
DIA-NN 2.1.0 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Mar 25 2025 10:59:54
Current date and time: Fri May 23 09:44:59 2025
CPU: AuthenticAMD AMD EPYC 9454 48-Core Processor
SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 SSE4a 
Logical CPU cores: 20
diann.exe --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw  --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw  --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw  --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw  --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw  --f S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw  --lib S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.predicted.speclib --threads 20 --verbose 1 --out S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.parquet --qvalue 0.01 --matrices --temp S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral --out-lib S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.parquet --gen-spec-lib --reannotate --fasta S:\Proteomics\PRC\PRCRT-336\proteobench\Module_2_DDA_quantification\FASTA\ProteoBenchFASTA_DDAQuantification.fasta --met-excision --min-pep-len 7 --max-pep-len 30 --min-pr-mz 380 --max-pr-mz 980 --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 --mass-acc 20 --mass-acc-ms1 10 --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
Library precursors will be reannotated using the FASTA database
N-terminal methionine excision enabled
Min peptide length set to 7
Max peptide length set to 30
Min precursor m/z set to 380
Max precursor m/z set to 980
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
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
WARNING: for DIA-NN to switch to the new .raw reader library, please download and install .NET Runtime 8.0.14 or later https://dotnet.microsoft.com/en-us/download/dotnet/8.0
Mass accuracy will be fixed to 2e-05 (MS2) and 1e-05 (MS1)
The following variable modifications will be localised: UniMod:35 

6 files will be processed
[0:00] Loading spectral library S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.predicted.speclib
[0:34] Library annotated with sequence database(s): S:\Proteomics\PRC\PRCRT-336\proteobench\Module_2_DDA_quantification\FASTA\ProteoBenchFASTA_DDAQuantification.fasta
[0:35] Spectral library loaded: 31829 protein isoforms, 42346 protein groups and 4884377 precursors in 2455327 elution groups.
[0:35] Loading FASTA S:\Proteomics\PRC\PRCRT-336\proteobench\Module_2_DDA_quantification\FASTA\ProteoBenchFASTA_DDAQuantification.fasta
[1:03] Reannotating library precursors with information from the FASTA database
[1:07] Finding proteotypic peptides (assuming that the list of UniProt ids provided for each peptide is complete)
[1:07] 4884377 precursors generated
[1:07] Protein names missing for some isoforms
[1:07] Gene names missing for some isoforms
[1:07] Library contains 31678 proteins, and 0 genes
[1:11] Initialising library

First pass: generating a spectral library from DIA data

[1:28] File #1/6
[1:28] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[3:11] Pre-processing...
[3:16] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 4880737 precursors in range
[3:21] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[3:54] RT window set to 1.34183
[3:54] Peak width: 2.716
[3:54] Scan window radius set to 5
[3:54] Recommended MS1 mass accuracy setting: 2.5 ppm
[4:23] Searching decoys
[5:29] Main search
[7:35] Removing low confidence identifications
[7:51] Removing interfering precursors
[8:02] Training neural networks on 168116 target and 109965 decoy PSMs
[9:12] Training neural networks on 168116 target and 109568 decoy PSMs
[10:14] Number of IDs at 0.01 FDR: 97145
[10:15] Precursors at 1% peptidoform FDR: 94907
[10:16] Calculating protein q-values
[10:16] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[10:16] Quantification
[10:18] Precursors with scored PTMs at 1% FDR: 2100 out of 2277 considered
[10:18] Precursors with all scored PTM sites unoccupied at 1% FDR: 92807
[10:18] Precursors with PTMs localised (when required) with > 90% confidence: 2037 out of 2100
[12:17] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP1_raw.quant

[12:17] File #2/6
[12:17] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[14:31] Pre-processing...
[14:35] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4880737 precursors in range
[14:41] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[15:15] RT window set to 1.19268
[15:15] Recommended MS1 mass accuracy setting: 2.4 ppm
[15:43] Searching decoys
[16:44] Main search
[18:39] Removing low confidence identifications
[18:55] Removing interfering precursors
[19:05] Training neural networks on 172025 target and 112758 decoy PSMs
[20:16] Training neural networks on 172025 target and 112196 decoy PSMs
[21:20] Number of IDs at 0.01 FDR: 97828
[21:21] Precursors at 1% peptidoform FDR: 95452
[21:22] Calculating protein q-values
[21:22] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[21:22] Quantification
[21:24] Precursors with scored PTMs at 1% FDR: 2187 out of 2359 considered
[21:24] Precursors with all scored PTM sites unoccupied at 1% FDR: 93265
[21:24] Precursors with PTMs localised (when required) with > 90% confidence: 2117 out of 2187
[23:33] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP2_raw.quant

