
DIA-NN 2.2.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on May 29 2025 21:29:29
Current date and time: Fri May 30 17:33:46 2025
CPU: GenuineIntel 13th Gen Intel(R) Core(TM) i9-13900F
SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 
Logical CPU cores: 32
diann.exe --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw  --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw  --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw  --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw  --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw  --f D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw  --lib  --threads 20 --verbose 1 --out D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.parquet --qvalue 0.01 --matrices --out-lib D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.parquet --gen-spec-lib --predictor --fasta D:\Proteobench_manuscript_data\ProteoBenchFASTA_DDAQuantification.fasta --fasta-search --min-fr-mz 50 --max-fr-mz 2000 --met-excision --min-pep-len 6 --max-pep-len 30 --min-pr-mz 400 --max-pr-mz 1000 --min-pr-charge 1 --max-pr-charge 5 --cut K*,R* --missed-cleavages 1 --unimod4 --var-mods 1 --var-mod UniMod:35,15.994915,M --var-mod UniMod:1,42.010565,*n --peptidoforms --reanalyse --rt-profiling 

Thread number set to 20
Output will be filtered at 0.01 FDR
Precursor/protein x samples expression level matrices will be saved along with the main report
A spectral library will be generated
Deep learning will be used to generate a new in silico spectral library from peptides provided
DIA-NN will carry out FASTA digest for in silico lib generation
Min fragment m/z set to 50
Max fragment m/z set to 2000
N-terminal methionine excision enabled
Min peptide length set to 6
Max peptide length set to 30
Min precursor m/z set to 400
Max precursor m/z set to 1000
Min precursor charge set to 1
Max precursor charge set to 5
In silico digest will involve cuts at K*,R*
Maximum number of missed cleavages set to 1
Cysteine carbamidomethylation enabled as a fixed modification
Maximum number of variable modifications set to 1
Modification UniMod:35 with mass delta 15.9949 at M will be considered as variable
Modification UniMod:1 with mass delta 42.0106 at *n will be considered as variable
Peptidoform scoring enabled
MBR enabled; .quant files will only be saved to disk during the first pass
The spectral library (if generated) will retain the original spectra but will include empirically-aligned RTs
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
The following variable modifications will be localised: UniMod:35 UniMod:1 

6 files will be processed
[0:00] Loading FASTA D:\Proteobench_manuscript_data\ProteoBenchFASTA_DDAQuantification.fasta
[0:03] Processing FASTA
[0:05] Assembling elution groups
[0:09] 5116700 precursors generated
[0:09] Protein names missing for some isoforms
[0:09] Gene names missing for some isoforms
[0:09] Library contains 31685 proteins, and 0 genes
[0:11] [0:16] [13:11] [14:47] [14:51] [14:52] Saving the library to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.predicted.speclib
[14:59] Initialising library
[15:08] Loading spectral library D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.predicted.speclib
[15:11] Library annotated with sequence database(s): D:\Proteobench_manuscript_data\ProteoBenchFASTA_DDAQuantification.fasta
[15:11] Spectral library loaded: 31837 protein isoforms, 51765 protein groups and 5116700 precursors in 2716671 elution groups.
[15:11] Loading protein annotations from FASTA D:\Proteobench_manuscript_data\ProteoBenchFASTA_DDAQuantification.fasta
[15:11] Annotating library proteins with information from the FASTA database
[15:11] Protein names missing for some isoforms
[15:11] Gene names missing for some isoforms
[15:11] Library contains 31685 proteins, and 0 genes
[15:14] Initialising library

First pass: generating a spectral library from DIA data

[15:22] File #1/6
[15:22] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[16:15] Pre-processing...
[16:16] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 5020863 precursors in range
[16:17] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[16:37] RT window set to 1.37503
[16:37] Peak width: 2.836
[16:37] Scan window radius set to 6
[16:37] Recommended MS1 mass accuracy setting: 2.8 ppm
[17:04] Optimised mass accuracy: 6 ppm
[17:11] Searching decoys
[17:59] Main search
[19:33] Removing low confidence identifications
[19:46] Removing interfering precursors
[19:54] Training neural networks on 207378 target and 130901 decoy PSMs
[21:46] Training neural networks on 207378 target and 129446 decoy PSMs
[23:29] Number of IDs at 0.01 FDR: 103247
[23:29] Precursors at 1% peptidoform FDR: 100642
[23:30] Calculating protein q-values
[23:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[23:30] Quantification
[23:31] Precursors with scored PTMs at 1% FDR: 3407 out of 3589 considered
[23:31] Precursors with all scored PTM sites unoccupied at 1% FDR: 97235
[23:31] Precursors with PTMs localised (when required) with > 90% confidence: 3302 out of 3407
[23:32] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw.quant

