DIA-NN 1.7.16 (Data-Independent Acquisition by Neural Networks) Compiled on Mar 27 2021 21:34:06 Current date and time: Mon Jun 12 11:19:03 2023 CPU: GenuineIntel Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz SIMD instructions: AVX AVX2 AVX512CD AVX512F FMA SSE4.1 SSE4.2 Logical CPU cores: 32 diann.exe --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S3.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S3.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S3.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S3.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S3.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S1.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S2.wiff --f D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S3.wiff --lib D:\Data\niwa_DIANN\SWATHatlas\EC2020\Ecoli_consensus_peakview.txt --threads 16 --verbose 1 --out D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.tsv --qvalue 0.01 --matrices --min-corr 1.0 --corr-diff 1.0 --time-corr-only --smart-profiling Thread number set to 16 Output will be filtered at 0.01 FDR Precursor/protein x samples expression level matrices will be saved along with the main report Only peaks with correlation sum exceeding 1 will be considered Peaks with correlation sum below 1 from maximum will not be considered A single score will be used until RT alignment to save memory; this can potentially lead to slower search When generating a spectral library, in silico predicted spectra will be retained if deemed more reliable than experimental ones 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. 18 files will be processed [0:00] Loading spectral library D:\Data\niwa_DIANN\SWATHatlas\EC2020\Ecoli_consensus_peakview.txt WARNING: no neutral loss information found in the library - assuming fragments without losses [0:02] Finding proteotypic peptides (assuming that the list of UniProt ids provided for each peptide is complete) [0:02] Spectral library loaded: 4152 protein isoforms, 4152 protein groups and 68959 precursors in 56883 elution groups. [0:02] Initialising library [0:02] Saving the library to D:\Data\niwa_DIANN\SWATHatlas\EC2020\Ecoli_consensus_peakview.txt.speclib [0:03] File #1/18 [0:03] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S1.wiff [5:24] 68709 library precursors are potentially detectable [5:24] Processing... [5:43] RT window set to 2.08368 [5:43] Peak width: 2.996 [5:43] Scan window radius set to 6 [5:43] Recommended MS1 mass accuracy setting: 24.6226 ppm [6:45] Optimised mass accuracy: 30.2636 ppm [7:09] Removing low confidence identifications [7:09] Removing interfering precursors [7:12] Training the neural network: 31462 targets, 57621 decoys [7:15] Number of IDs at 0.01 FDR: 16113 [7:15] Calculating protein q-values [7:15] Number of protein isoforms identified at 1% FDR: 1751 (precursor-level), 1625 (protein-level) (inference performed using proteotypic peptides only) [7:15] Quantification [7:17] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S1.wiff.quant. [7:17] File #2/18 [7:17] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S2.wiff [12:00] 68709 library precursors are potentially detectable [12:00] Processing... [12:12] RT window set to 2.16885 [12:12] Recommended MS1 mass accuracy setting: 20.5338 ppm [12:38] Removing low confidence identifications [12:38] Removing interfering precursors [12:41] Training the neural network: 31577 targets, 58031 decoys [12:44] Number of IDs at 0.01 FDR: 16017 [12:45] Calculating protein q-values [12:45] Number of protein isoforms identified at 1% FDR: 1739 (precursor-level), 1591 (protein-level) (inference performed using proteotypic peptides only) [12:45] Quantification [12:47] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S2.wiff.quant. [12:47] File #3/18 [12:47] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S3.wiff [18:17] 68709 library precursors are potentially detectable [18:17] Processing... [18:29] RT window set to 2.13446 [18:29] Recommended MS1 mass accuracy setting: 29.4822 ppm [18:55] Removing low confidence identifications [18:55] Removing interfering precursors [18:58] Training the neural network: 31586 targets, 57696 decoys [19:01] Number of IDs at 0.01 FDR: 15942 [19:01] Calculating protein q-values [19:01] Number of protein isoforms identified at 1% FDR: 1723 (precursor-level), 1609 (protein-level) (inference performed using proteotypic peptides only) [19:01] Quantification [19:03] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample1_S3.wiff.quant. [19:03] File #4/18 [19:03] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S1.wiff [23:56] 68709 library precursors are potentially detectable [23:56] Processing... [24:06] RT window set to 2.53222 [24:06] Recommended MS1 mass accuracy setting: 19.6502 ppm [24:32] Removing low confidence identifications [24:32] Removing interfering precursors [24:35] Training the neural network: 32440 targets, 58783 decoys [24:38] Number of IDs at 0.01 FDR: 17285 [24:39] Calculating protein q-values [24:39] Number of protein isoforms identified at 1% FDR: 1862 (precursor-level), 1713 (protein-level) (inference performed using proteotypic peptides only) [24:39] Quantification [24:41] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S1.wiff.quant. [24:41] File #5/18 [24:41] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S2.wiff [29:07] 68709 library precursors are potentially detectable [29:07] Processing... [29:17] RT window set to 2.67968 [29:17] Recommended MS1 mass accuracy setting: 23.2553 ppm [29:43] Removing low confidence identifications [29:43] Removing interfering precursors [29:46] Training the neural network: 32125 targets, 59328 decoys [29:49] Number of IDs at 0.01 FDR: 17128 [29:50] Calculating protein q-values [29:50] Number of protein isoforms identified