[23:33] File #3/6
[23:33] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[25:27] Pre-processing...
[25:31] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4880737 precursors in range
[25:37] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[26:10] RT window set to 1.30337
[26:10] Recommended MS1 mass accuracy setting: 2.4 ppm
[26:42] Searching decoys
[27:49] Main search
[29:54] Removing low confidence identifications
[30:11] Removing interfering precursors
[30:21] Training neural networks on 170100 target and 111955 decoy PSMs
[31:31] Training neural networks on 170100 target and 111292 decoy PSMs
[32:34] Number of IDs at 0.01 FDR: 98145
[32:35] Precursors at 1% peptidoform FDR: 96061
[32:36] Calculating protein q-values
[32:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[32:37] Quantification
[32:38] Precursors with scored PTMs at 1% FDR: 2165 out of 2307 considered
[32:38] Precursors with all scored PTM sites unoccupied at 1% FDR: 93896
[32:38] Precursors with PTMs localised (when required) with > 90% confidence: 2095 out of 2165
[34:42] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_A_REP3_raw.quant

[34:42] File #4/6
[34:42] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[36:38] Pre-processing...
[36:42] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4880737 precursors in range
[36:47] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[37:20] RT window set to 1.25239
[37:20] Recommended MS1 mass accuracy setting: 2.7 ppm
[37:53] Searching decoys
[38:57] Main search
[40:58] Removing low confidence identifications
[41:14] Removing interfering precursors
[41:24] Training neural networks on 174209 target and 115679 decoy PSMs
[42:36] Training neural networks on 174209 target and 114616 decoy PSMs
[43:40] Number of IDs at 0.01 FDR: 98220
[43:41] Precursors at 1% peptidoform FDR: 96092
[43:42] Calculating protein q-values
[43:42] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[43:42] Quantification
[43:44] Precursors with scored PTMs at 1% FDR: 2732 out of 2902 considered
[43:44] Precursors with all scored PTM sites unoccupied at 1% FDR: 93360
[43:44] Precursors with PTMs localised (when required) with > 90% confidence: 2639 out of 2732
[44:57] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP1_raw.quant

[44:57] File #5/6
[44:57] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[47:01] Pre-processing...
[47:06] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4880737 precursors in range
[47:11] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[47:44] RT window set to 1.16664
[47:44] Recommended MS1 mass accuracy setting: 2.7 ppm
[48:16] Searching decoys
[49:16] Main search
[51:09] Removing low confidence identifications
[51:26] Removing interfering precursors
[51:36] Training neural networks on 171864 target and 112290 decoy PSMs
[52:47] Training neural networks on 171864 target and 111996 decoy PSMs
[53:50] Number of IDs at 0.01 FDR: 97311
[53:51] Precursors at 1% peptidoform FDR: 95181
[53:52] Calculating protein q-values
[53:52] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[53:52] Quantification
[53:54] Precursors with scored PTMs at 1% FDR: 2689 out of 2897 considered
[53:54] Precursors with all scored PTM sites unoccupied at 1% FDR: 92492
[53:54] Precursors with PTMs localised (when required) with > 90% confidence: 2608 out of 2689
[55:30] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP2_raw.quant

[55:30] File #6/6
[55:30] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[57:40] Pre-processing...
[57:44] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 4880737 precursors in range
[57:50] Calibrating with mass accuracies 22 (MS1), 25 (MS2)
[58:23] RT window set to 1.18815
[58:23] Recommended MS1 mass accuracy setting: 2.5 ppm
[58:51] Searching decoys
[59:53] Main search
[61:50] Removing low confidence identifications
[62:07] Removing interfering precursors
[62:17] Training neural networks on 175386 target and 116403 decoy PSMs
[63:30] Training neural networks on 175386 target and 115825 decoy PSMs
[64:35] Number of IDs at 0.01 FDR: 98742
[64:36] Precursors at 1% peptidoform FDR: 96048
[64:37] Calculating protein q-values
[64:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[64:37] Quantification
[64:38] Precursors with scored PTMs at 1% FDR: 2696 out of 2925 considered
[64:38] Precursors with all scored PTM sites unoccupied at 1% FDR: 93352
[64:38] Precursors with PTMs localised (when required) with > 90% confidence: 2596 out of 2696
[65:01] Quantification information saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral/S__Proteomics_PRC_PRCRT-336_proteobench_Module_4_DIA_Quantification_RAW_Astral_LFQ_Astral_DIA_15min_50ng_Condition_B_REP3_raw.quant

