BgnormResult S3 class — BgnormResult • bgnormR

A lightweight list-based S3 class returned by bgnorm_pixels (per channel, via bgnorm_results) and bgnorm_cells.

Value

Not applicable; documents the BgnormResult class structure.

parameters: List with elements means, sds, props.
n: Integer; total number of input observations (pixels or cells, including zeros) for this channel.
threshold: For the 3-component (pixel-level) model: a single numeric scalar giving the maximum adjusted intensity of Non-specific pixels. Combined with the implicit class-1 boundary at 0, this encodes the full classification: adj == 0 -> Background; 0 < adj <= threshold -> Non-specific; adj > threshold -> Signal. NULL for 2-component models (cell-level or no-signal fallback), where the only boundary is 0 (adjusted > 0 -> Signal).
jsd: Jensen-Shannon Divergence QC metric between components 2 and 3. NA_real_ for no-signal channels.
level: "pixel" or "cell".
quantile_norm: Logical; whether quantile normalisation was applied.
histogram: List with $breaks and $density vectors from a pre-computed histogram of log2-transformed intensities. Used by plot_distributions.
no_signal: Logical; TRUE when the 3-component GMM failed and the channel was fitted with a 2-component fallback, indicating no detectable biological signal.
bic: Named numeric vector c(G2 = ..., G3 = ...) with mclust BIC values (higher is better in mclust's convention) divided by the number of points used to fit, giving a point-specific estimate comparable across channels regardless of sample size. NULL for cell-level results.