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Impute missing values using Singular Value Decomposition (SVD)

Source: R/imputes.R
impute_svd.Rd

Basically a wrapper around pcaMethods::pca(method = "svdImpute"). For a detailed discussion, see the vignette("pcaMethods") and vignette("missingValues", "pcaMethods") as well as the References section.

Important Note impute_svd() depends on the pcaMethods package from Bioconductor. If metamorphr was installed via install.packages(), dependencies from Bioconductor were not automatically installed. When impute_svd() is called without the pcaMethods package installed, you should be asked if you want to install pak and pcaMethods. If you want to use impute_svd() you have to install those. In case you run into trouble with the automatic installation, please install pcaMethods manually. See pcaMethods – a Bioconductor package providing PCA methods for incomplete data for instructions on manual installation.

Usage

impute_svd(data, n_pcs = 2, center = TRUE, scale = "none", direction = 2)

Arguments

data

A tidy tibble created by read_featuretable.

n_pcs

The number of PCs to calculate.

center

Should data be mean centered? See prep for details.

scale

Should data be scaled? See prep for details.

direction

Either 1 or 2. 1 runs pcaMethods::pca(method = "svdImpute") on a matrix with samples in columns and features in rows and 2 runs pcaMethods::pca(method = "svdImpute") on a matrix with features in columns and samples in rows. Both are valid according to this discussion on GitHub but give different results.

Value

A tibble with imputed missing values.

References

  • H. R. Wolfram Stacklies, 2017, DOI 10.18129/B9.BIOC.PCAMETHODS.

  • W. Stacklies, H. Redestig, M. Scholz, D. Walther, J. Selbig, Bioinformatics 2007, 23, 1164–1167, DOI 10.1093/bioinformatics/btm069.

  • O. Troyanskaya, M. Cantor, G. Sherlock, P. Brown, T. Hastie, R. Tibshirani, D. Botstein, R. B. Altman, Bioinformatics 2001, 17, 520–525, DOI 10.1093/bioinformatics/17.6.520.

Examples

toy_metaboscape %>%
  impute_svd()
#> # 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      4     0.45  162. NA         C7H15N…
#>  2     2 276.13647 Da 27.28 s   Sample1      3     0.45  277. Octyl hyd… C16H22…
#>  3     3 304.24023 Da 32.86 s   Sample1      4.61  0.55  305. Arachidon… C20H32…
#>  4     4 417.23236 Da 60.08 s   Sample1      5     1     418. NA         NA     
#>  5     5 104.10753 Da 170.31 s  Sample1      5     2.84  105. NA         C5H14NO
#>  6     6 105.04259 Da 199.80 s  Sample1      5     3.33  106. NA         C3H8NO3
#>  7     7 237.09204 Da 313.24 s  Sample1      8.12  5.22  238. Ketamine   C13H16…
#>  8     8 745.09111 Da 382.23 s  Sample1      3     6.37  746. NADPH      C21H30…
#>  9     9 427.02942 Da 424.84 s  Sample1      4     7.08  428. ADP        C10H15…
#> 10    10 1284.34904 Da 498.94 s Sample1      3.61  8.32 1285. NA         NA     
#> # ℹ 100 more rows