[65:01] Cross-run analysis
[65:01] Reading quantification information: 6 files
[65:25] Quantifying peptides
[68:05] Assembling protein groups
[68:07] Quantifying proteins
[68:08] Calculating q-values for protein and gene groups
[68:09] Calculating global q-values for protein and gene groups
[68:09] Protein groups with global q-value <= 0.01: 11121
[68:14] Compressed report saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[68:14] Saving precursor levels matrix
[68:19] Precursor levels matrix (1% precursor and protein group FDR) saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report-first-pass.pr_matrix.tsv.
[68:19] Manifest saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report-first-pass.manifest.txt
[68:19] Stats report saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report-first-pass.stats.tsv
[68:19] Generating spectral library:
[68:22] 128102 target and 1299 decoy precursors saved
[68:22] Spectral library saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.parquet

[68:23] Loading spectral library S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.parquet
[68:25] Spectral library loaded: 13005 protein isoforms, 12835 protein groups and 129401 precursors in 120484 elution groups.
[68:25] Loading protein annotations from FASTA S:\Proteomics\PRC\PRCRT-336\proteobench\Module_2_DDA_quantification\FASTA\ProteoBenchFASTA_DDAQuantification.fasta
[68:25] Annotating library proteins with information from the FASTA database
[68:25] Gene names missing for some isoforms
[68:25] Library contains 12994 proteins, and 0 genes
[68:25] Initialising library
[68:26] Saving the library to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\Lib.parquet.skyline.speclib


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

[68:34] File #1/6
[68:34] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP1.raw
[69:37] Pre-processing...
[69:40] 2931 MS1 and 293271 MS2 scans in 977 (inferred) and 977 (encoded) cycles, 128102 precursors in range
[69:40] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[69:41] RT window set to 0.41514
[69:41] Recommended MS1 mass accuracy setting: 2.7 ppm
[69:42] Searching decoys
[69:43] Main search
[69:46] Removing low confidence identifications
[69:50] Removing interfering precursors
[69:52] Training neural networks on 110322 target and 60532 decoy PSMs
[70:30] Training neural networks on 110271 target and 64382 decoy PSMs
[71:08] Number of IDs at 0.01 FDR: 107250
[71:08] Precursors at 1% peptidoform FDR: 105532
[71:08] Calculating protein q-values
[71:08] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[71:08] Quantification
[71:10] Precursors with scored PTMs at 1% FDR: 2550 out of 2617 considered
[71:10] Precursors with all scored PTM sites unoccupied at 1% FDR: 102982
[71:10] Precursors with PTMs localised (when required) with > 90% confidence: 2468 out of 2550

[71:10] File #2/6
[71:10] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP2.raw
[72:17] Pre-processing...
[72:20] 2933 MS1 and 293433 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 128102 precursors in range
[72:20] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[72:21] RT window set to 0.416607
[72:21] Recommended MS1 mass accuracy setting: 2.7 ppm
[72:21] Searching decoys
[72:23] Main search
[72:26] Removing low confidence identifications
[72:30] Removing interfering precursors
[72:32] Training neural networks on 110923 target and 60847 decoy PSMs
[73:10] Training neural networks on 110880 target and 64777 decoy PSMs
[73:48] Number of IDs at 0.01 FDR: 108204
[73:49] Precursors at 1% peptidoform FDR: 106578
[73:49] Calculating protein q-values
[73:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[73:49] Quantification
[73:50] Precursors with scored PTMs at 1% FDR: 2622 out of 2688 considered
[73:50] Precursors with all scored PTM sites unoccupied at 1% FDR: 103956
[73:50] Precursors with PTMs localised (when required) with > 90% confidence: 2543 out of 2622

[73:51] File #3/6
[73:51] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_A_REP3.raw
[75:16] Pre-processing...
[75:19] 2932 MS1 and 293358 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 128102 precursors in range
[75:19] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[75:19] RT window set to 0.417942
[75:19] Recommended MS1 mass accuracy setting: 2.6 ppm
[75:20] Searching decoys
[75:21] Main search
[75:24] Removing low confidence identifications
[75:29] Removing interfering precursors
[75:31] Training neural networks on 110812 target and 60729 decoy PSMs
[76:09] Training neural networks on 110760 target and 65261 decoy PSMs
[76:47] Number of IDs at 0.01 FDR: 108214
[76:48] Precursors at 1% peptidoform FDR: 106563
[76:48] Calculating protein q-values
[76:48] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[76:48] Quantification
[76:49] Precursors with scored PTMs at 1% FDR: 2626 out of 2700 considered
[76:49] Precursors with all scored PTM sites unoccupied at 1% FDR: 103937
[76:49] Precursors with PTMs localised (when required) with > 90% confidence: 2544 out of 2626

