DIA-NN 1.9.2 (Data-Independent Acquisition by Neural Networks)
Compiled on Oct 31 2024 04:27:44
Current date and time: Wed Apr 16 16:44:01 2025
Logical CPU cores: 128
diann-1.9.2/diann-linux --f Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML --f Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML --f Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML --f /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML --f /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML --f /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML --lib --threads 80 --verbose 1 --out run_output_Astral/diann_1.9.2_linearnn/report.tsv --qvalue 0.01 --gen-spec-lib --predictor --fasta 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 4 --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 --relaxed-prot-inf --rt-profiling --no-nn 

Thread number set to 80
Output will be filtered at 0.01 FDR
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 4
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
A spectral library will be created from the DIA runs and used to reanalyse them; .quant files will only be saved to disk during the first step
Heuristic protein grouping will be used, to reduce the number of protein groups obtained; this mode is recommended for benchmarking protein ID numbers, GO/pathway and system-scale analyses
The spectral library (if generated) will retain the original spectra but will include empirically-aligned RTs
Neural network classifier disabled
DIA-NN will optimise the mass accuracy automatically using the first run in the experiment. This is useful primarily for quick initial analyses, when it is not yet known which mass accuracy setting works best for a particular acquisition scheme.
WARNING: it is strongly recommended to first generate an in silico-predicted library in a separate pipeline step and then use it to process the raw data, now without activating FASTA digest
The following variable modifications will be scored: UniMod:35 UniMod:1 

6 files will be processed
[0:00] Loading FASTA ProteoBenchFASTA_DDAQuantification.fasta
[0:07] Processing FASTA
[0:15] Assembling elution groups
[0:22] 5116692 precursors generated
[0:22] Protein names missing for some isoforms
[0:22] Gene names missing for some isoforms
[0:22] Library contains 31685 proteins, and 0 genes
[0:30] [0:49] [4:30] [5:00] [5:16] [5:18] Saving the library to run_output_Astral/diann_1.9.2_linearnn/report-lib.predicted.speclib
[5:31] Initialising library
[5:44] Loading spectral library run_output_Astral/diann_1.9.2_linearnn/report-lib.predicted.speclib
[5:48] Library annotated with sequence database(s): ProteoBenchFASTA_DDAQuantification.fasta
[5:49] Spectral library loaded: 31837 protein isoforms, 51765 protein groups and 5116692 precursors in 2716663 elution groups.
[5:49] Loading protein annotations from FASTA ProteoBenchFASTA_DDAQuantification.fasta
[5:49] Annotating library proteins with information from the FASTA database
[5:49] Protein names missing for some isoforms
[5:49] Gene names missing for some isoforms
[5:49] Library contains 31685 proteins, and 0 genes
[5:56] Initialising library

First pass: generating a spectral library from DIA data

[6:12] File #1/6
[6:12] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML
[7:04] 5020855 library precursors are potentially detectable
[7:05] Calibrating with mass accuracies 30 (MS1), 20 (MS2)
[7:19] RT window set to 0.920269
[7:19] Peak width: 2.748
[7:19] Scan window radius set to 6
[7:19] Recommended MS1 mass accuracy setting: 2.42372 ppm
[7:48] Optimised mass accuracy: 8.32578 ppm
[8:01] Number of IDs at 0.01 FDR: 3406
[8:02] Number of IDs at 0.01 FDR: 5867
[8:29] Number of IDs at 0.01 FDR: 37167
[8:31] Number of IDs at 0.01 FDR: 65327
[8:31] Removing low confidence identifications
[8:47] Number of IDs at 0.01 FDR: 65327
[8:49] Precursors at 1% peptidoform FDR: 63699
[8:50] Removing interfering precursors
[8:54] Number of IDs at 0.01 FDR: 65413
[8:55] Calculating protein q-values
[8:56] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[8:56] Quantification
[8:56] Precursors with monitored PTMs at 1% FDR: 1834 out of 14058 considered
[8:56] Unmodified precursors with monitored PTM sites at 1% FDR: 11473
[8:56] Precursors with PTMs localised (when required) with > 90% confidence: 1790 out of 1834
[8:57] Quantification information saved to Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML.quant

