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Extract PCA Loadings and Metadata

Source: R/PCA_Functions.R
ExtractPCA.Rd

This function extracts PCA loadings stored in the DimReduction slot of a geneda object and combines them with the associated metadata. It ensures that the metadata has valid rownames and aligns the PCA loadings accordingly.

Usage

ExtractPCA(object)

Arguments

object

A geneda object containing PCA results in the DimReduction slot and sample-level metadata in the metadata slot.

Value

A data.frame combining PCA loadings and sample metadata, where rows correspond to samples and columns include principal component loadings and metadata fields.

Details

The function performs several checks:

  • Ensures the input object is of class geneda.

  • Verifies that the DimReduction slot contains PCA loadings.

  • Confirms that the metadata has valid rownames.

  • Reorders the PCA loadings to match the order of metadata rows.

If metadata rownames are missing or invalid, the function throws an error.

Examples

data(Snail1KO)
counts <- as.matrix(Snail1KO$rawCounts)
counts <- counts[rowSums(counts >= 10) >= 3, ]
meta <- Snail1KO$metadata
rownames(meta) <- meta$Sample
norm <- log2(t(t(counts) / colSums(counts)) * 1e6 + 1)
obj <- GenEDA(normalized = norm, metadata = meta, counts = counts)
obj <- FindVariableFeatures(obj, nfeatures = 1000)
obj <- RunPCA(obj)
#> Calculating principal components from top 1000 HVGs
#> Percent variations:
#> PC1: 88.56 %
#> PC2: 5.9 %
#> PC3: 2.91 %
#> PC4: 1.55 %
#> PC5: 1.08 %
#> PC6: 0 %
pca_df <- ExtractPCA(obj)
head(pca_df[, c("PC1", "PC2", "Genotype")])
#>                  PC1         PC2 Genotype
#> ERR1736465 -26.51610   8.8812248       WT
#> ERR1736466 -29.45724 -14.1901804       WT
#> ERR1736467 -28.65501   5.8971266       WT
#> ERR1736468  27.63783  -1.0411693 Snai1_KO
#> ERR1736469  27.39885  -0.8413095 Snai1_KO
#> ERR1736470  29.59167   1.2943077 Snai1_KO