Phenotype data for scWAT samples from the MoTrPAC endurance exercise training study in 6-month-old-rats: NMR body composition and VO\(_2\)max testing results.

PHENO_WAT

Format

An object of class data.frame with 92 rows and 21 columns.

Examples

head(PHENO_WAT)
#>        pid iowa_id omics_analysis    sex timepoint pre_weight vo2_pre_weight
#> 1 10043527  06F8T1           TRUE Female       SED      181.2          178.3
#> 2 10043799  06F8T3          FALSE Female       SED      179.0          182.8
#> 3 10043950  06F8T4           TRUE Female       SED      174.4          178.2
#> 4 10044094  06F8T5          FALSE Female       SED      181.2          182.0
#> 5 10044337  06F8T8           TRUE Female       SED      185.2          182.4
#> 6 10044418  06F8T9          FALSE Female       SED      178.3          174.5
#>   vo2_post_weight post_weight pre_fat pre_fat_pct post_fat post_fat_pct
#> 1           199.2         199 20.2944        11.2  21.2004         11.7
#> 2           203.0         203 19.1530        10.7  25.4180         14.2
#> 3           202.3         202 19.1840        11.0  27.0320         15.5
#> 4           190.4         190 20.4756        11.3  24.6432         13.6
#> 5           204.6         205 21.2980        11.5  27.5948         14.9
#> 6           190.8         191 20.1479        11.3  24.4271         13.7
#>   pre_lean pre_lean_pct post_lean post_lean_pct pre_vo2max_ml_kg_min
#> 1 109.2636         60.3  107.9952          59.6                 83.8
#> 2 105.9680         59.2   99.7030          55.7                 71.7
#> 3 103.2448         59.2   96.9664          55.6                 72.5
#> 4 105.4584         58.2  103.8276          57.3                 69.7
#> 5 108.8976         58.8  101.4896          54.8                 69.6
#> 6 104.1272         58.4  102.7008          57.6                 77.6
#>   post_vo2max_ml_kg_min pre_vo2max_ml_kg_lean_min post_vo2max_ml_kg_lean_min
#> 1                 73.16                  136.7476                   134.9456
#> 2                 63.77                  123.6860                   129.8387
#> 3                 64.63                  125.1346                   134.8369
#> 4                 61.85                  120.2882                   113.4211
#> 5                 73.52                  116.5778                   148.2141
#> 6                 63.65                  130.0448                   118.2505