hd_log_transform() log transforms the data in a dataset.
It replaces non-positive values (<= 0) with NA values and informs the user.
Examples
# Create the HDAnalyzeR object providing the data and metadata
hd_object <- hd_initialize(example_data, example_metadata)
hd_object$data
#> # A tibble: 586 × 101
#> DAid AARSD1 ABL1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACP6 ACTA2
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 DA00001 3.39 2.76 1.71 0.0333 1.76 -0.919 1.54 2.15 2.81
#> 2 DA00002 1.42 1.25 -0.816 -0.459 0.826 -0.902 0.647 1.30 0.798
#> 3 DA00003 NA NA NA 0.989 NA 0.330 1.37 NA NA
#> 4 DA00004 3.41 3.38 1.69 NA 1.52 NA 0.841 0.582 1.70
#> 5 DA00005 5.01 5.05 0.128 0.401 -0.933 -0.584 0.0265 1.16 2.73
#> 6 DA00006 6.83 1.18 -1.74 -0.156 1.53 -0.721 0.620 0.527 0.772
#> 7 DA00007 NA NA 3.96 0.682 3.14 2.62 1.47 2.25 2.01
#> 8 DA00008 2.78 0.812 -0.552 0.982 -0.101 -0.304 0.376 -0.826 1.52
#> 9 DA00009 4.39 3.34 -0.452 -0.868 0.395 1.71 1.49 -0.0285 0.200
#> 10 DA00010 1.83 1.21 -0.912 -1.04 -0.0918 -0.304 1.69 0.0920 2.04
#> # ℹ 576 more rows
#> # ℹ 91 more variables: ACTN4 <dbl>, ACY1 <dbl>, ADA <dbl>, ADA2 <dbl>,
#> # ADAM15 <dbl>, ADAM23 <dbl>, ADAM8 <dbl>, ADAMTS13 <dbl>, ADAMTS15 <dbl>,
#> # ADAMTS16 <dbl>, ADAMTS8 <dbl>, ADCYAP1R1 <dbl>, ADGRE2 <dbl>, ADGRE5 <dbl>,
#> # ADGRG1 <dbl>, ADGRG2 <dbl>, ADH4 <dbl>, ADM <dbl>, AGER <dbl>, AGR2 <dbl>,
#> # AGR3 <dbl>, AGRN <dbl>, AGRP <dbl>, AGXT <dbl>, AHCY <dbl>, AHSP <dbl>,
#> # AIF1 <dbl>, AIFM1 <dbl>, AK1 <dbl>, AKR1B1 <dbl>, AKR1C4 <dbl>, …
# Log transform the data
hd_object_transformed <- hd_log_transform(hd_object)
#> Warning: Data contains non-positive values (<= 0). These will be replaced with NA during log transformation.
# Normally you should not transform Olink data as they are already log-transformed
hd_object_transformed$data
#> # A tibble: 586 × 101
#> DAid AARSD1 ABL1 ACAA1 ACAN ACE2 ACOX1 ACP5 ACP6 ACTA2 ACTN4
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 DA000… 1.76 1.46 0.771 -4.91 0.812 NA 0.620 1.11 1.49 -0.431
#> 2 DA000… 0.509 0.319 NA NA -0.275 NA -0.628 0.379 -0.325 NA
#> 3 DA000… NA NA NA -0.0155 NA -1.60 0.456 NA NA NA
#> 4 DA000… 1.77 1.76 0.759 NA 0.605 NA -0.250 -0.781 0.766 -3.21
#> 5 DA000… 2.33 2.34 -2.97 -1.32 NA NA -5.24 0.210 1.45 -1.51
#> 6 DA000… 2.77 0.242 NA NA 0.611 NA -0.690 -0.925 -0.374 NA
#> 7 DA000… NA NA 1.99 -0.551 1.65 1.39 0.559 1.17 1.01 -2.56
#> 8 DA000… 1.48 -0.301 NA -0.0269 NA NA -1.41 NA 0.605 NA
#> 9 DA000… 2.14 1.74 NA NA -1.34 0.771 0.573 NA -2.32 NA
#> 10 DA000… 0.871 0.280 NA NA NA NA 0.757 -3.44 1.03 -0.997
#> # ℹ 576 more rows
#> # ℹ 90 more variables: ACY1 <dbl>, ADA <dbl>, ADA2 <dbl>, ADAM15 <dbl>,
#> # ADAM23 <dbl>, ADAM8 <dbl>, ADAMTS13 <dbl>, ADAMTS15 <dbl>, ADAMTS16 <dbl>,
#> # ADAMTS8 <dbl>, ADCYAP1R1 <dbl>, ADGRE2 <dbl>, ADGRE5 <dbl>, ADGRG1 <dbl>,
#> # ADGRG2 <dbl>, ADH4 <dbl>, ADM <dbl>, AGER <dbl>, AGR2 <dbl>, AGR3 <dbl>,
#> # AGRN <dbl>, AGRP <dbl>, AGXT <dbl>, AHCY <dbl>, AHSP <dbl>, AIF1 <dbl>,
#> # AIFM1 <dbl>, AK1 <dbl>, AKR1B1 <dbl>, AKR1C4 <dbl>, AKT1S1 <dbl>, …