
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 15:05:00
Current date and time: Tue Aug  4 14:24:34 2026
Logical CPU cores: 128
/usr/diann-2.2.0/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_v2.2.0/report.tsv --temp /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0 --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
[0:10] Processing FASTA
[0:13] Assembling elution groups
[0:23] 5055014 precursors generated
[0:23] Protein names missing for some isoforms
[0:23] Gene names missing for some isoforms
[0:23] Library contains 31685 proteins, and 0 genes
[0:36] [0:57] [25:10] [26:39] [26:45] [26:49] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-lib.predicted.speclib
[26:54] Initialising library
[27:10] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-lib.predicted.speclib
[27:14] Library annotated with sequence database(s): /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[27:15] Spectral library loaded: 31837 protein isoforms, 51483 protein groups and 5055014 precursors in 2602499 elution groups.
[27:15] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[27:15] Annotating library proteins with information from the FASTA database
[27:15] Protein names missing for some isoforms
[27:15] Gene names missing for some isoforms
[27:15] Library contains 31685 proteins, and 0 genes
[27:21] Initialising library

First pass: generating a spectral library from DIA data

[27:36] File #1/6
[27:36] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[28:01] Pre-processing...
[28:03] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5050223 precursors in range
[28:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[28:32] RT window set to 1.18418
[28:32] Peak width: 2.868
[28:32] Scan window radius set to 6
[28:32] Recommended MS1 mass accuracy setting: 2.5 ppm
[29:05] Optimised mass accuracy: 7 ppm
[29:16] Searching decoys
[30:02] Main search
[31:39] Removing low confidence identifications
[32:02] Removing interfering precursors
[32:16] Training neural networks on 217351 target and 133402 decoy PSMs
[34:39] Training neural networks on 217351 target and 135597 decoy PSMs
[36:36] Number of IDs at 0.01 FDR: 105397
[36:37] Precursors at 1% peptidoform FDR: 102853
[36:38] Calculating protein q-values
[36:39] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[36:39] Quantification
[36:40] Precursors with scored PTMs at 1% FDR: 2209 out of 2404 considered
[36:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 100644
[36:40] Precursors with PTMs localised (when required) with > 90% confidence: 2123 out of 2209
[36:41] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[36:41] File #2/6
[36:41] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[37:06] Pre-processing...
[37:08] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[37:09] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[37:39] RT window set to 1.17452
[37:40] Recommended MS1 mass accuracy setting: 2.8 ppm
[37:49] Searching decoys
[38:49] Main search
[40:00] Removing low confidence identifications
[40:19] Removing interfering precursors
[40:30] Training neural networks on 218455 target and 133825 decoy PSMs
[42:02] Training neural networks on 218455 target and 135952 decoy PSMs
[43:13] Number of IDs at 0.01 FDR: 107112
[43:14] Precursors at 1% peptidoform FDR: 104335
[43:15] Calculating protein q-values
[43:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[43:16] Quantification
[43:18] Precursors with scored PTMs at 1% FDR: 2318 out of 2516 considered
[43:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 102017
[43:18] Precursors with PTMs localised (when required) with > 90% confidence: 2238 out of 2318
[43:19] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[43:19] File #3/6
[43:19] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[43:42] Pre-processing...
[43:45] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[43:45] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[44:08] RT window set to 1.19014
[44:09] Recommended MS1 mass accuracy setting: 2.8 ppm
[44:15] Searching decoys
[45:00] Main search
[46:17] Removing low confidence identifications
[46:38] Removing interfering precursors
[46:51] Training neural networks on 220574 target and 136212 decoy PSMs
[48:31] Training neural networks on 220574 target and 138186 decoy PSMs
[49:44] Number of IDs at 0.01 FDR: 107744
[49:45] Precursors at 1% peptidoform FDR: 104673
[49:47] Calculating protein q-values
[49:47] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[49:47] Quantification
[49:49] Precursors with scored PTMs at 1% FDR: 2326 out of 2517 considered
[49:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 102347
[49:49] Precursors with PTMs localised (when required) with > 90% confidence: 2242 out of 2326
[49:50] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[49:50] File #4/6
[49:50] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[50:12] Pre-processing...
[50:14] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[50:15] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[50:34] RT window set to 1.26624
[50:35] Recommended MS1 mass accuracy setting: 3 ppm
[50:43] Searching decoys
[51:25] Main search
[53:05] Removing low confidence identifications
[53:26] Removing interfering precursors
[53:38] Training neural networks on 221862 target and 139531 decoy PSMs
[55:16] Training neural networks on 221862 target and 140425 decoy PSMs
[56:54] Number of IDs at 0.01 FDR: 107308
[56:55] Precursors at 1% peptidoform FDR: 104003
[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)
[56:58] Quantification
[56:59] Precursors with scored PTMs at 1% FDR: 2826 out of 3137 considered
[56:59] Precursors with all scored PTM sites unoccupied at 1% FDR: 101177
[56:59] Precursors with PTMs localised (when required) with > 90% confidence: 2725 out of 2826
[57:00] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[57:00] File #5/6
[57:00] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[57:25] Pre-processing...
[57:27] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[57:28] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[57:48] RT window set to 1.45421
[57:48] Recommended MS1 mass accuracy setting: 3 ppm
[57:55] Searching decoys
[58:31] Main search
[59:24] Removing low confidence identifications
[59:43] Removing interfering precursors
[59:55] Training neural networks on 220704 target and 137859 decoy PSMs
[61:23] Training neural networks on 220704 target and 138898 decoy PSMs
[62:51] Number of IDs at 0.01 FDR: 108763
[62:52] Precursors at 1% peptidoform FDR: 105279
[62:53] Calculating protein q-values
[62:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[62:54] Quantification
[62:55] Precursors with scored PTMs at 1% FDR: 2884 out of 3203 considered
[62:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 102395
[62:55] Precursors with PTMs localised (when required) with > 90% confidence: 2796 out of 2884
[62:56] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[62:56] File #6/6
[62:56] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[63:20] Pre-processing...
[63:21] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5050223 precursors in range
[63:22] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[63:48] RT window set to 1.17589
[63:48] Recommended MS1 mass accuracy setting: 2.6 ppm
[63:57] Searching decoys
[64:40] Main search
[65:55] Removing low confidence identifications
[66:16] Removing interfering precursors
[66:30] Training neural networks on 220598 target and 136880 decoy PSMs
[67:48] Training neural networks on 220598 target and 138709 decoy PSMs
[68:54] Number of IDs at 0.01 FDR: 108423
[68:55] Precursors at 1% peptidoform FDR: 104858
[68:57] Calculating protein q-values
[68:57] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[68:58] Quantification
[68:59] Precursors with scored PTMs at 1% FDR: 2899 out of 3188 considered
[68:59] Precursors with all scored PTM sites unoccupied at 1% FDR: 101959
[68:59] Precursors with PTMs localised (when required) with > 90% confidence: 2796 out of 2899
[69:00] Quantification information saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/_public_local_ProteoBench_HYE_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[69:00] Cross-run analysis
[69:00] Reading quantification information: 6 files
[69:20] Quantifying peptides
[74:16] Assembling protein groups
[74:20] Quantifying proteins
[74:21] Calculating q-values for protein and gene groups
[74:23] Calculating global q-values for protein and gene groups
[74:24] Protein groups with global q-value <= 0.01: 11563
[74:29] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[74:29] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-first-pass.stats.tsv
[74:29] Generating spectral library:
[74:32] 134001 target and 1221 decoy precursors saved
WARNING: 4143 precursors without any fragments annotated were skipped
[74:32] Spectral library saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-lib.parquet

