
DIA-NN 2.5.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 12 2026 10:45:33
Current date and time: Thu Apr 30 10:46:26 2026
Logical CPU cores: 128
/home/robbe/bin/diann-2.5.0/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/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/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 --reanalyse 

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
MBR enabled; .quant files will only be saved to disk during the first pass
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
[0:06] Processing FASTA
[0:09] Assembling elution groups
[0:18] 7429950 precursors generated
[0:18] Gene names missing for some isoforms
[0:18] Library contains 27293 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:25] [0:37] [7:03] [7:42] [7:45] [7:48] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-lib.predicted.speclib
[7:52] Initialising library
[8:05] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-lib.predicted.speclib
[8:08] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[8:10] Spectral library loaded: 27443 protein isoforms, 38575 protein groups and 7429950 precursors in 3511335 elution groups (targets and decoys).
[8:10] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[8:10] Annotating library proteins with information from the FASTA database
[8:10] Gene names missing for some isoforms
[8:10] Library contains 27293 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[8:15] Initialising library

First pass: generating a spectral library from DIA data

[8:28] File #1/6
[8:28] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw
[8:41] Pre-processing...
[8:44] 1842 MS1 and 27799 MS2 scans in 1842 (inferred) and 1842 (encoded) cycles, 5095220 precursors in range
[8:45] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[9:33] RT window set to 1.48954
[9:33] Peak width: 3.132
[9:33] Scan window radius set to 6
[9:33] Recommended MS1 mass accuracy setting: 2 ppm
[10:09] Searching decoys
[11:35] Main search
[14:24] Removing low confidence identifications
[14:35] Removing interfering precursors
[14:42] Training neural networks on 90461 target and 69217 decoy PSMs
[15:02] Training neural networks on 90461 target and 67827 decoy PSMs
[15:17] Precursors at 1% peptidoform FDR: 34163
[15:18] Number of IDs at 0.01 FDR: 35700
[15:18] Calculating protein q-values
[15:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[15:19] Quantification
[15:19] Precursors with scored PTMs at 1% FDR: 416 out of 457 considered
[15:19] Precursors with all scored PTM sites unoccupied at 1% FDR: 33896
[15:19] Precursors with PTMs localised (when required) with > 90% confidence: 396 out of 416
[15:19] 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

[15:19] File #2/6
[15:19] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw
[15:46] Pre-processing...
[15:51] 1859 MS1 and 28183 MS2 scans in 1859 (inferred) and 1859 (encoded) cycles, 5095220 precursors in range
[15:51] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[16:43] RT window set to 1.49216
[16:43] Recommended MS1 mass accuracy setting: 2.1 ppm
[17:20] Searching decoys
[18:55] Main search
[22:08] Removing low confidence identifications
[22:19] Removing interfering precursors
[22:26] Training neural networks on 103085 target and 81845 decoy PSMs
[22:49] Training neural networks on 103085 target and 80492 decoy PSMs
[23:07] Precursors at 1% peptidoform FDR: 36948
[23:08] Number of IDs at 0.01 FDR: 38416
[23:08] Calculating protein q-values
[23:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[23:09] Quantification
[23:09] Precursors with scored PTMs at 1% FDR: 1619 out of 1739 considered
[23:09] Precursors with all scored PTM sites unoccupied at 1% FDR: 35409
[23:09] Precursors with PTMs localised (when required) with > 90% confidence: 1589 out of 1619
[23:09] 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

[23:10] File #3/6
[23:10] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw
[23:23] Pre-processing...
[23:27] 1856 MS1 and 28105 MS2 scans in 1856 (inferred) and 1856 (encoded) cycles, 5095220 precursors in range
[23:28] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[24:16] RT window set to 1.5579
[24:16] Recommended MS1 mass accuracy setting: 2 ppm
[24:52] Searching decoys
[26:28] Main search
[29:52] Removing low confidence identifications
[30:06] Removing interfering precursors
[30:13] Training neural networks on 99359 target and 78199 decoy PSMs
[30:40] Training neural networks on 99359 target and 76757 decoy PSMs
[31:06] Precursors at 1% peptidoform FDR: 36024
[31:07] Number of IDs at 0.01 FDR: 37732
[31:07] Calculating protein q-values
[31:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[31:07] Quantification
[31:08] Precursors with scored PTMs at 1% FDR: 1735 out of 1902 considered
[31:08] Precursors with all scored PTM sites unoccupied at 1% FDR: 34327
[31:08] Precursors with PTMs localised (when required) with > 90% confidence: 1707 out of 1735
[31:08] 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

