| Type: | Package |
| Title: | Bayesian Quantification of Evidence Sufficiency |
| Version: | 0.1.0 |
| License: | MIT + file LICENSE |
| Language: | en-GB |
| Description: | Implements the Quantification Evidence Standard algorithm for computing Bayesian evidence sufficiency from binary evidence matrices. It provides posterior estimates, credible intervals, percentiles, and optional visual summaries. The method is universal, reproducible, and independent of any specific clinical or rule based framework. For details see The Quantitative Omics Epidemiology Group et al. (2025) <doi:10.64898/2025.12.02.25341503>. |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Depends: | R (≥ 4.1) |
| Imports: | ggplot2, tibble, dplyr, tidyr, purrr, stats, grDevices |
| Suggests: | knitr, rmarkdown, tidyverse |
| LazyData: | true |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2025-12-12 10:29:44 UTC; akira |
| Author: | Dylan Lawless |
| Maintainer: | Dylan Lawless <admin@switzerlandomics.ch> |
| Repository: | CRAN |
| Date/Publication: | 2025-12-18 14:00:02 UTC |
Example binary evidence dataset for Quant ES
Description
Demonstration dataset used in vignettes and examples.
Usage
data(core_test_data)
Format
A data frame with 50 variants and 12 binary evidence columns.
QuantBayES Universal Bayesian Evidence Sufficiency Scoring
Description
Computes posterior theta, credible intervals and percentiles for each variant given a binary evidence matrix.
Usage
quant_es_core(x, a = 1, b = 1, ci_level = 0.95)
Arguments
x |
matrix of 0 and 1, rows are variants and columns are evidence rules. |
a |
prior alpha parameter. |
b |
prior beta parameter. |
ci_level |
credible interval width. |
Value
A list with:
- variants
Data frame of per variant scores.
- global
Summary list of global posterior distribution.
Read a flat binary table and run quant_es_core
Description
Reads a TSV, CSV or other delimited file where:
the first column is a variant identifier (unless removed)
remaining columns contain binary 0, 1, or NA evidence indicators.
Usage
quant_es_from_binary_table(
path,
sep = "\t",
header = TRUE,
variant_col = NULL
)
Arguments
path |
Path to a text file. |
sep |
Field separator (default tab). |
header |
Whether the file has a header. |
variant_col |
Column name containing the variant IDs. If NULL and no such column exists, sequential IDs will be created. |
Value
A standard quantbayes result list.
Examples
tmp <- tempfile(fileext = ".tsv")
write.table(core_test_data, tmp, sep = "\t", quote = FALSE, row.names = FALSE)
res <- quant_es_from_binary_table(tmp)
res$global
quantbayes plotting utilities
Description
Produces diagnostic plots: global density, overlay density, evidence matrix, p_hat, and theta credible intervals.
Usage
quant_es_plots(
res,
x_matrix,
top_n = 20,
top_overlay = 10,
highlight_points = NULL,
palette10 = (grDevices::colorRampPalette(c("#2f4356", "#656d87", "#f1e1d4", "#ffbf00",
"#ee4035")))(10),
palette20 = (grDevices::colorRampPalette(c("#656d87", "#2f4356")))(20)
)
Arguments
res |
Result from quant_es_core. |
x_matrix |
Evidence matrix used for the run. |
top_n |
Number of variants for matrix and summary plots. |
top_overlay |
Number of top variants used in overlay density. |
highlight_points |
Optional list of highlighted variants. |
palette10 |
Colour palette for overlay density lines. |
palette20 |
Colour palette for p_hat plot. |
Value
A list of ggplot objects.