DIA-NN 1.8.1 (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 15 2022 08:45:18
Current date and time: Tue Aug  4 14:24:34 2026
Logical CPU cores: 128
/usr/diann/1.8.1/diann --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML --f /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/report.tsv --temp /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1 --threads 100 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 380 --max-pr-mz 980 --min-fr-mz 150 --max-fr-mz 2000 --cut K*,R* --gen-spec-lib --predictor --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 100
Maximum number of missed cleavages set to 1
Min peptide length set to 6
Max peptide length set to 30
Output will be filtered at 0.01 FDR
Output will be filtered at 0.01 protein-level FDR
Min precursor charge set to 1
Max precursor charge set to 5
Min precursor m/z set to 380
Max precursor m/z set to 980
Min fragment m/z set to 150
Max fragment m/z set to 2000
In silico digest will involve cuts at K*,R*
A spectral library will be generated
Deep learning will be used to generate a new in silico spectral library from peptides provided
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Maximum number of variable modifications set to 1
A spectral library will be generated
Library-free search enabled
A spectral library will be created from the DIA runs and used to reanalyse them; .quant files will only be saved to disk during the first step
DIA-NN will optimise the mass accuracy automatically using the first run in the experiment. This is useful primarily for quick initial analyses, when it is not yet known which mass accuracy setting works best for a particular acquisition scheme.
Exclusion of fragments shared between heavy and light peptides from quantification is not supported in FASTA digest mode - disabled; to enable, generate an in silico predicted spectral library and analyse with this library

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:09] Processing FASTA
[0:21] Assembling elution groups
[0:32] 4807588 precursors generated
[0:32] Protein names missing for some isoforms
[0:32] Gene names missing for some isoforms
[0:32] Library contains 31676 proteins, and 0 genes
[0:38] [0:56] [36:45] [39:09] [39:18] [39:22] Saving the library to lib.predicted.speclib
Could not save lib.predicted.speclib
[39:22] Initialising library

[39:26] First pass: generating a spectral library from DIA data
[39:26] File #1/6
[39:26] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML
[41:59] 4804019 library precursors are potentially detectable
[42:00] Processing...
[43:20] RT window set to 1.11033
[43:20] Peak width: 2.844
[43:20] Scan window radius set to 6
[43:21] Recommended MS1 mass accuracy setting: 2.60133 ppm
[45:14] Optimised mass accuracy: 6.20342 ppm
[48:29] Removing low confidence identifications
[48:29] Removing interfering precursors
[48:42] Training neural networks: 208112 targets, 143454 decoys
[48:53] Number of IDs at 0.01 FDR: 97615
[48:55] Calculating protein q-values
[48:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[48:55] Quantification
[48:58] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_mzML.quant.

[48:59] File #2/6
[48:59] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML
[54:23] 4804019 library precursors are potentially detectable
[54:23] Processing...
[55:58] RT window set to 1.08364
[55:58] Recommended MS1 mass accuracy setting: 2.55419 ppm
[59:38] Removing low confidence identifications
[59:39] Removing interfering precursors
[59:49] Training neural networks: 216285 targets, 144812 decoys
[60:00] Number of IDs at 0.01 FDR: 100250
[60:01] Calculating protein q-values
[60:01] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[60:01] Quantification
[60:04] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_mzML.quant.

[60:05] File #3/6
[60:05] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML
[64:40] 4804019 library precursors are potentially detectable
[64:40] Processing...
[66:20] RT window set to 1.16101
[66:21] Recommended MS1 mass accuracy setting: 2.75764 ppm
[70:24] Removing low confidence identifications
[70:24] Removing interfering precursors
[70:35] Training neural networks: 214466 targets, 146234 decoys
[70:47] Number of IDs at 0.01 FDR: 101804
[70:48] Calculating protein q-values
[70:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[70:49] Quantification
[70:52] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_mzML.quant.

[70:53] File #4/6
[70:53] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML
[76:01] 4804019 library precursors are potentially detectable
[76:01] Processing...
[77:37] RT window set to 1.10215
[77:39] Recommended MS1 mass accuracy setting: 2.74834 ppm
[81:04] Removing low confidence identifications
[81:04] Removing interfering precursors
[81:17] Training neural networks: 214799 targets, 145738 decoys
[81:29] Number of IDs at 0.01 FDR: 101055
[81:30] Calculating protein q-values
[81:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[81:30] Quantification
[81:33] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_mzML.quant.

[81:33] File #5/6
[81:33] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML
[84:22] 4804019 library precursors are potentially detectable
[84:23] Processing...
[85:44] RT window set to 1.1902
[85:44] Recommended MS1 mass accuracy setting: 2.50239 ppm
[89:31] Removing low confidence identifications
[89:31] Removing interfering precursors
[89:44] Training neural networks: 218733 targets, 146414 decoys
[89:57] Number of IDs at 0.01 FDR: 101756
[89:58] Calculating protein q-values
[89:59] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[89:59] Quantification
[90:02] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_mzML.quant.

[90:02] File #6/6
[90:02] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML
[94:09] 4804019 library precursors are potentially detectable
[94:10] Processing...
[95:24] RT window set to 1.18315
[95:24] Recommended MS1 mass accuracy setting: 2.73781 ppm
[98:29] Removing low confidence identifications
[98:29] Removing interfering precursors
[98:43] Training neural networks: 213583 targets, 145762 decoys
[98:53] Number of IDs at 0.01 FDR: 101597
[98:54] Calculating protein q-values
[98:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[98:55] Quantification
[98:57] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/_public_local_ProteoBench_HYE_Astral_mzml_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_mzML.quant.