[31:08] File #4/6
[31:08] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw
[31:20] Pre-processing...
[31:26] 1827 MS1 and 27525 MS2 scans in 1827 (inferred) and 1827 (encoded) cycles, 5095220 precursors in range
[31:26] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[32:17] RT window set to 1.70983
[32:18] Recommended MS1 mass accuracy setting: 2 ppm
[33:09] Searching decoys
[34:51] Main search
[38:39] Removing low confidence identifications
[38:54] Removing interfering precursors
[39:02] Training neural networks on 85116 target and 65321 decoy PSMs
[39:30] Training neural networks on 85116 target and 63618 decoy PSMs
[39:52] Precursors at 1% peptidoform FDR: 32598
[39:54] Number of IDs at 0.01 FDR: 33897
[39:54] Calculating protein q-values
[39:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[39:54] Quantification
[39:55] Precursors with scored PTMs at 1% FDR: 282 out of 328 considered
[39:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 32549
[39:55] Precursors with PTMs localised (when required) with > 90% confidence: 263 out of 282
[39:55] 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

[39:55] File #5/6
[39:55] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw
[40:07] Pre-processing...
[40:12] 1831 MS1 and 27624 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[40:13] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[41:10] RT window set to 1.49034
[41:10] Recommended MS1 mass accuracy setting: 1.9 ppm
[41:50] Searching decoys
[43:31] Main search
[46:51] Removing low confidence identifications
[47:02] Removing interfering precursors
[47:09] Training neural networks on 92205 target and 72416 decoy PSMs
[47:34] Training neural networks on 92205 target and 71016 decoy PSMs
[47:53] Precursors at 1% peptidoform FDR: 33342
[47:54] Number of IDs at 0.01 FDR: 34944
[47:54] Calculating protein q-values
[47:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[47:55] Quantification
[47:55] Precursors with scored PTMs at 1% FDR: 484 out of 535 considered
[47:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 32982
[47:55] Precursors with PTMs localised (when required) with > 90% confidence: 456 out of 484
[47:55] 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

[47:56] File #6/6
[47:56] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw
[48:07] Pre-processing...
[48:12] 1831 MS1 and 27589 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 5095220 precursors in range
[48:12] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[49:00] RT window set to 1.62455
[49:00] Recommended MS1 mass accuracy setting: 2 ppm
[49:41] Searching decoys
[51:17] Main search
[54:27] Removing low confidence identifications
[54:39] Removing interfering precursors
[54:47] Training neural networks on 87618 target and 67353 decoy PSMs
[55:12] Training neural networks on 87618 target and 66183 decoy PSMs
[55:31] Precursors at 1% peptidoform FDR: 33455
[55:32] Number of IDs at 0.01 FDR: 34588
[55:32] Calculating protein q-values
[55:33] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[55:33] Quantification
[55:33] Precursors with scored PTMs at 1% FDR: 495 out of 537 considered
[55:33] Precursors with all scored PTM sites unoccupied at 1% FDR: 32979
[55:33] Precursors with PTMs localised (when required) with > 90% confidence: 477 out of 495
[55:33] 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

[55:34] Cross-run analysis
[55:34] Reading quantification information: 6 files
[55:51] Target precursors at 1% global q-value: 47684
[55:51] Quantifying peptides
[56:00] Assembling protein groups
[56:01] Quantifying proteins
[56:01] Calculating q-values for protein and gene groups
[56:02] Calculating global q-values for protein and gene groups
[56:03] Protein groups with global q-value <= 0.01: 8259
[56:04] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[56:04] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-first-pass.stats.tsv
[56:04] Generating spectral library:
[56:05] 51815 target and 2888 decoy precursors saved
WARNING: 5577 precursors without any fragments annotated were skipped
[56:05] Spectral library saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-lib.parquet

