LFQBench · Orbitrap Astral AWS g5.4xlarge 9.7 h
223,062 Precursors
13,200 Protein groups
6 Raw files analysed

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 191,286 13,682 0.4599 12.8804 70.7773 3.1745
A_R2 189,188 13,700 0.4651 12.9333 71.2301 3.1345
A_R3 194,118 13,737 0.4576 12.3493 55.6807 3.1081
B_R1 193,790 13,892 0.5368 13.0432 64.4511 3.1665
B_R2 185,003 13,837 0.458 8.4606 55.6861 2.9413
B_R3 185,076 13,820 0.4838 10.0335 62.8471 2.993

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.