Benchmark run
2026-06-02
Quantification accuracy was not recorded for this run — the LFQBench analysis was added to the pipeline later. See the run list for runs that include it.
Per-file Results
Each of the 6 raw files, analysed independently. Mass and retention-time errors indicate calibration quality.
| File | Precursors | Proteins | MS1 error | MS2 error | RT error | FWHM (RT) |
|---|---|---|---|---|---|---|
A_R1 |
245,495 | 19,595 | 0.4061 | 9.3812 | 11.2734 | 2.8139 |
A_R2 |
242,934 | 19,454 | 0.4258 | 7.4177 | 10.3356 | 2.6484 |
A_R3 |
241,878 | 19,369 | 0.4209 | 9.2047 | 17.7345 | 2.791 |
B_R1 |
244,896 | 19,612 | 0.5372 | 7.6966 | 10.4723 | 2.6877 |
B_R2 |
244,491 | 19,589 | 0.405 | 7.7692 | 11.0345 | 2.6796 |
B_R3 |
241,472 | 19,459 | 0.4276 | 6.218 | 9.7111 | 2.5221 |
How this was measured
LFQBench is a community-standard benchmark for label-free quantification. Because the mixing ratios are fixed when the samples are prepared, the correct answer is known independently of any software — which makes it possible to measure accuracy rather than merely report output volume.
Dataset
Orbitrap Astral — 6 raw files: conditions A and B, 3 replicates each.
Ground truth
Expected log2 ratios — Human 0.0, E. coli -2.0, Yeast 1.0.
Environment
AWS g5.4xlarge, single run. Random seed fixed so the analysis is reproducible.
Scope
Measured on the main branch of the SynapSpec engine. Runtime reflects one run on shared infrastructure and will vary with hardware.