[56:05] Loading spectral library /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-lib.parquet
[56:06] Spectral library loaded: 11041 protein isoforms, 10904 protein groups and 54703 precursors in 53645 elution groups (targets and decoys).
[56:06] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_DDAQuantification_noecoli.fasta
[56:06] Annotating library proteins with information from the FASTA database
[56:06] Gene names missing for some isoforms
[56:06] Library contains 11036 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[56:06] Initialising library
[56:07] Saving the library to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report-lib.parquet.skyline.speclib


Second pass: using the newly created spectral library to reanalyse the data

[56:07] File #1/6
[56:07] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r1.raw
[56:11] Pre-processing...
[56:11] 1842 MS1 and 27799 MS2 scans in 1842 (inferred) and 1842 (encoded) cycles, 51815 precursors in range
[56:11] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[56:12] RT window set to 0.458638
[56:12] Recommended MS1 mass accuracy setting: 2.2 ppm
[56:13] Searching decoys
[56:13] Main search
[56:14] Removing low confidence identifications
[56:16] Removing interfering precursors
[56:16] Training neural networks on 44970 target and 23809 decoy PSMs
[56:24] Training neural networks on 44905 target and 23422 decoy PSMs
[56:31] Precursors at 1% peptidoform FDR: 34251
[56:31] Number of IDs at 0.01 FDR: 34879
[56:31] Calculating protein q-values
[56:31] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[56:31] Quantification
[56:31] Precursors with scored PTMs at 1% FDR: 690 out of 728 considered
[56:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 33600
[56:31] Precursors with PTMs localised (when required) with > 90% confidence: 673 out of 690

[56:31] File #2/6
[56:31] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r2.raw
[56:36] Pre-processing...
[56:36] 1859 MS1 and 28183 MS2 scans in 1859 (inferred) and 1859 (encoded) cycles, 51815 precursors in range
[56:36] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[56:36] RT window set to 0.45878
[56:36] Recommended MS1 mass accuracy setting: 2.4 ppm
[56:37] Searching decoys
[56:37] Main search
[56:38] Removing low confidence identifications
[56:40] Removing interfering precursors
[56:40] Training neural networks on 45334 target and 24443 decoy PSMs
[56:49] Training neural networks on 45267 target and 23766 decoy PSMs
[56:57] Precursors at 1% peptidoform FDR: 35489
[56:57] Number of IDs at 0.01 FDR: 36268
[56:57] Calculating protein q-values
[56:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[56:57] Quantification
[56:57] Precursors with scored PTMs at 1% FDR: 1292 out of 1364 considered
[56:57] Precursors with all scored PTM sites unoccupied at 1% FDR: 34325
[56:57] Precursors with PTMs localised (when required) with > 90% confidence: 1270 out of 1292

[56:58] File #3/6
[56:58] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_200pg_50pg_H_Y_r3.raw
[57:01] Pre-processing...
[57:02] 1856 MS1 and 28105 MS2 scans in 1856 (inferred) and 1856 (encoded) cycles, 51815 precursors in range
[57:02] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[57:02] RT window set to 0.466492
[57:02] Recommended MS1 mass accuracy setting: 2.4 ppm
[57:03] Searching decoys
[57:03] Main search
[57:04] Removing low confidence identifications
[57:06] Removing interfering precursors
[57:06] Training neural networks on 45386 target and 24348 decoy PSMs
[57:14] Training neural networks on 45329 target and 23984 decoy PSMs
[57:22] Precursors at 1% peptidoform FDR: 34776
[57:22] Number of IDs at 0.01 FDR: 35613
[57:22] Calculating protein q-values
[57:22] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[57:22] Quantification
[57:22] Precursors with scored PTMs at 1% FDR: 1329 out of 1404 considered
[57:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 33524
[57:22] Precursors with PTMs localised (when required) with > 90% confidence: 1313 out of 1329

