norm_CSS | R Documentation |
Calculate normalization factors from a phyloseq or TreeSummarizedExperiment
object. Inherited from metagenomeSeq
calcNormFactors
function which performs the
Cumulative Sum Scaling normalization.
norm_CSS(object, assay_name = "counts", method = "CSS", verbose = TRUE)
object |
a phyloseq or TreeSummarizedExperiment object. |
assay_name |
the name of the assay to extract from the
TreeSummarizedExperiment object (default |
method |
normalization method to be used (only CSS). |
verbose |
an optional logical value. If |
A new column containing the CSS normalization factors is added to
the sample_data
slot of the phyloseq object or the colData
slot of the TreeSummarizedExperiment object.
calcNormFactors
for details.
setNormalizations
and runNormalizations
to fastly
set and run normalizations.
set.seed(1) # Create a very simple phyloseq object counts <- matrix(rnbinom(n = 60, size = 3, prob = 0.5), nrow = 10, ncol = 6) metadata <- data.frame("Sample" = c("S1", "S2", "S3", "S4", "S5", "S6"), "group" = as.factor(c("A", "A", "A", "B", "B", "B"))) ps <- phyloseq::phyloseq(phyloseq::otu_table(counts, taxa_are_rows = TRUE), phyloseq::sample_data(metadata)) # Calculate the normalization factors ps_NF <- norm_CSS(object = ps, method = "CSS") # The phyloseq object now contains the normalization factors: CSSFacts <- phyloseq::sample_data(ps_NF)[, "NF.CSS"] head(CSSFacts) # VERY IMPORTANT: metagenomeSeq uses scaling factors to normalize counts # (even though they are called normalization factors). These factors are used # internally by a regression model. To make CSS size factors available for # edgeR, we need to transform them into normalization factors. This is # possible by dividing the factors for the library sizes and renormalizing. normCSSFacts = CSSFacts / colSums(phyloseq::otu_table(ps_stool_16S)) # Renormalize: multiply to 1 normFacts = normCSSFacts/exp(colMeans(log(normCSSFacts)))
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