[23:32] File #2/6
[23:32] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[24:23] Pre-processing...
[24:25] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5020863 precursors in range
[24:25] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[24:44] RT window set to 1.23136
[24:44] Recommended MS1 mass accuracy setting: 2.8 ppm
[24:49] Searching decoys
[25:38] Main search
[27:15] Removing low confidence identifications
[27:33] Removing interfering precursors
[27:44] Training neural networks on 219132 target and 137947 decoy PSMs
[30:23] Training neural networks on 219132 target and 136917 decoy PSMs
[32:10] Number of IDs at 0.01 FDR: 106335
[32:11] Precursors at 1% peptidoform FDR: 103046
[32:11] Calculating protein q-values
[32:11] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[32:11] Quantification
[32:12] Precursors with scored PTMs at 1% FDR: 3550 out of 3862 considered
[32:12] Precursors with all scored PTM sites unoccupied at 1% FDR: 99496
[32:12] Precursors with PTMs localised (when required) with > 90% confidence: 3465 out of 3550
[32:13] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw.quant

[32:13] File #3/6
[32:13] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[33:06] Pre-processing...
[33:08] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5020863 precursors in range
[33:08] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[33:31] RT window set to 1.16852
[33:31] Recommended MS1 mass accuracy setting: 2.7 ppm
[33:37] Searching decoys
[34:18] Main search
[35:39] Removing low confidence identifications
[35:53] Removing interfering precursors
[36:02] Training neural networks on 216845 target and 135950 decoy PSMs
[38:06] Training neural networks on 216845 target and 135189 decoy PSMs
[40:03] Number of IDs at 0.01 FDR: 105834
[40:04] Precursors at 1% peptidoform FDR: 103073
[40:04] Calculating protein q-values
[40:05] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[40:05] Quantification
[40:06] Precursors with scored PTMs at 1% FDR: 3575 out of 3792 considered
[40:06] Precursors with all scored PTM sites unoccupied at 1% FDR: 99498
[40:06] Precursors with PTMs localised (when required) with > 90% confidence: 3482 out of 3575
[40:07] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw.quant

[40:07] File #4/6
[40:07] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[41:05] Pre-processing...
[41:06] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5020863 precursors in range
[41:07] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[41:30] RT window set to 1.41965
[41:30] Recommended MS1 mass accuracy setting: 2.9 ppm
[41:36] Searching decoys
[42:27] Main search
[44:04] Removing low confidence identifications
[44:18] Removing interfering precursors
[44:26] Training neural networks on 221345 target and 141460 decoy PSMs
[46:33] Training neural networks on 221345 target and 139625 decoy PSMs
[48:41] Number of IDs at 0.01 FDR: 106379
[48:42] Precursors at 1% peptidoform FDR: 103559
[48:42] Calculating protein q-values
[48:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[48:43] Quantification
[48:44] Precursors with scored PTMs at 1% FDR: 4178 out of 4471 considered
[48:44] Precursors with all scored PTM sites unoccupied at 1% FDR: 99381
[48:44] Precursors with PTMs localised (when required) with > 90% confidence: 4059 out of 4178
[48:44] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw.quant

[48:45] File #5/6
[48:45] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[49:43] Pre-processing...
[49:45] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5020863 precursors in range
[49:45] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[50:08] RT window set to 1.23393
[50:08] Recommended MS1 mass accuracy setting: 2.8 ppm
[50:14] Searching decoys
[50:58] Main search
[52:21] Removing low confidence identifications
[52:35] Removing interfering precursors
[52:43] Training neural networks on 219236 target and 139403 decoy PSMs
[54:47] Training neural networks on 219236 target and 138035 decoy PSMs
[56:47] Number of IDs at 0.01 FDR: 106358
[56:48] Precursors at 1% peptidoform FDR: 103528
[56:48] Calculating protein q-values
[56:48] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[56:48] Quantification
[56:49] Precursors with scored PTMs at 1% FDR: 4158 out of 4467 considered
[56:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 99370
[56:49] Precursors with PTMs localised (when required) with > 90% confidence: 4051 out of 4158
[56:50] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw.quant

[56:50] File #6/6
[56:50] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[57:46] Pre-processing...
[57:48] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 5020863 precursors in range
[57:48] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[58:11] RT window set to 1.1542
[58:11] Recommended MS1 mass accuracy setting: 2.6 ppm
[58:17] Searching decoys
[59:00] Main search
[60:23] Removing low confidence identifications
[60:37] Removing interfering precursors
[60:45] Training neural networks on 217786 target and 136998 decoy PSMs
[62:49] Training neural networks on 217786 target and 136088 decoy PSMs
[64:53] Number of IDs at 0.01 FDR: 106137
[64:54] Precursors at 1% peptidoform FDR: 103217
[64:54] Calculating protein q-values
[64:55] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[64:55] Quantification
[64:56] Precursors with scored PTMs at 1% FDR: 4196 out of 4446 considered
[64:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 99021
[64:56] Precursors with PTMs localised (when required) with > 90% confidence: 4080 out of 4196
[64:57] Quantification information saved to D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw.quant