[8:57] File #2/6
[8:57] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML
[9:45] 5020855 library precursors are potentially detectable
[9:46] Calibrating with mass accuracies 30 (MS1), 18.8642 (MS2)
[9:56] RT window set to 0.836641
[9:56] Recommended MS1 mass accuracy setting: 2.46115 ppm
[10:01] Number of IDs at 0.01 FDR: 1525
[10:01] Number of IDs at 0.01 FDR: 2364
[10:34] Number of IDs at 0.01 FDR: 38115
[10:36] Number of IDs at 0.01 FDR: 65528
[10:36] Removing low confidence identifications
[10:55] Number of IDs at 0.01 FDR: 65528
[10:58] Precursors at 1% peptidoform FDR: 63818
[10:59] Removing interfering precursors
[11:02] Number of IDs at 0.01 FDR: 65344
[11:04] Calculating protein q-values
[11:04] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[11:04] Quantification
[11:05] Precursors with monitored PTMs at 1% FDR: 1901 out of 13940 considered
[11:05] Unmodified precursors with monitored PTM sites at 1% FDR: 11499
[11:05] Precursors with PTMs localised (when required) with > 90% confidence: 1867 out of 1901
[11:06] Quantification information saved to Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML.quant

[11:06] File #3/6
[11:06] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML
[11:49] 5020855 library precursors are potentially detectable
[11:50] Calibrating with mass accuracies 30 (MS1), 18.2063 (MS2)
[12:03] RT window set to 1.05907
[12:03] Recommended MS1 mass accuracy setting: 2.55657 ppm
[12:11] Number of IDs at 0.01 FDR: 1306
[12:11] Number of IDs at 0.01 FDR: 2447
[12:40] Number of IDs at 0.01 FDR: 36248
[12:42] Number of IDs at 0.01 FDR: 66004
[12:42] Removing low confidence identifications
[13:04] Number of IDs at 0.01 FDR: 66004
[13:07] Precursors at 1% peptidoform FDR: 64275
[13:08] Removing interfering precursors
[13:11] Number of IDs at 0.01 FDR: 66158
[13:13] Calculating protein q-values
[13:13] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[13:13] Quantification
[13:13] Precursors with monitored PTMs at 1% FDR: 1914 out of 14188 considered
[13:13] Unmodified precursors with monitored PTM sites at 1% FDR: 11584
[13:14] Precursors with PTMs localised (when required) with > 90% confidence: 1876 out of 1914
[13:15] Quantification information saved to Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML.quant

[13:15] File #4/6
[13:15] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML
[14:06] 5020855 library precursors are potentially detectable
[14:07] Calibrating with mass accuracies 30 (MS1), 18.835 (MS2)
[14:21] RT window set to 1.00069
[14:21] Recommended MS1 mass accuracy setting: 2.49086 ppm
[14:26] Number of IDs at 0.01 FDR: 1462
[14:26] Number of IDs at 0.01 FDR: 2371
[14:53] Number of IDs at 0.01 FDR: 38394
[14:55] Number of IDs at 0.01 FDR: 67111
[14:55] Removing low confidence identifications
[15:11] Number of IDs at 0.01 FDR: 67111
[15:13] Precursors at 1% peptidoform FDR: 65497
[15:14] Removing interfering precursors
[15:17] Number of IDs at 0.01 FDR: 67012
[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)
[15:18] Quantification
[15:19] Precursors with monitored PTMs at 1% FDR: 2431 out of 15015 considered
[15:19] Unmodified precursors with monitored PTM sites at 1% FDR: 12028
[15:19] Precursors with PTMs localised (when required) with > 90% confidence: 2385 out of 2431
[15:20] Quantification information saved to /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML.quant

