
DIA-NN 2.3.2 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Jan 22 2026 05:01:57
Current date and time: Tue Aug  4 15:48:57 2026
Logical CPU cores: 128
/usr/diann-2.3.2/diann --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw --f /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw --fasta /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta --out /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report.tsv --temp /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2 --threads 100 --missed-cleavages 1 --min-pep-len 6 --max-pep-len 30 --qvalue 0.01 --protein-qvalue 0.01 --min-pr-charge 1 --max-pr-charge 5 --min-pr-mz 380 --max-pr-mz 980 --min-fr-mz 150 --max-fr-mz 2000 --cut K*,R* --gen-spec-lib --predictor --unimod4 --var-mod UniMod:35,15.994915,M --var-mods 1 --gen-spec-lib --fasta-search --reanalyse 

Thread number set to 100
Maximum number of missed cleavages set to 1
Min peptide length set to 6
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 1
Max precursor charge set to 5
Min precursor m/z set to 380
Max precursor m/z set to 980
Min fragment m/z set to 150
Max fragment m/z set to 2000
In silico digest will involve cuts at K*,R*
A spectral library will be generated
Deep learning will be used to generate a new in silico spectral library from peptides provided
Cysteine carbamidomethylation enabled as a fixed modification
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Maximum number of variable modifications set to 1
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
DIA-NN will automatically optimise the mass accuracy for the first run of the experiment, use this mode for preliminary analyses only
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_MixedSpecies_HYE.fasta
[0:07] Processing FASTA
[0:11] Assembling elution groups
[0:20] 5055014 precursors generated
[0:20] Protein names missing for some isoforms
[0:20] Gene names missing for some isoforms
[0:20] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:31] [0:44] [6:17] [6:58] [7:00] [7:04] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-lib.predicted.speclib
[7:10] Initialising library
[7:27] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-lib.predicted.speclib
[7:31] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:32] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5055014 precursors in 2602499 elution groups.
[7:32] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[7:32] Annotating library proteins with information from the FASTA database
[7:32] Protein names missing for some isoforms
[7:32] Gene names missing for some isoforms
[7:32] Library contains 31685 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[7:38] Initialising library

