LFQBench · Orbitrap Astral AWS g5.4xlarge 9.02 h
261,656 Precursors
17,662 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 238,744 19,084 0.4036 5.8673 11.0153 2.492
A_R2 242,754 19,200 0.4213 7.6471 10.2417 2.6764
A_R3 238,836 19,010 0.4168 7.2974 16.9055 2.6477
B_R1 242,214 19,276 0.4486 7.2475 9.7104 2.6524
B_R2 242,351 19,287 0.4031 7.448 9.6634 2.6587
B_R3 244,154 19,341 0.4207 9.1618 9.687 2.8

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.