DIA-NN 1.8.1 (Data-Independent Acquisition by Neural Networks)
Compiled on Apr 14 2022 15:31:19
Current date and time: Fri Dec 22 14:48:40 2023
CPU: GenuineIntel Intel(R) Xeon(R) CPU E31225 @ 3.10GHz
SIMD instructions: AVX SSE4.1 SSE4.2 
Logical CPU cores: 4
diann.exe --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR1.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR2.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR3.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS1.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS2.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS3.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool1.raw  --f W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool2.raw  --lib  --threads 4 --verbose 1 --out W:\shashwati_DIA\DIANN_Result\report.tsv --qvalue 0.01 --matrices --out-lib W:\shashwati_DIA\DIANN_Result\DIANN_Results.tsv --gen-spec-lib --predictor --prosit --fasta W:\uniprotkb_HUMAN_AND_reviewed_true_AND_m_2023_08_08.fasta --fasta-search --min-fr-mz 300 --max-fr-mz 1500 --cut K*,R* --missed-cleavages 2 --min-pep-len 7 --max-pep-len 30 --min-pr-mz 385 --max-pr-mz 1015 --min-pr-charge 2 --max-pr-charge 5 --unimod4 --var-mods 5 --var-mod UniMod:35,15.994915,M --var-mod UniMod:1,42.010565,*n --monitor-mod UniMod:1 --reanalyse --relaxed-prot-inf --smart-profiling --peak-center --no-ifs-removal 

Thread number set to 4
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
Library-free search enabled
Min fragment m/z set to 300
Max fragment m/z set to 1500
In silico digest will involve cuts at K*,R*
Maximum number of missed cleavages set to 2
Min peptide length set to 7
Max peptide length set to 30
Min precursor m/z set to 385
Max precursor m/z set to 1015
Min precursor charge set to 2
Max precursor charge set to 5
Cysteine carbamidomethylation enabled as a fixed modification
Maximum number of variable modifications set to 5
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
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
Highly heuristic protein grouping will be used, to reduce the number of protein groups obtained; this mode is recommended for benchmarking protein ID numbers; use with caution for anything else
When generating a spectral library, in silico predicted spectra will be retained if deemed more reliable than experimental ones
Fixed-width center of each elution peak will be used for quantification
Interference removal from fragment elution curves 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.
Exclusion of fragments shared between heavy and light peptides from quantification is not supported in FASTA digest mode - disabled; to enable, generate an in silico predicted spectral library and analyse with this library
The following variable modifications will be scored: UniMod:1 

8 files will be processed
[0:00] Loading FASTA W:\uniprotkb_HUMAN_AND_reviewed_true_AND_m_2023_08_08.fasta
[4:16] Processing FASTA
[4:38] Assembling elution groups
[4:51] 5823322 precursors generated
[8:48] Prosit input saved to W:\shashwati_DIA\DIANN_Result\DIANN_Results.prosit.csv
[8:49] Gene names missing for some isoforms
[8:49] Library contains 20402 proteins, and 20186 genes
[8:51] [9:06] [119:54] [139:55] [140:42] [140:47] Saving the library to W:\shashwati_DIA\DIANN_Result\DIANN_Results.predicted.speclib
[144:13] Initialising library

[144:17] First pass: generating a spectral library from DIA data
[144:17] File #1/8
[144:17] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR1.raw
[145:01] 5823322 library precursors are potentially detectable
[145:02] Processing...
[161:40] RT window set to 6.68182
[161:40] Peak width: 5.508
[161:40] Scan window radius set to 12
[161:40] Recommended MS1 mass accuracy setting: 3.99487 ppm
[190:19] Optimised mass accuracy: 13.2203 ppm
[234:29] Removing low confidence identifications
[234:29] Searching PTM decoys
[235:02] Removing interfering precursors
[235:23] Training neural networks: 48260 targets, 36438 decoys
[235:42] Number of IDs at 0.01 FDR: 21644
[235:43] Calculating protein q-values
[235:45] Number of genes identified at 1% FDR: 4140 (precursor-level), 3737 (protein-level) (inference performed using proteotypic peptides only)
[235:45] Quantification
[235:49] Precursors with monitored PTMs at 1% FDR: 0 out of 27
[235:49] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 6
[235:56] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR1.raw.quant.

