
DIA-NN 2.3.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Sep 26 2025 02:56:25
Current date and time: Mon Apr 27 12:07:40 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.3.0/diann-linux --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw --f /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta --out /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report.tsv --threads 32 --missed-cleavages 2 --min-pep-len 7 --max-pep-len 30 --mass-acc 20 --mass-acc-ms1 20 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 2 --max-pr-charge 4 --min-pr-mz 400 --max-pr-mz 1200 --min-fr-mz 200 --max-fr-mz 2000 --unimod4 --var-mod UniMod:35,15.994915,M --gen-spec-lib --fasta-search 

Thread number set to 32
Maximum number of missed cleavages set to 2
Min peptide length set to 7
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 2
Max precursor charge set to 4
Min precursor m/z set to 400
Max precursor m/z set to 1200
Min fragment m/z set to 200
Max fragment m/z set to 2000
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
A spectral library will be generated
DIA-NN will carry out FASTA digest for in silico lib generation
Mass accuracy will be fixed to 2e-05 (MS2) and 2e-05 (MS1)
WARNING: FASTA digest mode enabled and raw data are provided, turning on deep learning spectra/RT/IM prediction
WARNING: incorrect settings, the in silico-predicted library must be generated in a separate pipeline step and then used to process the raw data, now without activating FASTA digest
WARNING: peptidoform scoring enabled because variable modifications have been declared; to disable, use --no-peptidoforms
The following variable modifications will be localised: UniMod:35 

6 files will be processed
[0:00] Loading FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[0:05] Processing FASTA
[0:08] Assembling elution groups
[0:16] 7429950 precursors generated
[0:16] Gene names missing for some isoforms
[0:16] Library contains 27293 proteins, and 0 genes
[0:22] [0:35] [5:37] [6:14] [6:17] [6:21] Saving the library to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report-lib.predicted.speclib
[6:30] Initialising library
[6:46] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report-lib.predicted.speclib
[6:49] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[6:51] Spectral library loaded: 27443 protein isoforms, 38575 protein groups and 7429950 precursors in 3511335 elution groups.
[6:51] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[6:51] Annotating library proteins with information from the FASTA database
[6:51] Gene names missing for some isoforms
[6:51] Library contains 27293 proteins, and 0 genes
[6:57] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[7:12] File #1/6
[7:12] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw
[7:17] Pre-processing...
[7:20] 1842 MS1 and 27799 MS2 scans in 1842 (inferred) and 1842 (encoded) cycles, 5095220 precursors in range
[7:20] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[8:08] RT window set to 1.48954
[8:08] Peak width: 3.132
[8:08] Scan window radius set to 6
[8:08] Recommended MS1 mass accuracy setting: 2 ppm
[8:40] Searching decoys
[10:14] Main search
[13:27] Removing low confidence identifications
[13:35] Removing interfering precursors
[13:42] Training neural networks on 68273 target and 41008 decoy PSMs
[14:02] Training neural networks on 68273 target and 38835 decoy PSMs
[14:15] IDs at 0.01 FDR: 34668
[14:15] Precursors at 1% peptidoform FDR: 33049
[14:17] Number of IDs at 0.01 FDR: 36589
[14:17] Calculating protein q-values
[14:17] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[14:17] Quantification
[14:17] Precursors with scored PTMs at 1% FDR: 379 out of 472 considered
[14:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 33206
[14:17] Precursors with PTMs localised (when required) with > 90% confidence: 361 out of 379
[14:18] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw.quant

[14:18] File #2/6
[14:18] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw
[14:21] Pre-processing...
[14:25] 1859 MS1 and 28183 MS2 scans in 1859 (inferred) and 1859 (encoded) cycles, 5095220 precursors in range
[14:26] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[15:23] RT window set to 1.50542
[15:23] Recommended MS1 mass accuracy setting: 2.1 ppm
[16:02] Searching decoys
[17:51] Main search
[21:19] Removing low confidence identifications
[21:27] Removing interfering precursors
[21:32] Training neural networks on 75816 target and 46855 decoy PSMs
[21:49] Training neural networks on 75816 target and 44688 decoy PSMs
[22:03] IDs at 0.01 FDR: 37072
[22:04] Precursors at 1% peptidoform FDR: 35524
[22:06] Number of IDs at 0.01 FDR: 39731
[22:06] Calculating protein q-values
[22:06] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[22:06] Quantification
[22:07] Precursors with scored PTMs at 1% FDR: 1587 out of 1855 considered
[22:07] Precursors with all scored PTM sites unoccupied at 1% FDR: 34678
[22:07] Precursors with PTMs localised (when required) with > 90% confidence: 1554 out of 1587
[22:07] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw.quant