First pass: generating a spectral library from DIA data

[7:54] File #1/6
[7:54] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[8:18] Pre-processing...
[8:20] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5050223 precursors in range
[8:21] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[8:47] RT window set to 1.11215
[8:47] Peak width: 2.828
[8:47] Scan window radius set to 6
[8:47] Recommended MS1 mass accuracy setting: 2.6 ppm
[9:12] Optimised mass accuracy: 7 ppm
[9:19] Searching decoys
[9:41] Main search
[10:33] Removing low confidence identifications
[10:53] Removing interfering precursors
[11:05] Training neural networks on 214997 target and 134217 decoy PSMs
[12:25] Training neural networks on 214997 target and 135044 decoy PSMs
[14:04] IDs at 0.01 FDR: 103951
[14:05] Precursors at 1% peptidoform FDR: 101925
[14:08] Number of IDs at 0.01 FDR: 106474
[14:08] Calculating protein q-values
[14:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[14:09] Quantification
[14:11] Precursors with scored PTMs at 1% FDR: 2250 out of 2497 considered
[14:11] Precursors with all scored PTM sites unoccupied at 1% FDR: 101025
[14:11] Precursors with PTMs localised (when required) with > 90% confidence: 2163 out of 2250
[14:12] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[14:12] File #2/6
[14:12] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[14:37] Pre-processing...
[14:39] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[14:39] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[14:56] RT window set to 1.16475
[14:56] Recommended MS1 mass accuracy setting: 2.6 ppm
[15:02] Searching decoys
[15:28] Main search
[16:44] Removing low confidence identifications
[17:06] Removing interfering precursors
[17:19] Training neural networks on 221941 target and 136835 decoy PSMs
[18:33] Training neural networks on 221941 target and 138932 decoy PSMs
[19:40] IDs at 0.01 FDR: 107070
[19:40] Precursors at 1% peptidoform FDR: 104301
[19:42] Number of IDs at 0.01 FDR: 109570
[19:42] Calculating protein q-values
[19:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[19:43] Quantification
[19:45] Precursors with scored PTMs at 1% FDR: 2340 out of 2664 considered
[19:45] Precursors with all scored PTM sites unoccupied at 1% FDR: 103053
[19:45] Precursors with PTMs localised (when required) with > 90% confidence: 2256 out of 2340
[19:46] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[19:46] File #3/6
[19:46] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[20:07] Pre-processing...
[20:09] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[20:10] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[20:42] RT window set to 1.24321
[20:42] Recommended MS1 mass accuracy setting: 2.8 ppm
[20:51] Searching decoys
[21:30] Main search
[22:25] Removing low confidence identifications
[22:45] Removing interfering precursors
[22:57] Training neural networks on 220793 target and 136764 decoy PSMs
[24:20] Training neural networks on 220793 target and 138344 decoy PSMs
[25:53] IDs at 0.01 FDR: 107225
[25:54] Precursors at 1% peptidoform FDR: 104377
[25:56] Number of IDs at 0.01 FDR: 110292
[25:56] Calculating protein q-values
[25:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[25:57] Quantification
[25:59] Precursors with scored PTMs at 1% FDR: 2255 out of 2644 considered
[25:59] Precursors with all scored PTM sites unoccupied at 1% FDR: 103397
[25:59] Precursors with PTMs localised (when required) with > 90% confidence: 2175 out of 2255
[26:00] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[26:00] File #4/6
[26:00] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[26:26] Pre-processing...
[26:28] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[26:28] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[26:41] RT window set to 1.46489
[26:41] Recommended MS1 mass accuracy setting: 3.1 ppm
[26:48] Searching decoys
[27:10] Main search
[28:06] Removing low confidence identifications
[28:27] Removing interfering precursors
[28:41] Training neural networks on 221808 target and 139423 decoy PSMs
[30:07] Training neural networks on 221808 target and 140220 decoy PSMs
[31:16] IDs at 0.01 FDR: 108177
[31:17] Precursors at 1% peptidoform FDR: 105581
[31:19] Number of IDs at 0.01 FDR: 110813
[31:19] Calculating protein q-values
[31:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[31:20] Quantification
[31:22] Precursors with scored PTMs at 1% FDR: 2952 out of 3267 considered
[31:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 103907
[31:22] Precursors with PTMs localised (when required) with > 90% confidence: 2844 out of 2952
[31:23] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[31:24] File #5/6
[31:24] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[31:49] Pre-processing...
[31:51] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[31:52] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[32:11] RT window set to 1.27025
[32:11] Recommended MS1 mass accuracy setting: 2.9 ppm
[32:18] Searching decoys
[32:48] Main search
[33:47] Removing low confidence identifications
[34:07] Removing interfering precursors
[34:20] Training neural networks on 220169 target and 138054 decoy PSMs
[35:41] Training neural networks on 220169 target and 139073 decoy PSMs
[36:51] IDs at 0.01 FDR: 107243
[36:52] Precursors at 1% peptidoform FDR: 104951
[36:54] Number of IDs at 0.01 FDR: 110304
[36:54] Calculating protein q-values
[36:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[36:55] Quantification
[36:56] Precursors with scored PTMs at 1% FDR: 3009 out of 3298 considered
[36:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 103383
[36:56] Precursors with PTMs localised (when required) with > 90% confidence: 2907 out of 3009
[36:58] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[36:58] File #6/6
[36:58] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[37:20] Pre-processing...
[37:22] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[37:22] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[37:43] RT window set to 1.2182
[37:43] Recommended MS1 mass accuracy setting: 2.7 ppm
[37:50] Searching decoys
[38:12] Main search
[38:57] Removing low confidence identifications
[39:18] Removing interfering precursors
[39:31] Training neural networks on 219914 target and 135741 decoy PSMs
[40:28] Training neural networks on 219914 target and 137699 decoy PSMs
[41:23] IDs at 0.01 FDR: 108645
[41:24] Precursors at 1% peptidoform FDR: 105271
[41:26] Number of IDs at 0.01 FDR: 110630
[41:26] Calculating protein q-values
[41:26] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[41:27] Quantification
[41:28] Precursors with scored PTMs at 1% FDR: 2892 out of 3319 considered
[41:28] Precursors with all scored PTM sites unoccupied at 1% FDR: 103119
[41:28] Precursors with PTMs localised (when required) with > 90% confidence: 2786 out of 2892
[41:30] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[41:30] Cross-run analysis
[41:30] Reading quantification information: 6 files
[41:52] Quantifying peptides
[42:54] Assembling protein groups
[42:59] Quantifying proteins
[42:59] Calculating q-values for protein and gene groups
[43:03] Calculating global q-values for protein and gene groups
[43:03] Protein groups with global q-value <= 0.01: 11560
[43:08] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[43:08] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-first-pass.stats.tsv
[43:09] Generating spectral library:
[43:12] 129136 target and 1163 decoy precursors saved
WARNING: 11627 precursors without any fragments annotated were skipped
[43:12] Spectral library saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-lib.parquet