[236:04] File #2/8
[236:04] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR2.raw
[237:43] 5823322 library precursors are potentially detectable
[237:44] Processing...
[254:03] RT window set to 6.55977
[254:03] Recommended MS1 mass accuracy setting: 3.52871 ppm
[295:44] Removing low confidence identifications
[295:45] Searching PTM decoys
[296:15] Removing interfering precursors
[296:21] Training neural networks: 47500 targets, 35296 decoys
[296:33] Number of IDs at 0.01 FDR: 21863
[296:34] Calculating protein q-values
[296:34] Number of genes identified at 1% FDR: 4307 (precursor-level), 3850 (protein-level) (inference performed using proteotypic peptides only)
[296:35] Quantification
[296:36] Precursors with monitored PTMs at 1% FDR: 0 out of 37
[296:36] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 2
[296:41] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR2.raw.quant.

[296:43] File #3/8
[296:43] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR3.raw
[297:24] 5823322 library precursors are potentially detectable
[297:25] Processing...
[312:22] RT window set to 7.0202
[312:22] Recommended MS1 mass accuracy setting: 3.62372 ppm
[348:23] Removing low confidence identifications
[348:24] Searching PTM decoys
[348:50] Removing interfering precursors
[348:56] Training neural networks: 41048 targets, 31291 decoys
[349:07] Number of IDs at 0.01 FDR: 19466
[349:07] Calculating protein q-values
[349:08] Number of genes identified at 1% FDR: 3674 (precursor-level), 3288 (protein-level) (inference performed using proteotypic peptides only)
[349:08] Quantification
[349:09] Precursors with monitored PTMs at 1% FDR: 0 out of 38
[349:09] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 8
[349:37] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR3.raw.quant.

[349:39] File #4/8
[349:39] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS1.raw
[350:34] 5823322 library precursors are potentially detectable
[350:35] Processing...
[365:03] RT window set to 6.10043
[365:04] Recommended MS1 mass accuracy setting: 3.16002 ppm
[403:00] Removing low confidence identifications
[403:01] Searching PTM decoys
[403:29] Removing interfering precursors
[403:35] Training neural networks: 49763 targets, 36623 decoys
[403:47] Number of IDs at 0.01 FDR: 23277
[403:47] Calculating protein q-values
[403:48] Number of genes identified at 1% FDR: 4316 (precursor-level), 3820 (protein-level) (inference performed using proteotypic peptides only)
[403:48] Quantification
[403:49] Precursors with monitored PTMs at 1% FDR: 0 out of 48
[403:49] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 7
[403:52] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS1.raw.quant.

[403:54] File #5/8
[403:54] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS2.raw
[404:18] 5823322 library precursors are potentially detectable
[404:19] Processing...
[420:57] RT window set to 6.7588
[420:57] Recommended MS1 mass accuracy setting: 3.72903 ppm
[462:59] Removing low confidence identifications
[463:00] Searching PTM decoys
[463:30] Removing interfering precursors
[463:36] Training neural networks: 46269 targets, 35306 decoys
[463:47] Number of IDs at 0.01 FDR: 22513
[463:48] Calculating protein q-values
[463:49] Number of genes identified at 1% FDR: 4180 (precursor-level), 3794 (protein-level) (inference performed using proteotypic peptides only)
[463:49] Quantification
[463:50] Precursors with monitored PTMs at 1% FDR: 0 out of 45
[463:50] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 8
[463:53] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS2.raw.quant.

