
DIA-NN 2.1.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Mar 23 2025 15:49:03
Current date and time: Sun Apr 26 19:10:29 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.1.0/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_v2.1.0/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] [0:36] [6:06] [6:44] [6:47] [6:50] Saving the library to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.1.0/report-lib.predicted.speclib
[6:54] Initialising library
[7:18] Loading spectral library /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.1.0/report-lib.predicted.speclib
[7:21] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[7:22] Spectral library loaded: 27443 protein isoforms, 38575 protein groups and 7429950 precursors in 3511335 elution groups.
[7:22] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[7:22] Annotating library proteins with information from the FASTA database
[7:22] Gene names missing for some isoforms
[7:22] Library contains 27293 proteins, and 0 genes
[7:28] Initialising library
WARNING: it is strongly recommended to enable MBR when analysing with a large library, if this is a quantitative analysis

[7:52] File #1/6
[7:52] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw
[8:01] Pre-processing...
[8:06] 1842 MS1 and 27799 MS2 scans in 1842 (inferred) and 1842 (encoded) cycles, 5095220 precursors in range
[8:07] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[9:23] RT window set to 1.53829
[9:23] Peak width: 2.912
[9:23] Scan window radius set to 6
[9:23] Recommended MS1 mass accuracy setting: 1.9 ppm
[10:42] Searching decoys
[11:59] Main search
[14:32] Removing low confidence identifications
[14:40] Removing interfering precursors
[14:47] Training neural networks on 61814 target and 35505 decoy PSMs
[15:06] Training neural networks on 61814 target and 33781 decoy PSMs
[15:19] Number of IDs at 0.01 FDR: 33743
[15:19] Precursors at 1% peptidoform FDR: 32097
[15:20] Calculating protein q-values
[15:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[15:20] Quantification
[15:20] Precursors with scored PTMs at 1% FDR: 350 out of 446 considered
[15:20] Precursors with all scored PTM sites unoccupied at 1% FDR: 31747
[15:20] Precursors with PTMs localised (when required) with > 90% confidence: 336 out of 350
[15:21] 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

[15:21] File #2/6
[15:21] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw
[15:31] Pre-processing...
[15:35] 1859 MS1 and 28183 MS2 scans in 1859 (inferred) and 1859 (encoded) cycles, 5095220 precursors in range
[15:36] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[16:41] RT window set to 1.4535
[16:42] Recommended MS1 mass accuracy setting: 1.9 ppm
[17:47] Searching decoys
[19:09] Main search
[21:52] Removing low confidence identifications
[22:01] Removing interfering precursors
[22:07] Training neural networks on 68665 target and 40308 decoy PSMs
[22:28] Training neural networks on 68665 target and 38685 decoy PSMs
[22:40] Number of IDs at 0.01 FDR: 35927
[22:40] Precursors at 1% peptidoform FDR: 34128
[22:41] Calculating protein q-values
[22:41] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[22:41] Quantification
[22:42] Precursors with scored PTMs at 1% FDR: 1461 out of 1621 considered
[22:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 32667
[22:42] Precursors with PTMs localised (when required) with > 90% confidence: 1433 out of 1461
[22:42] 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

[22:42] File #3/6
[22:42] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw
[22:52] Pre-processing...
[22:56] 1856 MS1 and 28105 MS2 scans in 1856 (inferred) and 1856 (encoded) cycles, 5095220 precursors in range
[22:57] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[24:14] RT window set to 1.50588
[24:15] Recommended MS1 mass accuracy setting: 1.9 ppm
[25:19] Searching decoys
[26:40] Main search
[29:22] Removing low confidence identifications
[29:31] Removing interfering precursors
[29:37] Training neural networks on 63449 target and 36242 decoy PSMs
[29:57] Training neural networks on 63449 target and 34879 decoy PSMs
[30:10] Number of IDs at 0.01 FDR: 35142
[30:10] Precursors at 1% peptidoform FDR: 33219
[30:11] Calculating protein q-values
[30:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[30:11] Quantification
[30:12] Precursors with scored PTMs at 1% FDR: 1511 out of 1681 considered
[30:12] Precursors with all scored PTM sites unoccupied at 1% FDR: 31708
[30:12] Precursors with PTMs localised (when required) with > 90% confidence: 1489 out of 1511
[30:12] 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