[57:22] File #4/6
[57:22] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r1.raw
[57:26] Pre-processing...
[57:26] 1827 MS1 and 27525 MS2 scans in 1827 (inferred) and 1827 (encoded) cycles, 51815 precursors in range
[57:26] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[57:26] RT window set to 0.45097
[57:26] Recommended MS1 mass accuracy setting: 2.4 ppm
[57:27] Searching decoys
[57:27] Main search
[57:28] Removing low confidence identifications
[57:29] Removing interfering precursors
[57:30] Training neural networks on 44096 target and 22811 decoy PSMs
[57:36] Training neural networks on 44026 target and 23453 decoy PSMs
[57:42] Precursors at 1% peptidoform FDR: 32858
[57:42] Number of IDs at 0.01 FDR: 33723
[57:42] Calculating protein q-values
[57:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[57:42] Quantification
[57:42] Precursors with scored PTMs at 1% FDR: 637 out of 679 considered
[57:42] Precursors with all scored PTM sites unoccupied at 1% FDR: 32316
[57:42] Precursors with PTMs localised (when required) with > 90% confidence: 610 out of 637

[57:42] File #5/6
[57:42] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r2.raw
[57:46] Pre-processing...
[57:46] 1831 MS1 and 27624 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 51815 precursors in range
[57:46] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[57:47] RT window set to 0.452391
[57:47] Recommended MS1 mass accuracy setting: 2.1 ppm
[57:47] Searching decoys
[57:48] Main search
[57:49] Removing low confidence identifications
[57:51] Removing interfering precursors
[57:51] Training neural networks on 44432 target and 23521 decoy PSMs
[58:00] Training neural networks on 44372 target and 23422 decoy PSMs
[58:07] Precursors at 1% peptidoform FDR: 33274
[58:07] Number of IDs at 0.01 FDR: 33986
[58:07] Calculating protein q-values
[58:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[58:07] Quantification
[58:07] Precursors with scored PTMs at 1% FDR: 719 out of 753 considered
[58:07] Precursors with all scored PTM sites unoccupied at 1% FDR: 32646
[58:07] Precursors with PTMs localised (when required) with > 90% confidence: 696 out of 719

[58:07] File #6/6
[58:07] Loading run /public/local/ProteoBench/HYE_Astral_Single_Cell/20231123_DIA_240k_20Th_40ms_FAIMSCV-48_gas3p8_240pg_10pg_H_Y_r3.raw
[58:11] Pre-processing...
[58:11] 1831 MS1 and 27589 MS2 scans in 1831 (inferred) and 1831 (encoded) cycles, 51815 precursors in range
[58:11] Calibrating with mass accuracies 22 (MS1), 24 (MS2)
[58:11] RT window set to 0.454351
[58:12] Recommended MS1 mass accuracy setting: 2.4 ppm
[58:12] Searching decoys
[58:12] Main search
[58:13] Removing low confidence identifications
[58:15] Removing interfering precursors
[58:15] Training neural networks on 44385 target and 23559 decoy PSMs
[58:23] Training neural networks on 44313 target and 23614 decoy PSMs
[58:30] Precursors at 1% peptidoform FDR: 33184
[58:30] Number of IDs at 0.01 FDR: 34202
[58:30] Calculating protein q-values
[58:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[58:30] Quantification
[58:30] Precursors with scored PTMs at 1% FDR: 694 out of 749 considered
[58:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 32656
[58:30] Precursors with PTMs localised (when required) with > 90% confidence: 672 out of 694

[58:30] Cross-run analysis
[58:30] Reading quantification information: 6 files
[58:31] Target precursors at 1% global q-value: 41712
[58:31] Quantifying peptides
[58:54] Quantification parameters: 0.314825, 0.00230713, 0.0117738, 0.0125167, 0.0124637, 0.0124622, 0.271527, 0.136328, 0.15849, 0.0137285, 0.0148172, 0.014273, 0.287853, 0.10625, 0.14552, 0.0118056
[58:58] Quantifying proteins
[58:58] Calculating q-values for protein and gene groups
[58:58] Calculating global q-values for protein and gene groups
[58:58] Protein groups with global q-value <= 0.01: 7876
[58:59] Compressed report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[58:59] Stats report saved to /home/robbe/PB_output/results/MBRDIANN2.5/HYE_Astral_Single_Cell/diann_v2.5.0/report.stats.tsv