[98:57] Cross-run analysis
[98:57] Reading quantification information: 6 files
[98:58] Quantifying peptides
[99:09] Assembling protein groups
[99:12] Quantifying proteins
[99:12] Calculating q-values for protein and gene groups
[99:13] Calculating global q-values for protein and gene groups
[99:13] Writing report
[99:30] Report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/report-first-pass.tsv.
[99:30] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/report-first-pass.stats.tsv
[99:30] Generating spectral library:
[99:31] 135866 precursors passing the FDR threshold are to be extracted
[99:31] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML
[102:58] 4804019 library precursors are potentially detectable
[103:00] 10756 spectra added to the library
[103:00] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML
[107:12] 4804019 library precursors are potentially detectable
[107:14] 12165 spectra added to the library
[107:14] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML
[110:57] 4804019 library precursors are potentially detectable
[111:01] 39986 spectra added to the library
[111:01] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML
[114:22] 4804019 library precursors are potentially detectable
[114:24] 13105 spectra added to the library
[114:24] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML
[116:28] 4804019 library precursors are potentially detectable
[116:30] 10378 spectra added to the library
[116:30] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML
[119:27] 4804019 library precursors are potentially detectable
[119:30] 28723 spectra added to the library
[119:30] Saving spectral library to lib.tsv
ERROR: cannot write to lib.tsv. Check if the destination folder is write-protected or the file is in use
[119:30] Loading the generated library and saving it in the .speclib format
[119:30] Loading spectral library lib.tsv
cannot read the file
[119:30] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[119:31] Library contains 0 proteins, and 0 genes
[119:31] Saving the library to lib.tsv.speclib
Could not save lib.tsv.speclib

[119:34] Second pass: using the newly created spectral library to reanalyse the data
[119:34] File #1/6
[119:34] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML
[122:24] 116735 library precursors are potentially detectable
[122:24] Processing...
[122:24] RT window set to 0.345331
[122:24] Recommended MS1 mass accuracy setting: 2.46885 ppm
[122:27] Removing low confidence identifications
[122:27] Removing interfering precursors
[122:30] Training neural networks: 104082 targets, 41054 decoys
[122:34] Number of IDs at 0.01 FDR: 96067
[122:35] Calculating protein q-values
[122:35] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[122:35] Quantification

[122:36] File #2/6
[122:36] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML
[124:18] 116735 library precursors are potentially detectable
[124:18] Processing...
[124:18] RT window set to 0.363644
[124:18] Recommended MS1 mass accuracy setting: 2.3883 ppm
[124:20] Removing low confidence identifications
[124:20] Removing interfering precursors
[124:24] Training neural networks: 104773 targets, 42436 decoys
[124:27] Number of IDs at 0.01 FDR: 97246
[124:28] Calculating protein q-values
[124:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[124:28] Quantification

[124:29] File #3/6
[124:29] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML
[126:09] 116735 library precursors are potentially detectable
[126:09] Processing...
[126:09] RT window set to 0.372963
[126:09] Recommended MS1 mass accuracy setting: 2.66303 ppm
[126:12] Removing low confidence identifications
[126:12] Removing interfering precursors
[126:16] Training neural networks: 105443 targets, 43166 decoys
[126:19] Number of IDs at 0.01 FDR: 97703
[126:20] Calculating protein q-values
[126:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[126:20] Quantification

[126:21] File #4/6
[126:21] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML
[127:59] 116735 library precursors are potentially detectable
[127:59] Processing...
[128:00] RT window set to 0.374211
[128:00] Recommended MS1 mass accuracy setting: 2.36402 ppm
[128:02] Removing low confidence identifications
[128:02] Removing interfering precursors
[128:06] Training neural networks: 105988 targets, 43464 decoys
[128:09] Number of IDs at 0.01 FDR: 98379
[128:11] Calculating protein q-values
[128:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[128:11] Quantification

[128:12] File #5/6
[128:12] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML
[129:47] 116735 library precursors are potentially detectable
[129:47] Processing...
[129:48] RT window set to 0.385921
[129:48] Recommended MS1 mass accuracy setting: 2.45273 ppm
[129:50] Removing low confidence identifications
[129:50] Removing interfering precursors
[129:54] Training neural networks: 106109 targets, 44408 decoys
[129:58] Number of IDs at 0.01 FDR: 98460
[129:59] Calculating protein q-values
[129:59] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[129:59] Quantification

[130:00] File #6/6
[130:00] Loading run /public/local/ProteoBench/HYE_Astral_mzml/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML
[131:38] 116735 library precursors are potentially detectable
[131:38] Processing...
[131:38] RT window set to 0.372121
[131:38] Recommended MS1 mass accuracy setting: 2.58024 ppm
[131:41] Removing low confidence identifications
[131:41] Removing interfering precursors
[131:45] Training neural networks: 106174 targets, 43183 decoys
[131:48] Number of IDs at 0.01 FDR: 98646
[131:49] Calculating protein q-values
[131:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[131:49] Quantification

[131:50] Cross-run analysis
[131:50] Reading quantification information: 6 files
[131:51] Quantifying peptides
[132:03] Quantifying proteins
[132:03] Calculating q-values for protein and gene groups
[132:04] Calculating global q-values for protein and gene groups
[132:04] Writing report
[132:18] Report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/report.tsv.
[132:18] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v1.8.1/report.stats.tsv

Finished