[22:07] File #3/6
[22:07] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw
[22:11] Pre-processing...
[22:17] 1856 MS1 and 28105 MS2 scans in 1856 (inferred) and 1856 (encoded) cycles, 5095220 precursors in range
[22:17] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[23:07] RT window set to 1.55468
[23:07] Recommended MS1 mass accuracy setting: 2.1 ppm
[23:47] Searching decoys
[25:38] Main search
[29:10] Removing low confidence identifications
[29:19] Removing interfering precursors
[29:24] Training neural networks on 71394 target and 42471 decoy PSMs
[29:44] Training neural networks on 71394 target and 40412 decoy PSMs
[29:57] IDs at 0.01 FDR: 36801
[29:58] Precursors at 1% peptidoform FDR: 34930
[30:00] Number of IDs at 0.01 FDR: 38931
[30:00] Calculating protein q-values
[30:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[30:00] Quantification
[30:00] Precursors with scored PTMs at 1% FDR: 1669 out of 1989 considered
[30:00] Precursors with all scored PTM sites unoccupied at 1% FDR: 33778
[30:00] Precursors with PTMs localised (when required) with > 90% confidence: 1645 out of 1669
[30:01] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw.quant

[30:01] File #4/6
[30:01] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw
[30:04] Pre-processing...
[30:08] 1827 MS1 and 27525 MS2 scans in 1827 (inferred) and 1827 (encoded) cycles, 5095220 precursors in range
[30:08] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[30:55] RT window set to 1.70724
[30:55] Recommended MS1 mass accuracy setting: 1.9 ppm
[31:39] Searching decoys
[33:15] Main search
[36:31] Removing low confidence identifications
[36:39] Removing interfering precursors
[36:45] Training neural networks on 64099 target and 38106 decoy PSMs
[37:02] Training neural networks on 64099 target and 36297 decoy PSMs
[37:14] IDs at 0.01 FDR: 33205
[37:15] Precursors at 1% peptidoform FDR: 31860
[37:16] Number of IDs at 0.01 FDR: 35117
[37:16] Calculating protein q-values
[37:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[37:16] Quantification
[37:16] Precursors with scored PTMs at 1% FDR: 286 out of 391 considered
[37:16] Precursors with all scored PTM sites unoccupied at 1% FDR: 32129
[37:16] Precursors with PTMs localised (when required) with > 90% confidence: 268 out of 286
[37:17] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw.quant

[37:17] File #5/6
[37:17] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw
[37:20] Pre-processing...
[37:23] 1831 MS1 and 27624 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[37:24] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[38:14] RT window set to 1.51084
[38:14] Recommended MS1 mass accuracy setting: 1.9 ppm
[38:49] Searching decoys
[40:11] Main search
[43:08] Removing low confidence identifications
[43:16] Removing interfering precursors
[43:22] Training neural networks on 66326 target and 39619 decoy PSMs
[43:40] Training neural networks on 66326 target and 37576 decoy PSMs
[43:55] IDs at 0.01 FDR: 33743
[43:55] Precursors at 1% peptidoform FDR: 32193
[43:56] Number of IDs at 0.01 FDR: 36157
[43:56] Calculating protein q-values
[43:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[43:57] Quantification
[43:57] Precursors with scored PTMs at 1% FDR: 455 out of 596 considered
[43:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 32315
[43:57] Precursors with PTMs localised (when required) with > 90% confidence: 431 out of 455
[43:58] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw.quant

[43:58] File #6/6
[43:58] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw
[44:01] Pre-processing...
[44:04] 1831 MS1 and 27589 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[44:05] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[44:54] RT window set to 1.63935
[44:54] Recommended MS1 mass accuracy setting: 1.9 ppm
[45:27] Searching decoys
[47:05] Main search
[50:21] Removing low confidence identifications
[50:28] Removing interfering precursors
[50:33] Training neural networks on 64466 target and 37442 decoy PSMs
[50:50] Training neural networks on 64466 target and 35768 decoy PSMs
[51:03] IDs at 0.01 FDR: 33592
[51:03] Precursors at 1% peptidoform FDR: 32344
[51:04] Number of IDs at 0.01 FDR: 35744
[51:04] Calculating protein q-values
[51:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[51:05] Quantification
[51:05] Precursors with scored PTMs at 1% FDR: 478 out of 570 considered
[51:05] Precursors with all scored PTM sites unoccupied at 1% FDR: 32540
[51:05] Precursors with PTMs localised (when required) with > 90% confidence: 461 out of 478
[51:06] Quantification information saved to /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw.quant

[51:06] Cross-run analysis
[51:06] Reading quantification information: 6 files
[51:22] Quantifying peptides
[51:46] Quantification parameters: 0.37207, 0.00225263, 0.0147603, 0.0125155, 0.0127288, 0.0125783, 0.31656, 0.149156, 0.185385, 0.0137528, 0.0152627, 0.0141157, 0.35918, 0.124984, 0.171569, 0.0115703
[51:50] Assembling protein groups
[51:51] Quantifying proteins
[51:51] Calculating q-values for protein and gene groups
[51:52] Calculating global q-values for protein and gene groups
[51:52] Protein groups with global q-value <= 0.01: 7890
[51:53] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[51:53] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report.stats.tsv
[51:54] Generating spectral library:
[51:54] 43627 target and 418 decoy precursors saved
WARNING: 2422 precursors without any fragments annotated were skipped
[51:54] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.3.0/report-lib.parquet

