
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 15:05:00
Current date and time: Sun Apr 26 19:09:47 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.2.0/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_v2.2.0/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
[0:15] 7429950 precursors generated
[0:15] Gene names missing for some isoforms
[0:15] Library contains 27293 proteins, and 0 genes
[0:21] [0:34] [5:41] [6:20] [6:22] [6:25] Saving the library to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.2.0/report-lib.predicted.speclib
[6:30] Initialising library
[6:42] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.2.0/report-lib.predicted.speclib
[6:45] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[6:46] Spectral library loaded: 27443 protein isoforms, 38575 protein groups and 7429950 precursors in 3511335 elution groups.
[6:46] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[6:47] Annotating library proteins with information from the FASTA database
[6:47] Gene names missing for some isoforms
[6:47] Library contains 27293 proteins, and 0 genes
[6:52] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[7:04] File #1/6
[7:04] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw
[7:08] Pre-processing...
[7:12] 1842 MS1 and 27799 MS2 scans in 1842 (inferred) and 1842 (encoded) cycles, 5095220 precursors in range
[7:12] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[8:10] RT window set to 1.56098
[8:10] Peak width: 3.092
[8:10] Scan window radius set to 6
[8:10] Recommended MS1 mass accuracy setting: 2 ppm
[8:44] Searching decoys
[10:12] Main search
[13:09] Removing low confidence identifications
[13:17] Removing interfering precursors
[13:22] Training neural networks on 69227 target and 41863 decoy PSMs
[13:39] Training neural networks on 69227 target and 40114 decoy PSMs
[13:52] Number of IDs at 0.01 FDR: 34809
[13:53] Precursors at 1% peptidoform FDR: 33095
[13:53] Calculating protein q-values
[13:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[13:54] Quantification
[13:54] Precursors with scored PTMs at 1% FDR: 387 out of 435 considered
[13:54] Precursors with all scored PTM sites unoccupied at 1% FDR: 32708
[13:54] Precursors with PTMs localised (when required) with > 90% confidence: 368 out of 387
[13:55] 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

[13:55] File #2/6
[13:55] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw
[13:59] Pre-processing...
[14:04] 1859 MS1 and 28183 MS2 scans in 1859 (inferred) and 1859 (encoded) cycles, 5095220 precursors in range
[14:05] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[14:54] RT window set to 1.53252
[14:55] Recommended MS1 mass accuracy setting: 2 ppm
[15:29] Searching decoys
[17:08] Main search
[20:24] Removing low confidence identifications
[20:32] Removing interfering precursors
[20:38] Training neural networks on 72748 target and 45227 decoy PSMs
[20:57] Training neural networks on 72748 target and 43411 decoy PSMs
[21:10] Number of IDs at 0.01 FDR: 36783
[21:10] Precursors at 1% peptidoform FDR: 35048
[21:11] Calculating protein q-values
[21:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[21:11] Quantification
[21:12] Precursors with scored PTMs at 1% FDR: 1500 out of 1617 considered
[21:12] Precursors with all scored PTM sites unoccupied at 1% FDR: 33548
[21:12] Precursors with PTMs localised (when required) with > 90% confidence: 1472 out of 1500
[21:13] 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

[21:13] File #3/6
[21:13] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw
[21:16] Pre-processing...
[21:20] 1856 MS1 and 28105 MS2 scans in 1856 (inferred) and 1856 (encoded) cycles, 5095220 precursors in range
[21:20] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[22:09] RT window set to 1.67456
[22:09] Recommended MS1 mass accuracy setting: 2.2 ppm
[22:44] Searching decoys
[24:26] Main search
[27:48] Removing low confidence identifications
[27:56] Removing interfering precursors
[28:01] Training neural networks on 69918 target and 41870 decoy PSMs
[28:18] Training neural networks on 69918 target and 40217 decoy PSMs
[28:31] Number of IDs at 0.01 FDR: 36311
[28:32] Precursors at 1% peptidoform FDR: 34342
[28:32] Calculating protein q-values
[28:33] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[28:33] Quantification
[28:33] Precursors with scored PTMs at 1% FDR: 1604 out of 1790 considered
[28:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 32738
[28:33] Precursors with PTMs localised (when required) with > 90% confidence: 1580 out of 1604
[28:34] 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