[15:20] File #5/6
[15:20] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML
[16:11] 5020855 library precursors are potentially detectable
[16:12] Calibrating with mass accuracies 30 (MS1), 19.0138 (MS2)
[16:25] RT window set to 0.825425
[16:25] Recommended MS1 mass accuracy setting: 2.21955 ppm
[16:31] Number of IDs at 0.01 FDR: 1547
[16:32] Number of IDs at 0.01 FDR: 2458
[16:59] Number of IDs at 0.01 FDR: 40023
[17:01] Number of IDs at 0.01 FDR: 66263
[17:01] Removing low confidence identifications
[17:17] Number of IDs at 0.01 FDR: 66263
[17:20] Precursors at 1% peptidoform FDR: 64709
[17:20] Removing interfering precursors
[17:23] Number of IDs at 0.01 FDR: 66512
[17:24] Calculating protein q-values
[17:25] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[17:25] Quantification
[17:26] Precursors with monitored PTMs at 1% FDR: 2298 out of 14868 considered
[17:26] Unmodified precursors with monitored PTM sites at 1% FDR: 11863
[17:26] Precursors with PTMs localised (when required) with > 90% confidence: 2252 out of 2298
[17:27] Quantification information saved to /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML.quant

[17:27] File #6/6
[17:27] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML
[18:13] 5020855 library precursors are potentially detectable
[18:14] Calibrating with mass accuracies 30 (MS1), 18.9828 (MS2)
[18:27] RT window set to 0.887665
[18:27] Recommended MS1 mass accuracy setting: 2.51973 ppm
[18:33] Number of IDs at 0.01 FDR: 1552
[18:34] Number of IDs at 0.01 FDR: 2368
[19:04] Number of IDs at 0.01 FDR: 38955
[19:06] Number of IDs at 0.01 FDR: 66022
[19:06] Removing low confidence identifications
[19:22] Number of IDs at 0.01 FDR: 66022
[19:25] Precursors at 1% peptidoform FDR: 64414
[19:26] Removing interfering precursors
[19:28] Number of IDs at 0.01 FDR: 66237
[19:29] Calculating protein q-values
[19:30] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[19:30] Quantification
[19:30] Precursors with monitored PTMs at 1% FDR: 2265 out of 14773 considered
[19:30] Unmodified precursors with monitored PTM sites at 1% FDR: 11795
[19:30] Precursors with PTMs localised (when required) with > 90% confidence: 2216 out of 2265
[19:31] Quantification information saved to /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML.quant

[19:31] Cross-run analysis
[19:31] Reading quantification information: 6 files
[19:37] Quantifying peptides
[20:05] Assembling protein groups
[20:08] Quantifying proteins
[20:08] Calculating q-values for protein and gene groups
[20:10] Calculating global q-values for protein and gene groups
[20:10] Protein groups with global q-value <= 0.01: 8868
[20:13] Compressed report saved to run_output_Astral/diann_1.9.2_linearnn/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[20:13] Writing report
[20:24] Report saved to run_output_Astral/diann_1.9.2_linearnn/report-first-pass.tsv.
[20:24] Stats report saved to run_output_Astral/diann_1.9.2_linearnn/report-first-pass.stats.tsv
[20:24] Generating spectral library:
[20:26] 83467 target and 842 decoy precursors saved
[20:26] Spectral library saved to run_output_Astral/diann_1.9.2_linearnn/report-lib.parquet

[20:27] Loading spectral library run_output_Astral/diann_1.9.2_linearnn/report-lib.parquet
[20:28] Spectral library loaded: 9962 protein isoforms, 9820 protein groups and 84309 precursors in 79169 elution groups.
[20:28] Loading protein annotations from FASTA ProteoBenchFASTA_DDAQuantification.fasta
[20:28] Annotating library proteins with information from the FASTA database
[20:28] Gene names missing for some isoforms
[20:28] Library contains 9953 proteins, and 0 genes
[20:29] Initialising library
[20:29] Saving the library to run_output_Astral/diann_1.9.2_linearnn/report-lib.parquet.skyline.speclib