[76:50] File #4/6
[76:50] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP1.raw
[77:48] Pre-processing...
[77:51] 2933 MS1 and 293382 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 128102 precursors in range
[77:51] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[77:52] RT window set to 0.406492
[77:52] Recommended MS1 mass accuracy setting: 2.7 ppm
[77:53] Searching decoys
[77:54] Main search
[77:57] Removing low confidence identifications
[78:01] Removing interfering precursors
[78:03] Training neural networks on 111011 target and 61086 decoy PSMs
[78:42] Training neural networks on 110970 target and 65375 decoy PSMs
[79:20] Number of IDs at 0.01 FDR: 109003
[79:20] Precursors at 1% peptidoform FDR: 107234
[79:20] Calculating protein q-values
[79:20] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[79:20] Quantification
[79:22] Precursors with scored PTMs at 1% FDR: 2918 out of 2971 considered
[79:22] Precursors with all scored PTM sites unoccupied at 1% FDR: 104316
[79:22] Precursors with PTMs localised (when required) with > 90% confidence: 2838 out of 2918

[79:22] File #5/6
[79:22] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP2.raw
[80:21] Pre-processing...
[80:24] 2933 MS1 and 293330 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 128102 precursors in range
[80:24] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[80:24] RT window set to 0.396905
[80:24] Recommended MS1 mass accuracy setting: 2.8 ppm
[80:25] Searching decoys
[80:26] Main search
[80:29] Removing low confidence identifications
[80:35] Removing interfering precursors
[80:36] Training neural networks on 111049 target and 60989 decoy PSMs
[81:15] Training neural networks on 111007 target and 65246 decoy PSMs
[81:54] Number of IDs at 0.01 FDR: 108922
[81:54] Precursors at 1% peptidoform FDR: 106981
[81:54] Calculating protein q-values
[81:54] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[81:54] Quantification
[81:56] Precursors with scored PTMs at 1% FDR: 2882 out of 2945 considered
[81:56] Precursors with all scored PTM sites unoccupied at 1% FDR: 104099
[81:56] Precursors with PTMs localised (when required) with > 90% confidence: 2806 out of 2882

[81:57] File #6/6
[81:57] Loading run S:\Proteomics\PRC\PRCRT-336\proteobench\Module_4_DIA_Quantification\RAW\Astral\LFQ_Astral_DIA_15min_50ng_Condition_B_REP3.raw
[82:54] Pre-processing...
[82:57] 2934 MS1 and 293446 MS2 scans in 978 (inferred) and 978 (encoded) cycles, 128102 precursors in range
[82:57] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[82:57] RT window set to 0.42968
[82:57] Recommended MS1 mass accuracy setting: 2.7 ppm
[82:58] Searching decoys
[82:59] Main search
[83:02] Removing low confidence identifications
[83:08] Removing interfering precursors
[83:10] Training neural networks on 111240 target and 60301 decoy PSMs
[83:48] Training neural networks on 111205 target and 65594 decoy PSMs
[84:26] Number of IDs at 0.01 FDR: 108948
[84:27] Precursors at 1% peptidoform FDR: 107203
[84:27] Calculating protein q-values
[84:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[84:27] Quantification
[84:28] Precursors with scored PTMs at 1% FDR: 2899 out of 2939 considered
[84:28] Precursors with all scored PTM sites unoccupied at 1% FDR: 104304
[84:28] Precursors with PTMs localised (when required) with > 90% confidence: 2803 out of 2899

[84:29] Cross-run analysis
[84:29] Reading quantification information: 6 files
[84:31] Quantifying peptides
[87:09] Quantification parameters: 0.36487, 0.00135972, 0.00149916, 0.0131711, 0.0129459, 0.0131227, 0.266786, 0.141671, 0.160421, 0.0359289, 0.0460361, 0.0403482, 0.237671, 0.0515692, 0.0640258, 0.011645
[88:13] Quantifying proteins
[88:14] Calculating q-values for protein and gene groups
[88:14] Calculating global q-values for protein and gene groups
[88:14] Protein groups with global q-value <= 0.01: 10760
[88:19] Compressed report saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[88:19] Saving precursor levels matrix
[88:23] Precursor levels matrix (1% precursor and protein group FDR) saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.pr_matrix.tsv.
[88:23] Saving protein group levels matrix
[88:24] Protein groups matrix saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.pg_matrix.tsv.
[88:24] Saving gene group levels matrix
[88:24] Gene groups matrix saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.gg_matrix.tsv.
[88:24] Saving unique genes levels matrix
[88:24] Unique genes matrix saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.unique_genes_matrix.tsv.
[88:26] Manifest saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.manifest.txt
[88:26] Stats report saved to S:\Proteomics\PRC\PRCRT-336\proteobench\VIB_DIANN_Astral\report.stats.tsv

