A stratified subsample of 2,000 vaginal samples from the Valencia 13k CST-classifier training set (France et al. 2020), bundled as an example dataset for demonstrating dCST construction after L-infinity normalization.
Format
A list with five components:
- rel
Numeric matrix (2000 x 178). Compositional relative abundances; each row sums to 1. Rows are samples, columns are taxonomic features.
- cst
Data frame (2000 x 3) with columns:
sample_id(character),Val_CST(Valencia CST assignment: I, II, III, IV-A, IV-B, IV-C, V),Val_subCST(Valencia sub-CST assignment: I-A, I-B, II, III-A, III-B, IV-A, IV-B, IV-C0, IV-C1, IV-C2, IV-C3, IV-C4, V).- reads
Integer vector of length 2000. Per-sample read counts after taxonomic filtering. Use
sweep(valencia2k$rel, 1, valencia2k$reads, "*")to reconstruct a count-like matrix.- taxa
Character vector of 178 taxon names (column names of
rel).- source
Character string documenting provenance.
Source
Subsampled from the VALENCIA training data at
https://github.com/ravel-lab/VALENCIA. See
data-raw/build_valencia2k.R and the installed
DATA_PROVENANCE.md file for construction and licensing details.
Details
The subsample preserves proportional representation of all 13 Valencia
sub-CSTs and was drawn with set.seed(42).
The Valencia CST classifier (France et al. 2020) assigns vaginal microbiome samples to community state types (CSTs) based on nearest-centroid classification in relative-abundance space. The original training set contains 12,881 samples and 178 taxonomic features after filtering.
This 2,000-sample subsample is intended for vignette demonstrations. The
compositional matrix can be used directly with normalize.linf
and downstream dCST functions. For workflows that require count-like input,
reconstruct approximate counts using the reads vector.
References
France, M. T., Ma, B., Gajer, P., Brown, S., Humphrys, M. S., Holm, J. B., Waetjen, L. E., Brotman, R. M., & Ravel, J. (2020). VALENCIA: a nearest centroid classification method for vaginal microbial communities based on composition. Microbiome, 8(1), 166. doi:10.1186/s40168-020-00934-6
Examples
data(valencia2k)
dim(valencia2k$rel) # 2000 x 178
#> [1] 2000 178
table(valencia2k$cst$Val_CST) # CST distribution
#>
#> I II III IV-A IV-B IV-C V
#> 557 69 582 141 454 117 80
head(valencia2k$taxa, 10) # first 10 taxon names
#> [1] "Lactobacillus_iners" "Lactobacillus_crispatus"
#> [3] "Gardnerella_vaginalis" "Lactobacillus_jensenii"
#> [5] "Lactobacillus_gasseri" "Atopobium_vaginae"
#> [7] "BVAB1" "Sneathia_sanguinegens"
#> [9] "g_Megasphaera" "g_Streptococcus"