
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 21:29:29
Current date and time: Fri Jul 18 13:15:30 2025
CPU: GenuineIntel Intel(R) Xeon(R) Gold 6430
SIMD instructions: AVX AVX2 AVX512CD AVX512F FMA SSE4.1 SSE4.2 
Logical CPU cores: 128
diann.exe --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw  --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw  --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw  --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw  --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw  --f H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw  --lib H:\DELALANDE Frankois\ProteoBench\DIA Astral\Test 7\library7step1.predicted.speclib --threads 64 --verbose 1 --out H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.parquet --qvalue 0.01 --matrices --out-lib H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\PB1.parquet --gen-spec-lib --fasta H:\DELALANDE Frankois\ProteoBench\DIA Astral\Test 7\ProteoBenchFASTA_MixedSpecies_HYE.fasta --met-excision --cut K*,R* --missed-cleavages 1 --unimod4 --var-mods 1 --var-mod UniMod:35,15.994915,M --var-mod UniMod:1,42.010565,*n --window 6 --mass-acc 3.0 --mass-acc-ms1 7.0 --peptidoforms --rt-profiling --pg-level 1 

Thread number set to 64
Output will be filtered at 0.01 FDR
Precursor/protein x samples expression level matrices will be saved along with the main report
A spectral library will be generated
N-terminal methionine excision enabled
In silico digest will involve cuts at K*,R*
Maximum number of missed cleavages set to 1
Cysteine carbamidomethylation enabled as a fixed modification
Maximum number of variable modifications set to 1
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Modification UniMod:1 with mass delta 42.0106 at *n will be considered as variable
Scan window radius set to 6
Peptidoform scoring enabled
The spectral library (if generated) will retain the original spectra but will include empirically-aligned RTs
Implicit protein grouping: protein names; this determines which peptides are considered 'proteotypic' and thus affects protein FDR calculation
WARNING: for DIA-NN to switch to the new .raw reader library, please download and install .NET SDK 8.0.407 or later https://dotnet.microsoft.com/en-us/download/dotnet/8.0
Mass accuracy will be fixed to 3e-06 (MS2) and 7e-06 (MS1)
The following variable modifications will be localised: UniMod:35 UniMod:1 

6 files will be processed
[0:00] Loading spectral library H:\DELALANDE Frankois\ProteoBench\DIA Astral\Test 7\library7step1.predicted.speclib
[0:18] Library annotated with sequence database(s): H:\DELALANDE Frankois\ProteoBench\DIA Astral\Test 7\ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:18] Spectral library loaded: 31837 protein isoforms, 51765 protein groups and 5275217 precursors in 2716671 elution groups.
[0:18] Loading protein annotations from FASTA H:\DELALANDE Frankois\ProteoBench\DIA Astral\Test 7\ProteoBenchFASTA_MixedSpecies_HYE.fasta
[0:19] Annotating library proteins with information from the FASTA database
[0:19] Protein names missing for some isoforms
[0:19] Gene names missing for some isoforms
[0:19] Library contains 31685 proteins, and 0 genes
[0:23] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[0:38] File #1/6
[0:38] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[2:22] Pre-processing...
[2:24] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5270221 precursors in range
[2:25] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[2:37] RT window set to 1.15599
[2:37] Recommended MS1 mass accuracy setting: 2.5 ppm
[2:41] Searching decoys
[2:59] Main search
[3:34] Removing low confidence identifications
[3:46] Removing interfering precursors
[3:54] Training neural networks on 212592 target and 129831 decoy PSMs
[4:47] Training neural networks on 212592 target and 131977 decoy PSMs
[5:36] Number of IDs at 0.01 FDR: 95905
[5:37] Precursors at 1% peptidoform FDR: 93684
[5:37] Calculating protein q-values
[5:38] Number of proteins identified at 1% FDR: 10489 (precursor-level), 9590 (protein-level) (inference performed using proteotypic peptides only)
[5:38] Quantification
[5:39] Precursors with scored PTMs at 1% FDR: 2914 out of 3086 considered
[5:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 90770
[5:39] Precursors with PTMs localised (when required) with > 90% confidence: 2826 out of 2914
[6:03] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw.quant

[6:03] File #2/6
[6:03] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[8:25] Pre-processing...
[8:26] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5270221 precursors in range
[8:27] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[8:40] RT window set to 1.42472
[8:40] Recommended MS1 mass accuracy setting: 2.6 ppm
[8:45] Searching decoys
[9:06] Main search
[9:48] Removing low confidence identifications
[10:00] Removing interfering precursors
[10:07] Training neural networks on 207819 target and 126767 decoy PSMs
[10:59] Training neural networks on 207819 target and 128080 decoy PSMs
[11:46] Number of IDs at 0.01 FDR: 97793
[11:47] Precursors at 1% peptidoform FDR: 94798
[11:48] Calculating protein q-values
[11:48] Number of proteins identified at 1% FDR: 10529 (precursor-level), 9604 (protein-level) (inference performed using proteotypic peptides only)
[11:49] Quantification
[11:50] Precursors with scored PTMs at 1% FDR: 2981 out of 3199 considered
[11:50] Precursors with all scored PTM sites unoccupied at 1% FDR: 91817
[11:50] Precursors with PTMs localised (when required) with > 90% confidence: 2910 out of 2981
[12:13] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw.quant