[74:36] Loading spectral library /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-lib.parquet
[74:38] Spectral library loaded: 13169 protein isoforms, 13009 protein groups and 135222 precursors in 125896 elution groups.
[74:38] Loading protein annotations from FASTA /public/local/ProteoBench/fastas/ProteoBenchFASTA_MixedSpecies_HYE.fasta
[74:38] Annotating library proteins with information from the FASTA database
[74:38] Gene names missing for some isoforms
[74:38] Library contains 13158 proteins, and 0 genes
[74:38] Initialising library
[74:41] Saving the library to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report-lib.parquet.skyline.speclib


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

[74:41] File #1/6
[74:41] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[75:04] Pre-processing...
[75:05] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 134001 precursors in range
[75:05] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[75:06] RT window set to 0.432443
[75:06] Recommended MS1 mass accuracy setting: 3.4 ppm
[75:06] Searching decoys
[75:07] Main search
[75:09] Removing low confidence identifications
[75:14] Removing interfering precursors
[75:17] Training neural networks on 115816 target and 57519 decoy PSMs
[75:54] Training neural networks on 115761 target and 64266 decoy PSMs
[76:27] Number of IDs at 0.01 FDR: 110564
[76:27] Precursors at 1% peptidoform FDR: 109160
[76:27] Calculating protein q-values
[76:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[76:27] Quantification
[76:29] Precursors with scored PTMs at 1% FDR: 2562 out of 2625 considered
[76:29] Precursors with all scored PTM sites unoccupied at 1% FDR: 106598
[76:29] Precursors with PTMs localised (when required) with > 90% confidence: 2475 out of 2562

[76:29] File #2/6
[76:29] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[76:51] Pre-processing...
[76:53] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 134001 precursors in range
[76:53] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[76:53] RT window set to 0.436897
[76:53] Recommended MS1 mass accuracy setting: 3.3 ppm
[76:54] Searching decoys
[76:55] Main search
[76:57] Removing low confidence identifications
[77:02] Removing interfering precursors
[77:05] Training neural networks on 116133 target and 57702 decoy PSMs
[77:45] Training neural networks on 116075 target and 64152 decoy PSMs
[78:22] Number of IDs at 0.01 FDR: 112135
[78:23] Precursors at 1% peptidoform FDR: 110773
[78:23] Calculating protein q-values
[78:23] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[78:23] Quantification
[78:24] Precursors with scored PTMs at 1% FDR: 2611 out of 2670 considered
[78:24] Precursors with all scored PTM sites unoccupied at 1% FDR: 108162
[78:24] Precursors with PTMs localised (when required) with > 90% confidence: 2539 out of 2611

