Valencia 1k four-component hypercube embedding example

A stratified 1,000-sample subset of the Valencia 13k vaginal microbiome training set, reduced to four selected phylotype coordinates and L1-normalized over those coordinates. The object is bundled as a lightweight example for the zero-aware homogeneous-coordinate hypercube embedding in linf.hypercube.embedding.

Usage

valencia_linf_hypercube_1k

Format

A list with four components:

rel4

Numeric matrix (1000 x 4). Rows are samples and columns are Li, Lc, Gv, and Bv. Each row sums to 1 after restricting the original Valencia profile to the four mapped taxa.

meta

Data frame (1000 rows) with columns: sample_id (anonymized bundled-data identifier), source_row (row number in the filtered Valencia 13k source), Val_CST, Val_subCST, selected_mass (original relative-abundance mass carried by the four selected taxa), and dominant_component (largest of Li, Lc, Gv, Bv after renormalization).

component_map

Named character vector mapping Li, Lc, Gv, and Bv to the original Valencia taxon names: Lactobacillus_iners, Lactobacillus_crispatus, Gardnerella_vaginalis, and BVAB1.

source

Character string documenting provenance.

Source

Generated from the VALENCIA training data at https://github.com/ravel-lab/VALENCIA. See data-raw/build_valencia_linf_hypercube_1k.R and the installed DATA_PROVENANCE.md file.

Details

Rows with zero total mass in the four selected taxa are removed before renormalization. Sampling is stratified by the dominant selected component, using set.seed(20261604). The object is not intended to replace the full Valencia matrix; it is a compact reproducible example for visualizing compositional projective-space coordinate charts.

Examples

data(valencia_linf_hypercube_1k)
dim(valencia_linf_hypercube_1k$rel4)
#> [1] 1000    4
table(valencia_linf_hypercube_1k$meta$dominant_component)
#> 
#>  Li  Lc  Gv  Bv 
#> 366 321 257  56 
emb <- linf.hypercube.embedding(
  valencia_linf_hypercube_1k$rel4,
  reference = "Li"
)
dim(emb)
#> [1] 1000    3