[43:14] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-lib.parquet
[43:15] Spectral library loaded: 12550 protein isoforms, 12416 protein groups and 130299 precursors in 121472 elution groups.
[43:15] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[43:16] Annotating library proteins with information from the FASTA database
[43:16] Gene names missing for some isoforms
[43:16] Library contains 12540 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[43:16] Initialising library
[43:18] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report-lib.parquet.skyline.speclib


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

[43:19] File #1/6
[43:19] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[43:46] Pre-processing...
[43:47] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 129136 precursors in range
[43:47] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[43:48] RT window set to 0.428038
[43:48] Recommended MS1 mass accuracy setting: 3.2 ppm
[43:48] Searching decoys
[43:49] Main search
[43:51] Removing low confidence identifications
[43:54] Removing interfering precursors
[43:56] Training neural networks on 102847 target and 50109 decoy PSMs
[44:17] Training neural networks on 102828 target and 57783 decoy PSMs
[44:39] IDs at 0.01 FDR: 98411
[44:39] Precursors at 1% peptidoform FDR: 97411
[44:39] Number of IDs at 0.01 FDR: 98859
[44:39] Calculating protein q-values
[44:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[44:39] Quantification
[44:40] Precursors with scored PTMs at 1% FDR: 2284 out of 2353 considered
[44:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 95445
[44:40] Precursors with PTMs localised (when required) with > 90% confidence: 2200 out of 2284

[44:40] File #2/6
[44:40] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[45:02] Pre-processing...
[45:03] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 129136 precursors in range
[45:03] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[45:04] RT window set to 0.432158
[45:04] Recommended MS1 mass accuracy setting: 3.2 ppm
[45:04] Searching decoys
[45:04] Main search
[45:06] Removing low confidence identifications
[45:11] Removing interfering precursors
[45:13] Training neural networks on 103249 target and 50628 decoy PSMs
[45:33] Training neural networks on 103226 target and 58329 decoy PSMs
[46:00] IDs at 0.01 FDR: 98886
[46:00] Precursors at 1% peptidoform FDR: 97866
[46:00] Number of IDs at 0.01 FDR: 99358
[46:00] Calculating protein q-values
[46:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[46:00] Quantification
[46:02] Precursors with scored PTMs at 1% FDR: 2329 out of 2381 considered
[46:02] Precursors with all scored PTM sites unoccupied at 1% FDR: 95902
[46:02] Precursors with PTMs localised (when required) with > 90% confidence: 2257 out of 2329

[46:02] File #3/6
[46:02] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[46:28] Pre-processing...
[46:29] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 129136 precursors in range
[46:29] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[46:29] RT window set to 0.433378
[46:29] Recommended MS1 mass accuracy setting: 3 ppm
[46:30] Searching decoys
[46:30] Main search
[46:32] Removing low confidence identifications
[46:36] Removing interfering precursors
[46:38] Training neural networks on 103394 target and 51688 decoy PSMs
[47:04] Training neural networks on 103370 target and 58817 decoy PSMs
[47:28] IDs at 0.01 FDR: 99376
[47:28] Precursors at 1% peptidoform FDR: 98478
[47:29] Number of IDs at 0.01 FDR: 100017
[47:29] Calculating protein q-values
[47:29] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[47:29] Quantification
[47:30] Precursors with scored PTMs at 1% FDR: 2369 out of 2414 considered
[47:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 96575
[47:30] Precursors with PTMs localised (when required) with > 90% confidence: 2283 out of 2369