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

[20:29] File #1/6
[20:29] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.mzML
[21:19] 83467 library precursors are potentially detectable
[21:19] Calibrating with mass accuracies 30 (MS1), 18.2314 (MS2)
[21:19] RT window set to 0.4067
[21:19] Recommended MS1 mass accuracy setting: 2.32807 ppm
[21:20] Number of IDs at 0.01 FDR: 2750
[21:20] Number of IDs at 0.01 FDR: 3335
[21:21] Number of IDs at 0.01 FDR: 50053
[21:21] Number of IDs at 0.01 FDR: 60531
[21:21] Removing low confidence identifications
[21:21] Number of IDs at 0.01 FDR: 60531
[21:23] Precursors at 1% peptidoform FDR: 59791
[21:23] Removing interfering precursors
[21:24] Number of IDs at 0.01 FDR: 61271
[21:24] Calculating protein q-values
[21:24] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[21:24] Quantification
[21:24] Precursors with monitored PTMs at 1% FDR: 1848 out of 12928 considered
[21:24] Unmodified precursors with monitored PTM sites at 1% FDR: 10753
[21:24] Precursors with PTMs localised (when required) with > 90% confidence: 1824 out of 1848

[21:24] File #2/6
[21:24] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.mzML
[22:21] 83467 library precursors are potentially detectable
[22:21] Calibrating with mass accuracies 30 (MS1), 18.6576 (MS2)
[22:22] RT window set to 0.419114
[22:22] Recommended MS1 mass accuracy setting: 2.42998 ppm
[22:23] Number of IDs at 0.01 FDR: 2582
[22:23] Number of IDs at 0.01 FDR: 3224
[22:24] Number of IDs at 0.01 FDR: 50843
[22:24] Number of IDs at 0.01 FDR: 58149
[22:24] Removing low confidence identifications
[22:25] Number of IDs at 0.01 FDR: 58149
[22:27] Precursors at 1% peptidoform FDR: 57404
[22:27] Removing interfering precursors
[22:27] Number of IDs at 0.01 FDR: 60311
[22:27] Calculating protein q-values
[22:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[22:27] Quantification
[22:28] Precursors with monitored PTMs at 1% FDR: 1791 out of 12726 considered
[22:28] Unmodified precursors with monitored PTM sites at 1% FDR: 10262
[22:28] Precursors with PTMs localised (when required) with > 90% confidence: 1774 out of 1791

[22:28] File #3/6
[22:28] Loading run Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.mzML
[23:14] 83467 library precursors are potentially detectable
[23:14] Calibrating with mass accuracies 30 (MS1), 17.8993 (MS2)
[23:15] RT window set to 0.416229
[23:15] Recommended MS1 mass accuracy setting: 2.58571 ppm
[23:16] Number of IDs at 0.01 FDR: 2641
[23:16] Number of IDs at 0.01 FDR: 3291
[23:17] Number of IDs at 0.01 FDR: 50935
[23:17] Number of IDs at 0.01 FDR: 63229
[23:17] Removing low confidence identifications
[23:18] Number of IDs at 0.01 FDR: 63229
[23:20] Precursors at 1% peptidoform FDR: 62445
[23:20] Removing interfering precursors
[23:21] Number of IDs at 0.01 FDR: 64336
[23:21] Calculating protein q-values
[23:21] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[23:21] Quantification
[23:21] Precursors with monitored PTMs at 1% FDR: 2017 out of 13687 considered
[23:21] Unmodified precursors with monitored PTM sites at 1% FDR: 11212
[23:21] Precursors with PTMs localised (when required) with > 90% confidence: 1990 out of 2017

[23:21] File #4/6
[23:21] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.mzML
[24:04] 83467 library precursors are potentially detectable
[24:04] Calibrating with mass accuracies 30 (MS1), 18.5474 (MS2)
[24:04] RT window set to 0.431517
[24:04] Recommended MS1 mass accuracy setting: 2.54096 ppm
[24:05] Number of IDs at 0.01 FDR: 2706
[24:05] Number of IDs at 0.01 FDR: 3463
[24:06] Number of IDs at 0.01 FDR: 52459
[24:06] Number of IDs at 0.01 FDR: 66652
[24:06] Removing low confidence identifications
[24:07] Number of IDs at 0.01 FDR: 66652
[24:09] Precursors at 1% peptidoform FDR: 65838
[24:09] Removing interfering precursors
[24:10] Number of IDs at 0.01 FDR: 67479
[24:10] Calculating protein q-values
[24:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[24:10] Quantification
[24:10] Precursors with monitored PTMs at 1% FDR: 2327 out of 14733 considered
[24:10] Unmodified precursors with monitored PTM sites at 1% FDR: 12004
[24:10] Precursors with PTMs localised (when required) with > 90% confidence: 2297 out of 2327

