
DIA-NN 2.3.1 Academia  (Data-Independent Acquisition by Neural Networks)
Compiled on Dec  5 2025 10:52:39
Current date and time: Tue Jun 23 14:20:29 2026
CPU: AuthenticAMD AMD Ryzen 9 5950X 16-Core Processor
SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 SSE4a 
Logical CPU cores: 32
111Gb out of 127Gb RAM is free
diann.exe --f C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_01.raw  --f C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_02.raw  --f C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_03.raw  --lib C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.predicted.speclib --threads 16 --verbose 1 --out C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.parquet --qvalue 0.1 --matrices --out-lib C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.parquet --gen-spec-lib --fasta C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\FDRBench_output\ProteoBenchFASTA_Entrapment_Human_with_contaminants_entrapment_pep.fasta --min-pep-len 7 --max-pep-len 30 --min-pr-mz 300 --max-pr-mz 1800 --min-pr-charge 1 --max-pr-charge 4 --min-fr-mz 200 --max-fr-mz 1800 --cut K*,R* --missed-cleavages 1 --unimod4 --reanalyse --rt-profiling --cut 

Thread number set to 16
Output will be filtered at 0.1 FDR
Precursor/protein x samples expression level matrices will be saved along with the main report
A spectral library will be generated
Min peptide length set to 7
Max peptide length set to 30
Min precursor m/z set to 300
Max precursor m/z set to 1800
Min precursor charge set to 1
Max precursor charge set to 4
Min fragment m/z set to 200
Max fragment m/z set to 1800
In silico digest will involve cuts at K*,R*
Maximum number of missed cleavages set to 1
Cysteine carbamidomethylation enabled as a fixed modification
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: protein inference will only be performed for precursors identified with global q-value <= 0.05 or q-value <= 0.05.
WARNING: it is strongly recommended to set the q-value threshold to 5% or lower when generating an empirical library.

3 files will be processed
[0:00] Loading spectral library C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.predicted.speclib
[0:06] Library annotated with sequence database(s): C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\FDRBench_output\ProteoBenchFASTA_Entrapment_Human_with_contaminants_entrapment_pep.fasta
[0:07] Spectral library loaded: 2692562 protein isoforms, 2692562 protein groups and 8649692 precursors in 2692562 elution groups.
[0:07] Loading protein annotations from FASTA C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\FDRBench_output\ProteoBenchFASTA_Entrapment_Human_with_contaminants_entrapment_pep.fasta
[0:35] Annotating library proteins with information from the FASTA database
[0:37] Gene names missing for some isoforms
[0:37] Library contains 2692562 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[0:41] Initialising library

First pass: generating a spectral library from DIA data

[0:53] File #1/3
[0:53] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_01.raw
[1:03] Pre-processing...
[1:08] 2928 MS1 and 292883 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 5370648 precursors in range
[1:09] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[1:40] RT window set to 1.49073
[1:40] Peak width: 2.856
[1:40] Scan window radius set to 6
[1:40] Recommended MS1 mass accuracy setting: 2.2 ppm
[2:32] Optimised mass accuracy: 7 ppm
[2:46] Main search
[4:57] Removing low confidence identifications
[5:08] Removing interfering precursors
[5:17] Training neural networks on 162322 target and 100568 decoy PSMs
[6:46] IDs at 0.01 FDR: 81701
[6:48] Number of IDs at 0.01 FDR: 81701
[6:48] Calculating protein q-values
[6:48] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[6:48] Quantification
[6:51] Quantification information saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_01.raw.quant

[6:51] File #2/3
[6:51] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_02.raw
[7:02] Pre-processing...
[7:07] 2928 MS1 and 292914 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 5370648 precursors in range
[7:08] Calibrating with mass accuracies 20 (MS1), 25 (MS2)
[7:41] RT window set to 1.56762
[7:41] Recommended MS1 mass accuracy setting: 2.3 ppm
[7:55] Main search
[10:16] Removing low confidence identifications
[10:28] Removing interfering precursors
[10:38] Training neural networks on 163437 target and 100620 decoy PSMs
[12:07] IDs at 0.01 FDR: 82781
[12:10] Number of IDs at 0.01 FDR: 82781
[12:10] Calculating protein q-values
[12:10] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[12:10] Quantification
[12:13] Quantification information saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_02.raw.quant

[12:13] File #3/3
[12:13] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_03.raw
[12:23] Pre-processing...
[12:28] 2927 MS1 and 292757 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 5370648 precursors in range
[12:29] Calibrating with mass accuracies 20 (MS1), 25 (MS2)
[13:03] RT window set to 1.4467
[13:03] Recommended MS1 mass accuracy setting: 2.2 ppm
[13:15] Main search
[15:25] Removing low confidence identifications
[15:35] Removing interfering precursors
[15:44] Training neural networks on 162512 target and 100309 decoy PSMs
[17:11] IDs at 0.01 FDR: 81529
[17:13] Number of IDs at 0.01 FDR: 81529
[17:13] Calculating protein q-values
[17:14] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[17:14] Quantification
[17:16] Quantification information saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_03.raw.quant