[28:34] File #4/6
[28:34] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw
[28:37] Pre-processing...
[28:40] 1827 MS1 and 27525 MS2 scans in 1827 (inferred) and 1827 (encoded) cycles, 5095220 precursors in range
[28:41] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[29:25] RT window set to 1.67378
[29:25] Recommended MS1 mass accuracy setting: 2 ppm
[29:58] Searching decoys
[31:22] Main search
[34:07] Removing low confidence identifications
[34:14] Removing interfering precursors
[34:19] Training neural networks on 63914 target and 38108 decoy PSMs
[34:36] Training neural networks on 63914 target and 36420 decoy PSMs
[34:48] Number of IDs at 0.01 FDR: 33127
[34:48] Precursors at 1% peptidoform FDR: 31593
[34:49] Calculating protein q-values
[34:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[34:49] Quantification
[34:50] Precursors with scored PTMs at 1% FDR: 266 out of 325 considered
[34:50] Precursors with all scored PTM sites unoccupied at 1% FDR: 31327
[34:50] Precursors with PTMs localised (when required) with > 90% confidence: 249 out of 266
[34:50] 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

[34:50] File #5/6
[34:50] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw
[34:54] Pre-processing...
[34:59] 1831 MS1 and 27624 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[35:00] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[35:45] RT window set to 1.44882
[35:45] Recommended MS1 mass accuracy setting: 1.9 ppm
[36:16] Searching decoys
[37:34] Main search
[40:04] Removing low confidence identifications
[40:12] Removing interfering precursors
[40:17] Training neural networks on 65997 target and 38650 decoy PSMs
[40:33] Training neural networks on 65997 target and 36888 decoy PSMs
[40:45] Number of IDs at 0.01 FDR: 33919
[40:46] Precursors at 1% peptidoform FDR: 32493
[40:46] Calculating protein q-values
[40:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[40:47] Quantification
[40:47] Precursors with scored PTMs at 1% FDR: 475 out of 534 considered
[40:47] Precursors with all scored PTM sites unoccupied at 1% FDR: 32018
[40:47] Precursors with PTMs localised (when required) with > 90% confidence: 448 out of 475
[40:48] 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

[40:48] File #6/6
[40:48] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw
[40:51] Pre-processing...
[40:54] 1831 MS1 and 27589 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[40:55] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[41:39] RT window set to 1.61068
[41:39] Recommended MS1 mass accuracy setting: 2 ppm
[42:12] Searching decoys
[43:35] Main search
[46:17] Removing low confidence identifications
[46:24] Removing interfering precursors
[46:29] Training neural networks on 63242 target and 36112 decoy PSMs
[46:44] Training neural networks on 63242 target and 34304 decoy PSMs
[46:54] Number of IDs at 0.01 FDR: 33327
[46:54] Precursors at 1% peptidoform FDR: 32102
[46:55] Calculating protein q-values
[46:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[46:55] Quantification
[46:56] Precursors with scored PTMs at 1% FDR: 429 out of 470 considered
[46:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 31673
[46:56] Precursors with PTMs localised (when required) with > 90% confidence: 413 out of 429
[46:56] 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

[46:56] Cross-run analysis
[46:56] Reading quantification information: 6 files
[47:11] Quantifying peptides
[47:46] Quantification parameters: 0.361497, 0.00233827, 0.0143755, 0.0127157, 0.012819, 0.0125412, 0.308641, 0.158132, 0.184385, 0.0139561, 0.0155455, 0.0146144, 0.352755, 0.114684, 0.161279, 0.0123491
[48:03] Assembling protein groups
[48:05] Quantifying proteins
[48:05] Calculating q-values for protein and gene groups
[48:06] Calculating global q-values for protein and gene groups
[48:06] Protein groups with global q-value <= 0.01: 7814
[48:07] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.2.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[48:07] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.2.0/report.stats.tsv
[48:07] Generating spectral library:
[48:08] 43891 target and 415 decoy precursors saved
WARNING: 407 precursors without any fragments annotated were skipped
[48:08] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.2.0/report-lib.parquet