[463:55] File #6/8
[463:55] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS3.raw
[464:22] 5823322 library precursors are potentially detectable
[464:22] Processing...
[480:26] RT window set to 6.9387
[480:27] Recommended MS1 mass accuracy setting: 3.54479 ppm
[524:10] Removing low confidence identifications
[524:10] Searching PTM decoys
[524:41] Removing interfering precursors
[524:48] Training neural networks: 46517 targets, 35217 decoys
[524:59] Number of IDs at 0.01 FDR: 21801
[525:00] Calculating protein q-values
[525:00] Number of genes identified at 1% FDR: 4099 (precursor-level), 3677 (protein-level) (inference performed using proteotypic peptides only)
[525:00] Quantification
[525:02] Precursors with monitored PTMs at 1% FDR: 0 out of 42
[525:02] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 11
[525:09] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS3.raw.quant.

[525:11] File #7/8
[525:11] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool1.raw
[525:34] 5823322 library precursors are potentially detectable
[525:35] Processing...
[541:15] RT window set to 4.88643
[541:15] Recommended MS1 mass accuracy setting: 3.20272 ppm
[570:16] Removing low confidence identifications
[570:16] Searching PTM decoys
[570:38] Removing interfering precursors
[570:45] Training neural networks: 47572 targets, 34435 decoys
[570:56] Number of IDs at 0.01 FDR: 22477
[570:56] Calculating protein q-values
[570:57] Number of genes identified at 1% FDR: 4138 (precursor-level), 3685 (protein-level) (inference performed using proteotypic peptides only)
[570:57] Quantification
[570:58] Precursors with monitored PTMs at 1% FDR: 0 out of 41
[570:58] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 10
[571:06] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool1.raw.quant.

[571:07] File #8/8
[571:07] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool2.raw
[571:30] 5823322 library precursors are potentially detectable
[571:30] Processing...
[587:28] RT window set to 7.08468
[587:29] Recommended MS1 mass accuracy setting: 3.75591 ppm
[628:26] Removing low confidence identifications
[628:26] Searching PTM decoys
[628:56] Removing interfering precursors
[629:02] Training neural networks: 45154 targets, 34117 decoys
[629:13] Number of IDs at 0.01 FDR: 20902
[629:13] Calculating protein q-values
[629:14] Number of genes identified at 1% FDR: 3894 (precursor-level), 3525 (protein-level) (inference performed using proteotypic peptides only)
[629:14] Quantification
[629:16] Precursors with monitored PTMs at 1% FDR: 0 out of 35
[629:16] Unmodified precursors with monitored PTM sites at 1% FDR: 0 out of 5
[629:18] Quantification information saved to W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool2.raw.quant.

[629:20] Cross-run analysis
[629:20] Reading quantification information: 8 files
[629:26] Quantifying peptides
[629:30] Assembling protein groups
[629:45] Quantifying proteins
[629:47] Calculating q-values for protein and gene groups
[629:47] Calculating global q-values for protein and gene groups
[629:47] Writing report
[630:15] Report saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.tsv.
[630:15] Saving precursor levels matrix
[630:16] Precursor levels matrix (1% precursor and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.pr_matrix.tsv.
[630:16] Saving protein group levels matrix
[630:16] Protein group levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.pg_matrix.tsv.
[630:16] Saving gene group levels matrix
[630:16] Gene groups levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.gg_matrix.tsv.
[630:16] Saving unique genes levels matrix
[630:16] Unique genes levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.unique_genes_matrix.tsv.
[630:16] Stats report saved to W:\shashwati_DIA\DIANN_Result\report-first-pass.stats.tsv
[630:16] Generating spectral library:
[630:16] 31144 precursors passing the FDR threshold are to be extracted
[630:16] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR1.raw
[630:42] 5823322 library precursors are potentially detectable
[630:43] 634 spectra added to the library
[630:43] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR2.raw
[631:08] 5823322 library precursors are potentially detectable
[631:09] 779 spectra added to the library
[631:10] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR3.raw
[631:30] 5823322 library precursors are potentially detectable
[631:31] 6038 spectra added to the library
[631:31] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS1.raw
[631:54] 5823322 library precursors are potentially detectable
[631:56] 4635 spectra added to the library
[631:56] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS2.raw
[632:16] 5823322 library precursors are potentially detectable
[632:17] 1723 spectra added to the library
[632:18] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS3.raw
[632:39] 5823322 library precursors are potentially detectable
[632:40] 1509 spectra added to the library
[632:40] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool1.raw
[632:59] 5823322 library precursors are potentially detectable
[633:00] 2596 spectra added to the library
[633:00] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool2.raw
[633:19] 5823322 library precursors are potentially detectable
[633:20] 2154 spectra added to the library
[633:20] Saving spectral library to W:\shashwati_DIA\DIANN_Result\DIANN_Results.tsv
[633:34] 31144 precursors saved
[633:34] Loading the generated library and saving it in the .speclib format
[633:34] Loading spectral library W:\shashwati_DIA\DIANN_Result\DIANN_Results.tsv
[633:36] Spectral library loaded: 6066 protein isoforms, 6263 protein groups and 31144 precursors in 27767 elution groups.
[633:36] Loading protein annotations from FASTA W:\uniprotkb_HUMAN_AND_reviewed_true_AND_m_2023_08_08.fasta
[633:38] Gene names missing for some isoforms
[633:38] Library contains 6066 proteins, and 6052 genes
[633:38] Saving the library to W:\shashwati_DIA\DIANN_Result\DIANN_Results.tsv.speclib