[64:57] Cross-run analysis
[64:57] Reading quantification information: 6 files
[65:10] Quantifying peptides
[66:57] Assembling protein groups
[66:59] Quantifying proteins
[66:59] Calculating q-values for protein and gene groups
[67:00] Calculating global q-values for protein and gene groups
[67:00] Protein groups with global q-value <= 0.01: 11589
[67:03] Compressed report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[67:03] Site report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report-first-pass.site_report.parquet
[67:03] Saving precursor levels matrix
[67:04] Precursor levels matrix (1% precursor and protein group FDR) saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report-first-pass.pr_matrix.tsv.
[67:04] Manifest saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report-first-pass.manifest.txt
[67:04] Stats report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report-first-pass.stats.tsv
[67:04] Generating spectral library:
[67:06] 136827 target and 1389 decoy precursors saved
[67:06] Spectral library saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.parquet

[67:07] Loading spectral library D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.parquet
[67:08] Spectral library loaded: 13410 protein isoforms, 13260 protein groups and 138216 precursors in 129233 elution groups.
[67:08] Loading protein annotations from FASTA D:\Proteobench_manuscript_data\ProteoBenchFASTA_DDAQuantification.fasta
[67:08] Annotating library proteins with information from the FASTA database
[67:08] Gene names missing for some isoforms
[67:08] Library contains 13400 proteins, and 0 genes
[67:08] Initialising library
[67:09] Saving the library to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\lib.parquet.skyline.speclib


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

[67:09] File #1/6
[67:09] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[68:03] Pre-processing...
[68:04] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 136827 precursors in range
[68:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[68:05] RT window set to 0.433768
[68:05] Recommended MS1 mass accuracy setting: 3.1 ppm
[68:05] Searching decoys
[68:06] Main search
[68:09] Removing low confidence identifications
[68:14] Removing interfering precursors
[68:16] Training neural networks on 119866 target and 58381 decoy PSMs
[69:15] Training neural networks on 119820 target and 63874 decoy PSMs
[70:14] Number of IDs at 0.01 FDR: 116077
[70:14] Precursors at 1% peptidoform FDR: 114137
[70:14] Calculating protein q-values
[70:14] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[70:14] Quantification
[70:15] Precursors with scored PTMs at 1% FDR: 4083 out of 4212 considered
[70:15] Precursors with all scored PTM sites unoccupied at 1% FDR: 110054
[70:15] Precursors with PTMs localised (when required) with > 90% confidence: 3978 out of 4083

[70:16] File #2/6
[70:16] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[70:28] Pre-processing...
[70:29] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 136827 precursors in range
[70:29] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[70:30] RT window set to 0.430524
[70:30] Recommended MS1 mass accuracy setting: 3.2 ppm
[70:30] Searching decoys
[70:31] Main search
[70:34] Removing low confidence identifications
[70:39] Removing interfering precursors
[70:40] Training neural networks on 120197 target and 58341 decoy PSMs
[71:38] Training neural networks on 120134 target and 63935 decoy PSMs
[72:36] Number of IDs at 0.01 FDR: 116604
[72:36] Precursors at 1% peptidoform FDR: 114801
[72:36] Calculating protein q-values
[72:36] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[72:36] Quantification
[72:37] Precursors with scored PTMs at 1% FDR: 4189 out of 4274 considered
[72:37] Precursors with all scored PTM sites unoccupied at 1% FDR: 110612
[72:37] Precursors with PTMs localised (when required) with > 90% confidence: 4081 out of 4189

[72:38] File #3/6
[72:38] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[72:50] Pre-processing...
[72:50] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 136827 precursors in range
[72:50] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[72:51] RT window set to 0.435818
[72:51] Recommended MS1 mass accuracy setting: 3.1 ppm
[72:51] Searching decoys
[72:52] Main search
[72:55] Removing low confidence identifications
[73:00] Removing interfering precursors
[73:01] Training neural networks on 120104 target and 58500 decoy PSMs
[73:57] Training neural networks on 120054 target and 64110 decoy PSMs
[74:53] Number of IDs at 0.01 FDR: 116916
[74:54] Precursors at 1% peptidoform FDR: 115137
[74:54] Calculating protein q-values
[74:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[74:54] Quantification
[74:55] Precursors with scored PTMs at 1% FDR: 4199 out of 4300 considered
[74:55] Precursors with all scored PTM sites unoccupied at 1% FDR: 110938
[74:55] Precursors with PTMs localised (when required) with > 90% confidence: 4092 out of 4199