[24:10] File #5/6
[24:10] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.mzML
[24:53] 83467 library precursors are potentially detectable
[24:54] Calibrating with mass accuracies 30 (MS1), 18.8842 (MS2)
[24:54] RT window set to 0.443175
[24:54] Recommended MS1 mass accuracy setting: 2.46077 ppm
[24:55] Number of IDs at 0.01 FDR: 2698
[24:55] Number of IDs at 0.01 FDR: 3420
[24:57] Number of IDs at 0.01 FDR: 53083
[24:57] Number of IDs at 0.01 FDR: 66714
[24:57] Removing low confidence identifications
[24:57] Number of IDs at 0.01 FDR: 66714
[25:00] Precursors at 1% peptidoform FDR: 65847
[25:01] Removing interfering precursors
[25:01] Number of IDs at 0.01 FDR: 67708
[25:01] Calculating protein q-values
[25:01] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[25:01] Quantification
[25:02] Precursors with monitored PTMs at 1% FDR: 2358 out of 14753 considered
[25:02] Unmodified precursors with monitored PTM sites at 1% FDR: 11962
[25:02] Precursors with PTMs localised (when required) with > 90% confidence: 2328 out of 2358

[25:02] File #6/6
[25:02] Loading run /home/robbe/ProteoBench_diaPASEF/Raw_Astral/mzmls/LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.mzML
[25:46] 83467 library precursors are potentially detectable
[25:46] Calibrating with mass accuracies 30 (MS1), 18.8235 (MS2)
[25:47] RT window set to 0.435073
[25:47] Recommended MS1 mass accuracy setting: 2.62683 ppm
[25:47] Number of IDs at 0.01 FDR: 2610
[25:47] Number of IDs at 0.01 FDR: 3254
[25:48] Number of IDs at 0.01 FDR: 51851
[25:48] Number of IDs at 0.01 FDR: 62934
[25:48] Removing low confidence identifications
[25:48] Number of IDs at 0.01 FDR: 62934
[25:51] Precursors at 1% peptidoform FDR: 62089
[25:51] Removing interfering precursors
[25:51] Number of IDs at 0.01 FDR: 63852
[25:52] Calculating protein q-values
[25:52] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[25:52] Quantification
[25:52] Precursors with monitored PTMs at 1% FDR: 2165 out of 13930 considered
[25:52] Unmodified precursors with monitored PTM sites at 1% FDR: 11332
[25:52] Precursors with PTMs localised (when required) with > 90% confidence: 2141 out of 2165

[25:52] Cross-run analysis
[25:52] Reading quantification information: 6 files
[25:54] Quantifying peptides
[26:57] Quantification parameters: 0.307051, 0.00169701, 0.0012802, 0.0120702, 0.0123164, 0.0119662, 0.193936, 0.222982, 0.168463, 0.0135014, 0.0373756, 0.0149842, 0.342234, 0.0520621, 0.072659, 0.0125474
[27:08] Quantifying proteins
[27:09] Calculating q-values for protein and gene groups
[27:09] Calculating global q-values for protein and gene groups
[27:09] Protein groups with global q-value <= 0.01: 7801
[27:11] Compressed report saved to run_output_Astral/diann_1.9.2_linearnn/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[27:11] Writing report
[27:23] Report saved to run_output_Astral/diann_1.9.2_linearnn/report.tsv.
[27:23] Stats report saved to run_output_Astral/diann_1.9.2_linearnn/report.stats.tsv

