Scales the intensities of all features using
$$\widetilde{x}_{ij}=\frac{x_{ij}-\overline{x}_{i}}{\sqrt{s_i}}$$
where \(\widetilde{x}_{ij}\) is the intensity of sample \(j\), feature \(i\) after scaling, \(x_{ij}\) is the intensity of sample \(j\), feature \(i\) before scaling, \(\overline{x}_{i}\) is the mean of intensities of feature \(i\) across all samples and \({\sqrt{s_i}}\) is the square root of the standard deviation of intensities of feature \(i\) across all samples. In other words, it subtracts the mean intensity of a feature across samples from the intensities of that feature in each sample and divides by the square root of the standard deviation of that feature. For more information, see the reference section.
Arguments
- data
A tidy tibble created by
read_featuretable.
References
R. A. Van Den Berg, H. C. Hoefsloot, J. A. Westerhuis, A. K. Smilde, M. J. Van Der Werf, BMC Genomics 2006, 7, 142, DOI 10.1186/1471-2164-7-142.
Examples
toy_metaboscape %>%
scale_pareto()
#> # A tibble: 110 × 8
#> UID Feature Sample Intensity RT `m/z` Name Formula
#> <int> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr>
#> 1 1 161.10519 Da 26.98 s Sample1 -0.983 0.45 162. NA C7H15N…
#> 2 2 276.13647 Da 27.28 s Sample1 -1.15 0.45 277. Octyl hyd… C16H22…
#> 3 3 304.24023 Da 32.86 s Sample1 NA 0.55 305. Arachidon… C20H32…
#> 4 4 417.23236 Da 60.08 s Sample1 -0.563 1 418. NA NA
#> 5 5 104.10753 Da 170.31 s Sample1 -0.337 2.84 105. NA C5H14NO
#> 6 6 105.04259 Da 199.80 s Sample1 0.213 3.33 106. NA C3H8NO3
#> 7 7 237.09204 Da 313.24 s Sample1 NA 5.22 238. Ketamine C13H16…
#> 8 8 745.09111 Da 382.23 s Sample1 -0.156 6.37 746. NADPH C21H30…
#> 9 9 427.02942 Da 424.84 s Sample1 -0.607 7.08 428. ADP C10H15…
#> 10 10 1284.34904 Da 498.94 s Sample1 NA 8.32 1285. NA NA
#> # ℹ 100 more rows