[74:55] File #4/6
[74:55] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[75:08] Pre-processing...
[75:09] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 136827 precursors in range
[75:09] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[75:10] RT window set to 0.452559
[75:10] Recommended MS1 mass accuracy setting: 3.3 ppm
[75:10] Searching decoys
[75:11] Main search
[75:14] Removing low confidence identifications
[75:19] Removing interfering precursors
[75:20] Training neural networks on 120860 target and 59689 decoy PSMs
[76:19] Training neural networks on 120818 target and 64985 decoy PSMs
[77:17] Number of IDs at 0.01 FDR: 117515
[77:18] Precursors at 1% peptidoform FDR: 115607
[77:18] Calculating protein q-values
[77:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[77:18] Quantification
[77:19] Precursors with scored PTMs at 1% FDR: 4489 out of 4592 considered
[77:19] Precursors with all scored PTM sites unoccupied at 1% FDR: 111118
[77:19] Precursors with PTMs localised (when required) with > 90% confidence: 4377 out of 4489

[77:19] File #5/6
[77:19] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[77:32] Pre-processing...
[77:32] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 136827 precursors in range
[77:32] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[77:33] RT window set to 0.452068
[77:33] Recommended MS1 mass accuracy setting: 3.1 ppm
[77:33] Searching decoys
[77:34] Main search
[77:37] Removing low confidence identifications
[77:42] Removing interfering precursors
[77:44] Training neural networks on 120842 target and 59150 decoy PSMs
[78:40] Training neural networks on 120792 target and 64931 decoy PSMs
[79:38] Number of IDs at 0.01 FDR: 117542
[79:38] Precursors at 1% peptidoform FDR: 115704
[79:38] Calculating protein q-values
[79:38] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[79:38] Quantification
[79:39] Precursors with scored PTMs at 1% FDR: 4528 out of 4614 considered
[79:39] Precursors with all scored PTM sites unoccupied at 1% FDR: 111176
[79:39] Precursors with PTMs localised (when required) with > 90% confidence: 4423 out of 4528

[79:40] File #6/6
[79:40] Loading run D:\Proteobench_manuscript_data\Astral_raw\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[79:52] Pre-processing...
[79:53] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 136827 precursors in range
[79:53] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[79:53] RT window set to 0.449017
[79:53] Recommended MS1 mass accuracy setting: 3.2 ppm
[79:54] Searching decoys
[79:55] Main search
[79:57] Removing low confidence identifications
[80:03] Removing interfering precursors
[80:05] Training neural networks on 120778 target and 58673 decoy PSMs
[81:00] Training neural networks on 120719 target and 64378 decoy PSMs
[81:59] Number of IDs at 0.01 FDR: 117685
[82:00] Precursors at 1% peptidoform FDR: 115513
[82:00] Calculating protein q-values
[82:00] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[82:00] Quantification
[82:01] Precursors with scored PTMs at 1% FDR: 4490 out of 4575 considered
[82:01] Precursors with all scored PTM sites unoccupied at 1% FDR: 111023
[82:01] Precursors with PTMs localised (when required) with > 90% confidence: 4386 out of 4490

[82:01] Cross-run analysis
[82:01] Reading quantification information: 6 files
[82:03] Quantifying peptides
[84:14] Quantification parameters: 0.365357, 0.00136759, 0.0016165, 0.0121193, 0.0118474, 0.0119386, 0.176531, 0.256089, 0.195057, 0.0134159, 0.0329148, 0.0147511, 0.375381, 0.0533513, 0.0793601, 0.0121897
[85:05] Quantifying proteins
[85:05] Calculating q-values for protein and gene groups
[85:05] Calculating global q-values for protein and gene groups
[85:05] Protein groups with global q-value <= 0.01: 11053
[85:08] Compressed report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[85:08] Site report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.site_report.parquet
[85:08] Saving precursor levels matrix
[85:08] Precursor levels matrix (1% precursor and protein group FDR) saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.pr_matrix.tsv.
[85:08] Saving protein group levels matrix
[85:08] Protein groups matrix saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.pg_matrix.tsv.
[85:08] Saving gene group levels matrix
[85:08] Gene groups matrix saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.gg_matrix.tsv.
[85:08] Saving unique genes levels matrix
[85:08] Unique genes matrix saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.unique_genes_matrix.tsv.
[85:08] Manifest saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.manifest.txt
[85:08] Stats report saved to D:\Proteobench_manuscript_data\run_output_Astral\diann_2.2_default\report.stats.tsv

