Datasets
The suite reuses the count matrices and sample definitions from the
archived ComBat-ref implementation. GFRN retains 47 samples across six
biological signatures. The NASA collection combines mouse liver studies
OSD/GLDS 47, 48, 137, 173, 242, and 245; GLDS-168 is excluded to match
the ComBat-ref analysis. Condition is the protected biological factor
and study-mission is the batch. The source files are pinned to
ComBat-ref commit
f0c6d3f313e9f1f29de2c8c8f12b98113443be55.
The NASA design follows Sanders et al. (2023), who identified mission and library preparation as major technical variables in seven combined GeneLab mouse-liver RNA-seq datasets (doi:10.3389/fspas.2023.1200132).
Reproduce
system("Rscript validation/run_all.R")
metrics <- read.delim("validation/real_data_metrics.tsv")
metricsResults
| Dataset | Conditional batch R2, raw -> adjusted | Mean-alignment RMSE, raw -> adjusted | Residual variance alignment, raw -> adjusted |
|---|---|---|---|
| GFRN | 0.54941 -> 0.03111 | 1.19145 -> 0.08128 | 0.27014 -> 0.17773 |
| NASA GeneLab | 0.83903 -> 0.10079 | 1.38250 -> 0.19178 | 0.53028 -> 0.09293 |
validation/run_all.R checks these regression anchors
directly against the TSV output. Reference counts are exactly invariant
in both datasets, and the TSV also records retained samples/genes,
outcomes, reference batch, and transformation magnitude.
For all three diagnostics, smaller values indicate closer cross-batch alignment after conditioning on biology. The table reports both raw and adjusted values; the adjusted values remain regression anchors. Residual logCPM variance alignment is descriptive, not negative-binomial dispersion. Neither dataset provides uniform biological ground truth, so the suite tests alignment and invariants rather than claiming biological superiority.
Related methods
ComBat-refQL is derived from ComBat-ref (doi:10.1016/j.csbj.2024.12.010). ComBat-seq is the established negative-binomial count-scale comparator (doi:10.1093/nargab/lqaa078). The current regression suite evaluates ComBat-refQL itself; it does not present a head-to-head benchmark.