[12:13] File #3/6
[12:13] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[14:13] Pre-processing...
[14:15] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5270221 precursors in range
[14:16] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[14:29] RT window set to 1.26241
[14:29] Recommended MS1 mass accuracy setting: 2.7 ppm
[14:33] Searching decoys
[14:51] Main search
[15:29] Removing low confidence identifications
[15:41] Removing interfering precursors
[15:49] Training neural networks on 211591 target and 129408 decoy PSMs
[16:42] Training neural networks on 211591 target and 130609 decoy PSMs
[17:30] Number of IDs at 0.01 FDR: 98365
[17:31] Precursors at 1% peptidoform FDR: 95857
[17:32] Calculating protein q-values
[17:32] Number of proteins identified at 1% FDR: 10598 (precursor-level), 9625 (protein-level) (inference performed using proteotypic peptides only)
[17:32] Quantification
[17:34] Precursors with scored PTMs at 1% FDR: 3058 out of 3217 considered
[17:34] Precursors with all scored PTM sites unoccupied at 1% FDR: 92799
[17:34] Precursors with PTMs localised (when required) with > 90% confidence: 2971 out of 3058
[17:54] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw.quant

[17:54] File #4/6
[17:54] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[20:08] Pre-processing...
[20:10] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5270221 precursors in range
[20:11] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[20:21] RT window set to 1.32292
[20:21] Recommended MS1 mass accuracy setting: 2.7 ppm
[20:25] Searching decoys
[20:44] Main search
[21:23] Removing low confidence identifications
[21:36] Removing interfering precursors
[21:43] Training neural networks on 213424 target and 131576 decoy PSMs
[22:37] Training neural networks on 213424 target and 132891 decoy PSMs
[23:25] Number of IDs at 0.01 FDR: 98159
[23:26] Precursors at 1% peptidoform FDR: 95314
[23:27] Calculating protein q-values
[23:28] Number of proteins identified at 1% FDR: 10336 (precursor-level), 9287 (protein-level) (inference performed using proteotypic peptides only)
[23:28] Quantification
[23:29] Precursors with scored PTMs at 1% FDR: 3511 out of 3811 considered
[23:29] Precursors with all scored PTM sites unoccupied at 1% FDR: 91803
[23:29] Precursors with PTMs localised (when required) with > 90% confidence: 3398 out of 3511
[23:50] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw.quant

[23:50] File #5/6
[23:50] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[26:05] Pre-processing...
[26:07] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5270221 precursors in range
[26:08] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[26:18] RT window set to 1.2753
[26:18] Recommended MS1 mass accuracy setting: 2.7 ppm
[26:22] Searching decoys
[26:40] Main search
[27:18] Removing low confidence identifications
[27:30] Removing interfering precursors
[27:37] Training neural networks on 211510 target and 129901 decoy PSMs
[28:31] Training neural networks on 211510 target and 131601 decoy PSMs
[29:19] Number of IDs at 0.01 FDR: 97517
[29:20] Precursors at 1% peptidoform FDR: 94719
[29:21] Calculating protein q-values
[29:21] Number of proteins identified at 1% FDR: 10288 (precursor-level), 9294 (protein-level) (inference performed using proteotypic peptides only)
[29:22] Quantification
[29:23] Precursors with scored PTMs at 1% FDR: 3518 out of 3798 considered
[29:23] Precursors with all scored PTM sites unoccupied at 1% FDR: 91201
[29:23] Precursors with PTMs localised (when required) with > 90% confidence: 3420 out of 3518
[29:44] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw.quant

[29:44] File #6/6
[29:44] Loading run H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[31:58] Pre-processing...
[32:00] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5270221 precursors in range
[32:01] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[32:11] RT window set to 1.28987
[32:11] Recommended MS1 mass accuracy setting: 2.8 ppm
[32:16] Searching decoys
[32:35] Main search
[33:13] Removing low confidence identifications
[33:25] Removing interfering precursors
[33:32] Training neural networks on 213168 target and 132099 decoy PSMs
[34:26] Training neural networks on 213168 target and 132812 decoy PSMs
[35:15] Number of IDs at 0.01 FDR: 97973
[35:15] Precursors at 1% peptidoform FDR: 95465
[35:16] Calculating protein q-values
[35:17] Number of proteins identified at 1% FDR: 10395 (precursor-level), 9360 (protein-level) (inference performed using proteotypic peptides only)
[35:17] Quantification
[35:18] Precursors with scored PTMs at 1% FDR: 3575 out of 3837 considered
[35:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 91890
[35:18] Precursors with PTMs localised (when required) with > 90% confidence: 3457 out of 3575
[35:38] Quantification information saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw.quant

[35:39] Cross-run analysis
[35:39] Reading quantification information: 6 files
[36:04] Quantifying peptides
[38:56] Quantification parameters: 0.365704, 0.00143286, 0.00158586, 0.0119388, 0.0119641, 0.0120481, 0.175534, 0.240423, 0.198905, 0.013188, 0.0374556, 0.0148148, 0.240795, 0.0519434, 0.0694219, 0.0114133
[40:11] Assembling protein groups
[40:14] Quantifying proteins
[40:14] Calculating q-values for protein and gene groups
[40:17] Calculating global q-values for protein and gene groups
[40:17] Protein groups with global q-value <= 0.01: 11035
[40:24] Compressed report saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[40:24] Site report saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.site_report.parquet
[40:24] Saving precursor levels matrix
[40:28] Precursor levels matrix (1% precursor and protein group FDR) saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.pr_matrix.tsv.
[40:28] Saving protein group levels matrix
[40:28] Protein groups matrix saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.pg_matrix.tsv.
[40:28] Saving gene group levels matrix
[40:28] Gene groups matrix saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.gg_matrix.tsv.
[40:28] Saving unique genes levels matrix
[40:28] Unique genes matrix saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.unique_genes_matrix.tsv.
[40:34] Manifest saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.manifest.txt
[40:34] Stats report saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\reportPB1.stats.tsv
[40:35] Generating spectral library:
[40:37] 129146 target and 1309 decoy precursors saved
[40:38] Spectral library saved to H:\DELALANDE Frankois\ProteoBench\DIA Astral\PB1\PB1.parquet