[633:45] Second pass: using the newly created spectral library to reanalyse the data
[633:45] File #1/8
[633:45] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR1.raw
[634:06] 31144 library precursors are potentially detectable
[634:06] Processing...
[634:11] RT window set to 2.21116
[634:11] Recommended MS1 mass accuracy setting: 3.76959 ppm
[634:19] Removing low confidence identifications
[634:19] Searching PTM decoys
[634:19] Removing interfering precursors
[634:21] Training neural networks: 29696 targets, 21369 decoys
[634:27] Number of IDs at 0.01 FDR: 26847
[634:27] Calculating protein q-values
[634:27] Number of genes identified at 1% FDR: 4647 (precursor-level), 3932 (protein-level) (inference performed using proteotypic peptides only)
[634:27] Quantification

[634:28] File #2/8
[634:28] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR2.raw
[634:49] 31144 library precursors are potentially detectable
[634:49] Processing...
[634:54] RT window set to 2.17887
[634:54] Recommended MS1 mass accuracy setting: 3.81558 ppm
[635:02] Removing low confidence identifications
[635:02] Searching PTM decoys
[635:02] Removing interfering precursors
[635:04] Training neural networks: 29432 targets, 20669 decoys
[635:10] Number of IDs at 0.01 FDR: 26900
[635:10] Calculating protein q-values
[635:10] Number of genes identified at 1% FDR: 4725 (precursor-level), 4042 (protein-level) (inference performed using proteotypic peptides only)
[635:10] Quantification

[635:11] File #3/8
[635:11] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisR3.raw
[635:28] 31144 library precursors are potentially detectable
[635:28] Processing...
[635:33] RT window set to 2.2174
[635:33] Recommended MS1 mass accuracy setting: 3.18745 ppm
[635:40] Removing low confidence identifications
[635:40] Searching PTM decoys
[635:40] Removing interfering precursors
[635:41] Training neural networks: 27686 targets, 17250 decoys
[635:46] Number of IDs at 0.01 FDR: 24732
[635:47] Calculating protein q-values
[635:47] Number of genes identified at 1% FDR: 4334 (precursor-level), 3661 (protein-level) (inference performed using proteotypic peptides only)
[635:47] Quantification

[635:47] File #4/8
[635:47] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS1.raw
[636:07] 31144 library precursors are potentially detectable
[636:07] Processing...
[636:12] RT window set to 2.19564
[636:12] Recommended MS1 mass accuracy setting: 3.73469 ppm
[636:20] Removing low confidence identifications
[636:20] Searching PTM decoys
[636:20] Removing interfering precursors
[636:22] Training neural networks: 29724 targets, 20458 decoys
[636:28] Number of IDs at 0.01 FDR: 27321
[636:28] Calculating protein q-values
[636:28] Number of genes identified at 1% FDR: 4662 (precursor-level), 4101 (protein-level) (inference performed using proteotypic peptides only)
[636:28] Quantification