[17:16] Cross-run analysis
[17:16] Reading quantification information: 3 files
[17:30] Quantifying peptides
[18:11] Assembling protein groups
[18:13] Quantifying proteins
[18:13] Calculating q-values for protein and gene groups
[18:14] Calculating global q-values for protein and gene groups
[18:14] Protein groups with global q-value <= 0.01: 85140
[18:15] Compressed report saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[18:15] Saving precursor levels matrix
[18:16] Precursor levels matrix (1% precursor and protein group FDR) saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces-first-pass.pr_matrix.tsv.
[18:16] Manifest saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces-first-pass.manifest.txt
[18:16] Stats report saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces-first-pass.stats.tsv
[18:16] Generating spectral library:
[18:18] 125191 target and 12530 decoy precursors saved
[18:18] Spectral library saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.parquet

[18:19] Loading spectral library C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.parquet
[18:21] Spectral library loaded: 107792 protein isoforms, 107792 protein groups and 137719 precursors in 126463 elution groups.
[18:21] Loading protein annotations from FASTA C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\FDRBench_output\ProteoBenchFASTA_Entrapment_Human_with_contaminants_entrapment_pep.fasta
[18:52] Annotating library proteins with information from the FASTA database
[18:52] Gene names missing for some isoforms
[18:52] Library contains 107792 proteins, and 0 genes
WARNING: no gene information in the FASTA or library: consider using --ids-to-names
[18:52] Initialising library
[18:53] Saving the library to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_speclibs\no_Mexcision_no_varmods_cutempty_7_30\no_Mexc_no_varmods_cutempty_7_30.parquet.skyline.speclib


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

[18:53] File #1/3
[18:53] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_01.raw
[19:04] Pre-processing...
[19:04] 2928 MS1 and 292883 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 125191 precursors in range
[19:04] Calibrating with mass accuracies 21 (MS1), 25 (MS2)
[19:05] RT window set to 0.425596
[19:05] Recommended MS1 mass accuracy setting: 2.6 ppm
[19:06] Main search
[19:09] Removing low confidence identifications
[19:13] Removing interfering precursors
[19:14] Training neural networks on 118938 target and 52292 decoy PSMs
[20:08] IDs at 0.01 FDR: 82360
[20:09] Number of IDs at 0.01 FDR: 82360
[20:09] Calculating protein q-values
[20:09] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[20:09] Quantification

[20:10] File #2/3
[20:10] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_02.raw
[20:21] Pre-processing...
[20:22] 2928 MS1 and 292914 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 125191 precursors in range
[20:22] Calibrating with mass accuracies 20 (MS1), 25 (MS2)
[20:23] RT window set to 0.427694
[20:23] Recommended MS1 mass accuracy setting: 2.5 ppm
[20:23] Main search
[20:26] Removing low confidence identifications
[20:30] Removing interfering precursors
[20:32] Training neural networks on 119012 target and 52369 decoy PSMs
[21:27] IDs at 0.01 FDR: 82498
[21:27] Number of IDs at 0.01 FDR: 82498
[21:27] Calculating protein q-values
[21:27] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[21:27] Quantification

[21:29] File #3/3
[21:29] Loading run C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\LFQ_Astral_DIA_15min_50ng_Human_03.raw
[21:39] Pre-processing...
[21:40] 2927 MS1 and 292757 MS2 scans in 976 (inferred) and 976 (encoded) cycles, 125191 precursors in range
[21:40] Calibrating with mass accuracies 20 (MS1), 25 (MS2)
[21:41] RT window set to 0.441612
[21:41] Recommended MS1 mass accuracy setting: 2.6 ppm
[21:41] Main search
[21:45] Removing low confidence identifications
[21:49] Removing interfering precursors
[21:50] Training neural networks on 118464 target and 52335 decoy PSMs
[22:45] IDs at 0.01 FDR: 81685
[22:46] Number of IDs at 0.01 FDR: 81685
[22:46] Calculating protein q-values
[22:46] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only)
[22:46] Quantification

[22:47] Cross-run analysis
[22:47] Reading quantification information: 3 files
[22:48] Quantifying peptides
WARNING: QuantUMS requires 6 or more runs for the optimisation of its hyperparameters to perform best.
[24:04] Quantification parameters: 0.342101, 0.00220528, 0.00159253, 0.251051, 0.214119, 0.206445, 0.115263, 0.12193, 0.0932984, 0.159217, 0.0482724, 0.0558807, 0.583379, 0.0503789, 0.0638371, 0.00817909
[24:18] Quantifying proteins
[24:18] Calculating q-values for protein and gene groups
[24:19] Calculating global q-values for protein and gene groups
[24:19] Protein groups with global q-value <= 0.01: 83415
[24:20] Compressed report saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.parquet. Use R 'arrow' or Python 'PyArrow' package to process
[24:20] Saving precursor levels matrix
[24:20] Precursor levels matrix (1% precursor and protein group FDR) saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.pr_matrix.tsv.
[24:20] Saving protein group levels matrix
[24:21] Protein groups matrix saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.pg_matrix.tsv.
[24:21] Saving gene group levels matrix
[24:21] Gene groups matrix saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.gg_matrix.tsv.
[24:21] Saving unique genes levels matrix
[24:21] Unique genes matrix saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.unique_genes_matrix.tsv.
[24:21] Manifest saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.manifest.txt
[24:21] Stats report saved to C:\Users\cajac\Documents\ProteoBench\Entrapment_Runs\DIANN_output\DIANN_search_results\report_10_percent_no_Mexc_no_varmods_7_3_cutempty_twoshitespaces.stats.tsv