[78:25] File #3/6
[78:25] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[78:47] Pre-processing...
[78:49] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 134001 precursors in range
[78:49] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[78:49] RT window set to 0.432607
[78:49] Recommended MS1 mass accuracy setting: 3.6 ppm
[78:50] Searching decoys
[78:51] Main search
[78:54] Removing low confidence identifications
[78:59] Removing interfering precursors
[79:02] Training neural networks on 116053 target and 57450 decoy PSMs
[79:45] Training neural networks on 116001 target and 64302 decoy PSMs
[80:27] Number of IDs at 0.01 FDR: 112176
[80:27] Precursors at 1% peptidoform FDR: 111005
[80:28] Calculating protein q-values
[80:28] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[80:28] Quantification
[80:29] Precursors with scored PTMs at 1% FDR: 2654 out of 2712 considered
[80:29] Precursors with all scored PTM sites unoccupied at 1% FDR: 108351
[80:29] Precursors with PTMs localised (when required) with > 90% confidence: 2566 out of 2654

[80:30] File #4/6
[80:30] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[80:53] Pre-processing...
[80:54] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 134001 precursors in range
[80:54] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[80:55] RT window set to 0.44759
[80:55] Recommended MS1 mass accuracy setting: 3.4 ppm
[80:55] Searching decoys
[80:56] Main search
[80:59] Removing low confidence identifications
[81:04] Removing interfering precursors
[81:07] Training neural networks on 116690 target and 58279 decoy PSMs
[81:54] Training neural networks on 116635 target and 64974 decoy PSMs
[82:38] Number of IDs at 0.01 FDR: 112128
[82:38] Precursors at 1% peptidoform FDR: 111088
[82:38] Calculating protein q-values
[82:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[82:39] Quantification
[82:40] Precursors with scored PTMs at 1% FDR: 2895 out of 2935 considered
[82:40] Precursors with all scored PTM sites unoccupied at 1% FDR: 108193
[82:40] Precursors with PTMs localised (when required) with > 90% confidence: 2807 out of 2895

[82:40] File #5/6
[82:40] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[83:03] Pre-processing...
[83:04] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 134001 precursors in range
[83:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[83:05] RT window set to 0.448183
[83:05] Recommended MS1 mass accuracy setting: 3.4 ppm
[83:06] Searching decoys
[83:07] Main search
[83:09] Removing low confidence identifications
[83:15] Removing interfering precursors
[83:17] Training neural networks on 116772 target and 57996 decoy PSMs
[83:48] Training neural networks on 116709 target and 64817 decoy PSMs
[84:17] Number of IDs at 0.01 FDR: 112868
[84:17] Precursors at 1% peptidoform FDR: 111575
[84:17] Calculating protein q-values
[84:17] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[84:17] Quantification
[84:18] Precursors with scored PTMs at 1% FDR: 2929 out of 2965 considered
[84:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 108646
[84:18] Precursors with PTMs localised (when required) with > 90% confidence: 2836 out of 2929

[84:19] File #6/6
[84:19] Loading run /public/local/ProteoBench/HYE_Astral/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[84:43] Pre-processing...
[84:44] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 134001 precursors in range
[84:44] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[84:45] RT window set to 0.449618
[84:45] Recommended MS1 mass accuracy setting: 3.4 ppm
[84:46] Searching decoys
[84:46] Main search
[84:49] Removing low confidence identifications
[84:55] Removing interfering precursors
[84:57] Training neural networks on 116526 target and 57836 decoy PSMs
[85:40] Training neural networks on 116474 target and 64681 decoy PSMs
[86:28] Number of IDs at 0.01 FDR: 112612
[86:29] Precursors at 1% peptidoform FDR: 111465
[86:29] Calculating protein q-values
[86:29] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[86:29] Quantification
[86:30] Precursors with scored PTMs at 1% FDR: 2939 out of 2971 considered
[86:30] Precursors with all scored PTM sites unoccupied at 1% FDR: 108526
[86:30] Precursors with PTMs localised (when required) with > 90% confidence: 2852 out of 2939

[86:31] Cross-run analysis
[86:31] Reading quantification information: 6 files
[86:35] Quantifying peptides
[90:07] Quantification parameters: 0.323363, 0.00138453, 0.00140167, 0.012067, 0.0116718, 0.012045, 0.136697, 0.230728, 0.170318, 0.0132503, 0.0362069, 0.0145567, 0.325887, 0.0523487, 0.0734779, 0.0116277
[91:49] Quantifying proteins
[91:50] Calculating q-values for protein and gene groups
[91:50] Calculating global q-values for protein and gene groups
[91:50] Protein groups with global q-value <= 0.01: 11030
[91:55] Compressed report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[91:55] Stats report saved to /home/robbe/PB_output/results/Astral_DIANN_version_comparison/HYE_Astral/diann_v2.2.0/report.stats.tsv