[47:30] File #4/6
[47:30] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[47:56] Pre-processing...
[47:57] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 129136 precursors in range
[47:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[47:58] RT window set to 0.459559
[47:58] Recommended MS1 mass accuracy setting: 3.2 ppm
[47:58] Searching decoys
[47:59] Main search
[48:01] Removing low confidence identifications
[48:04] Removing interfering precursors
[48:07] Training neural networks on 103854 target and 52015 decoy PSMs
[48:29] Training neural networks on 103836 target and 59158 decoy PSMs
[48:52] IDs at 0.01 FDR: 100506
[48:53] Precursors at 1% peptidoform FDR: 99261
[48:53] Number of IDs at 0.01 FDR: 101007
[48:53] Calculating protein q-values
[48:53] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[48:53] Quantification
[48:54] Precursors with scored PTMs at 1% FDR: 2614 out of 2660 considered
[48:54] Precursors with all scored PTM sites unoccupied at 1% FDR: 96995
[48:54] Precursors with PTMs localised (when required) with > 90% confidence: 2531 out of 2614

[48:55] File #5/6
[48:55] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[49:19] Pre-processing...
[49:21] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 129136 precursors in range
[49:21] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[49:21] RT window set to 0.458466
[49:21] Recommended MS1 mass accuracy setting: 3 ppm
[49:22] Searching decoys
[49:22] Main search
[49:24] Removing low confidence identifications
[49:28] Removing interfering precursors
[49:30] Training neural networks on 103852 target and 51792 decoy PSMs
[49:53] Training neural networks on 103838 target and 59199 decoy PSMs
[50:15] IDs at 0.01 FDR: 100801
[50:16] Precursors at 1% peptidoform FDR: 99819
[50:16] Number of IDs at 0.01 FDR: 101332
[50:16] Calculating protein q-values
[50:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[50:16] Quantification
[50:17] Precursors with scored PTMs at 1% FDR: 2681 out of 2732 considered
[50:17] Precursors with all scored PTM sites unoccupied at 1% FDR: 97513
[50:17] Precursors with PTMs localised (when required) with > 90% confidence: 2593 out of 2681

[50:18] File #6/6
[50:18] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[50:42] Pre-processing...
[50:43] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 129136 precursors in range
[50:43] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[50:44] RT window set to 0.457848
[50:44] Recommended MS1 mass accuracy setting: 3.1 ppm
[50:44] Searching decoys
[50:45] Main search
[50:46] Removing low confidence identifications
[50:51] Removing interfering precursors
[50:53] Training neural networks on 103844 target and 51220 decoy PSMs
[51:14] Training neural networks on 103828 target and 58975 decoy PSMs
[51:38] IDs at 0.01 FDR: 100737
[51:38] Precursors at 1% peptidoform FDR: 99600
[51:38] Number of IDs at 0.01 FDR: 101233
[51:38] Calculating protein q-values
[51:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[51:38] Quantification
[51:39] Precursors with scored PTMs at 1% FDR: 2644 out of 2692 considered
[51:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 97320
[51:39] Precursors with PTMs localised (when required) with > 90% confidence: 2563 out of 2644

[51:40] Cross-run analysis
[51:40] Reading quantification information: 6 files
[51:43] Quantifying peptides
[53:07] Quantification parameters: 0.30749, 0.00144607, 0.00137765, 0.0117267, 0.0117065, 0.0118253, 0.122009, 0.207017, 0.160713, 0.0129193, 0.0340809, 0.0144362, 0.285673, 0.0523486, 0.0725713, 0.0118248
[53:25] Quantifying proteins
[53:25] Calculating q-values for protein and gene groups
[53:26] Calculating global q-values for protein and gene groups
[53:26] Protein groups with global q-value <= 0.01: 10555
[53:31] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[53:31] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.3.2/report.stats.tsv