[30:12] File #4/6
[30:12] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw
[30:20] Pre-processing...
[30:24] 1827 MS1 and 27525 MS2 scans in 1827 (inferred) and 1827 (encoded) cycles, 5095220 precursors in range
[30:25] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[31:35] RT window set to 1.58133
[31:35] Recommended MS1 mass accuracy setting: 1.9 ppm
[32:50] Searching decoys
[34:00] Main search
[36:22] Removing low confidence identifications
[36:29] Removing interfering precursors
[36:36] Training neural networks on 59096 target and 34736 decoy PSMs
[36:55] Training neural networks on 59096 target and 33077 decoy PSMs
[37:07] Number of IDs at 0.01 FDR: 31630
[37:08] Precursors at 1% peptidoform FDR: 30078
[37:08] Calculating protein q-values
[37:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[37:09] Quantification
[37:09] Precursors with scored PTMs at 1% FDR: 178 out of 311 considered
[37:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 29900
[37:09] Precursors with PTMs localised (when required) with > 90% confidence: 168 out of 178
[37:10] 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

[37:10] File #5/6
[37:10] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw
[37:18] Pre-processing...
[37:22] 1831 MS1 and 27624 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[37:23] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[38:36] RT window set to 1.55253
[38:36] Recommended MS1 mass accuracy setting: 1.8 ppm
[39:51] Searching decoys
[41:03] Main search
[43:26] Removing low confidence identifications
[43:34] Removing interfering precursors
[43:41] Training neural networks on 61454 target and 35812 decoy PSMs
[43:59] Training neural networks on 61454 target and 34436 decoy PSMs
[44:12] Number of IDs at 0.01 FDR: 32565
[44:13] Precursors at 1% peptidoform FDR: 31131
[44:13] Calculating protein q-values
[44:14] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[44:14] Quantification
[44:14] Precursors with scored PTMs at 1% FDR: 421 out of 533 considered
[44:14] Precursors with all scored PTM sites unoccupied at 1% FDR: 30710
[44:14] Precursors with PTMs localised (when required) with > 90% confidence: 401 out of 421
[44:15] 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

[44:15] File #6/6
[44:15] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw
[44:23] Pre-processing...
[44:27] 1831 MS1 and 27589 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[44:28] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[45:40] RT window set to 1.46687
[45:40] Recommended MS1 mass accuracy setting: 1.8 ppm
[46:48] Searching decoys
[47:55] Main search
[50:15] Removing low confidence identifications
[50:25] Removing interfering precursors
[50:33] Training neural networks on 61937 target and 35431 decoy PSMs
[50:52] Training neural networks on 61937 target and 34027 decoy PSMs
[51:06] Number of IDs at 0.01 FDR: 32516
[51:06] Precursors at 1% peptidoform FDR: 31065
[51:07] Calculating protein q-values
[51:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[51:07] Quantification
[51:08] Precursors with scored PTMs at 1% FDR: 408 out of 489 considered
[51:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 30657
[51:08] Precursors with PTMs localised (when required) with > 90% confidence: 394 out of 408
[51:08] 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

[51:08] Cross-run analysis
[51:08] Reading quantification information: 6 files
[51:23] Quantifying peptides
[51:58] Quantification parameters: 0.359982, 0.00234345, 0.0143564, 0.0126382, 0.012586, 0.0126514, 0.306258, 0.161704, 0.183335, 0.0139192, 0.0150665, 0.0145578, 0.361217, 0.120067, 0.168604, 0.012302
[52:15] Assembling protein groups
[52:17] Quantifying proteins
[52:17] Calculating q-values for protein and gene groups
[52:18] Calculating global q-values for protein and gene groups
[52:18] Protein groups with global q-value <= 0.01: 7788
[52:20] Compressed report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.1.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[52:20] Stats report saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.1.0/report.stats.tsv
[52:20] Generating spectral library:
[52:20] 43768 target and 422 decoy precursors saved
WARNING: 381 precursors without any fragments annotated were skipped
[52:20] Spectral library saved to /home/robbe/PB_output/results/test_run/HYE_Astral_Single_Cell/diann_v2.1.0/report-lib.parquet

