0.1954
C3H/HeJ both 0.2348 0.0275 0.2888 0.1807
C57BL/6J both 0.4507 0.0312 0.5121 0.3893
CAST/EiJ both 0.268 0.0418 0.3504 0.1856
DBA/2J both 0.5182 0.0306 0.5784 0.458
FVB/NJ both 0.4041 0.0312 0.4655 0.3427
MOLF/EiJ both 0.4099 0.0326 0.474 0.3458
SJL/J both 0.4018 0.0306 0.462 0.3416
SM/J both 0.1982 0.0355 0.268 0.1283




  GWAS USING LINEAR MIXED MODELS