[636:29] File #5/8
[636:29] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS2.raw
[636:49] 31144 library precursors are potentially detectable
[636:49] Processing...
[636:54] RT window set to 2.17608
[636:54] Recommended MS1 mass accuracy setting: 3.31289 ppm
[637:02] Removing low confidence identifications
[637:02] Searching PTM decoys
[637:02] Removing interfering precursors
[637:03] Training neural networks: 29128 targets, 20083 decoys
[637:09] Number of IDs at 0.01 FDR: 26622
[637:10] Calculating protein q-values
[637:10] Number of genes identified at 1% FDR: 4571 (precursor-level), 4004 (protein-level) (inference performed using proteotypic peptides only)
[637:10] Quantification

[637:11] File #6/8
[637:11] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_CisS3.raw
[637:31] 31144 library precursors are potentially detectable
[637:31] Processing...
[637:36] RT window set to 2.18184
[637:36] Recommended MS1 mass accuracy setting: 3.71928 ppm
[637:43] Removing low confidence identifications
[637:43] Searching PTM decoys
[637:43] Removing interfering precursors
[637:45] Training neural networks: 28982 targets, 20452 decoys
[637:51] Number of IDs at 0.01 FDR: 26310
[637:51] Calculating protein q-values
[637:51] Number of genes identified at 1% FDR: 4549 (precursor-level), 3903 (protein-level) (inference performed using proteotypic peptides only)
[637:51] Quantification

[637:52] File #7/8
[637:52] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool1.raw
[638:10] 31144 library precursors are potentially detectable
[638:10] Processing...
[638:15] RT window set to 2.19625
[638:15] Recommended MS1 mass accuracy setting: 3.73878 ppm
[638:22] Removing low confidence identifications
[638:22] Searching PTM decoys
[638:22] Removing interfering precursors
[638:24] Training neural networks: 29140 targets, 19504 decoys
[638:29] Number of IDs at 0.01 FDR: 26290
[638:30] Calculating protein q-values
[638:30] Number of genes identified at 1% FDR: 4459 (precursor-level), 3901 (protein-level) (inference performed using proteotypic peptides only)
[638:30] Quantification

[638:31] File #8/8
[638:31] Loading run W:\shashwati_DIA\DIA_cellline\18122023_SP_QCpool2.raw
[638:49] 31144 library precursors are potentially detectable
[638:49] Processing...
[638:54] RT window set to 2.1869
[638:54] Recommended MS1 mass accuracy setting: 3.37135 ppm
[639:01] Removing low confidence identifications
[639:01] Searching PTM decoys
[639:01] Removing interfering precursors
[639:03] Training neural networks: 29001 targets, 19232 decoys
[639:08] Number of IDs at 0.01 FDR: 26507
[639:09] Calculating protein q-values
[639:09] Number of genes identified at 1% FDR: 4557 (precursor-level), 3905 (protein-level) (inference performed using proteotypic peptides only)
[639:09] Quantification

[639:10] Cross-run analysis
[639:10] Reading quantification information: 8 files
[639:10] Quantifying peptides
[639:14] Quantifying proteins
[639:15] Calculating q-values for protein and gene groups
[639:16] Calculating global q-values for protein and gene groups
[639:16] Writing report
[639:47] Report saved to W:\shashwati_DIA\DIANN_Result\report.tsv.
[639:47] Saving precursor levels matrix
[639:49] Precursor levels matrix (1% precursor and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report.pr_matrix.tsv.
[639:49] Saving protein group levels matrix
[639:49] Protein group levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report.pg_matrix.tsv.
[639:49] Saving gene group levels matrix
[639:49] Gene groups levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report.gg_matrix.tsv.
[639:49] Saving unique genes levels matrix
[639:49] Unique genes levels matrix (1% precursor FDR and protein group FDR) saved to W:\shashwati_DIA\DIANN_Result\report.unique_genes_matrix.tsv.
[639:49] Stats report saved to W:\shashwati_DIA\DIANN_Result\report.stats.tsv

Finished