at 1% FDR: 1835 (precursor-level), 1705 (protein-level) (inference performed using proteotypic peptides only) [29:50] Quantification [29:52] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S2.wiff.quant. [29:52] File #6/18 [29:52] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S3.wiff [33:45] 68709 library precursors are potentially detectable [33:45] Processing... [33:55] RT window set to 2.56183 [33:55] Recommended MS1 mass accuracy setting: 36.5007 ppm [34:21] Removing low confidence identifications [34:21] Removing interfering precursors [34:24] Training the neural network: 32096 targets, 58912 decoys [34:27] Number of IDs at 0.01 FDR: 16716 [34:27] Calculating protein q-values [34:27] Number of protein isoforms identified at 1% FDR: 1797 (precursor-level), 1663 (protein-level) (inference performed using proteotypic peptides only) [34:27] Quantification [34:29] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample2_S3.wiff.quant. [34:30] File #7/18 [34:30] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S1.wiff [38:31] 68709 library precursors are potentially detectable [38:31] Processing... [38:41] RT window set to 2.68574 [38:41] Recommended MS1 mass accuracy setting: 30.2228 ppm [39:08] Removing low confidence identifications [39:08] Removing interfering precursors [39:11] Training the neural network: 31271 targets, 59244 decoys [39:14] Number of IDs at 0.01 FDR: 16430 [39:14] Calculating protein q-values [39:14] Number of protein isoforms identified at 1% FDR: 1760 (precursor-level), 1628 (protein-level) (inference performed using proteotypic peptides only) [39:14] Quantification [39:16] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S1.wiff.quant. [39:17] File #8/18 [39:17] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S2.wiff [43:17] 68709 library precursors are potentially detectable [43:17] Processing... [43:30] RT window set to 1.96735 [43:30] Recommended MS1 mass accuracy setting: 24.0458 ppm [43:56] Removing low confidence identifications [43:56] Removing interfering precursors [43:58] Training the neural network: 31095 targets, 56555 decoys [44:01] Number of IDs at 0.01 FDR: 16204 [44:02] Calculating protein q-values [44:02] Number of protein isoforms identified at 1% FDR: 1776 (precursor-level), 1640 (protein-level) (inference performed using proteotypic peptides only) [44:02] Quantification [44:04] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S2.wiff.quant. [44:04] File #9/18 [44:04] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S3.wiff [47:57] 68709 library precursors are potentially detectable [47:57] Processing... [48:09] RT window set to 2.11169 [48:09] Recommended MS1 mass accuracy setting: 28.648 ppm [48:34] Removing low confidence identifications [48:34] Removing interfering precursors [48:37] Training the neural network: 31189 targets, 57091 decoys [48:40] Number of IDs at 0.01 FDR: 16129 [48:40] Calculating protein q-values [48:40] Number of protein isoforms identified at 1% FDR: 1752 (precursor-level), 1620 (protein-level) (inference performed using proteotypic peptides only) [48:40] Quantification [48:42] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample3_S3.wiff.quant. [48:42] File #10/18 [48:42] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S1.wiff [53:45] 68709 library precursors are potentially detectable [53:45] Processing... [53:55] RT window set to 2.74712 [53:55] Recommended MS1 mass accuracy setting: 27.7746 ppm [54:23] Removing low confidence identifications [54:23] Removing interfering precursors [54:26] Training the neural network: 32212 targets, 58181 decoys [54:29] Number of IDs at 0.01 FDR: 18852 [54:29] Calculating protein q-values [54:29] Number of protein isoforms identified at 1% FDR: 1927 (precursor-level), 1773 (protein-level) (inference performed using proteotypic peptides only) [54:29] Quantification [54:31] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S1.wiff.quant. [54:32] File #11/18 [54:32] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S2.wiff [59:12] 68709 library precursors are potentially detectable [59:12] Processing... [59:22] RT window set to 2.70918 [59:22] Recommended MS1 mass accuracy setting: 27.409 ppm [59:49] Removing low confidence identifications [59:49] Removing interfering precursors [59:53] Training the neural network: 33160 targets, 58124 decoys [59:56] Number of IDs at 0.01 FDR: 18417 [59:56] Calculating protein q-values [59:56] Number of protein isoforms identified at 1% FDR: 1909 (precursor-level), 1767 (protein-level) (inference performed using proteotypic peptides only) [59:56] Quantification [59:58] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S2.wiff.quant. [59:59] File #12/18 [59:59] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S3.wiff [64:32] 68709 library precursors are potentially detectable [64:32] Processing... [64:43] RT window set to 2.36002 [64:43] Recommended MS1 mass accuracy setting: 27.2299 ppm [65:09] Removing low confidence identifications [65:09] Removing interfering precursors [65:12] Training the neural network: 33121 targets, 57226 decoys [65:15] Number of IDs at 0.01 FDR: 18322 [65:15] Calculating protein q-values [65:15] Number of protein isoforms identified at 1% FDR: 1898 (precursor-level), 1760 (protein-level) (inference performed using proteotypic peptides only) [65:15] Quantification [65:17] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample4_S3.wiff.quant. [65:18] File #13/18 [65:18] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S1.wiff [70:04] 68709 library precursors are potentially detectable [70:04] Processing... [70:15] RT window set to 2.59778 [70:15] Recommended MS1 mass accuracy setting: 28.8619 ppm [70:42] Removing low confidence identifications [70:42] Removing interfering precursors [70:45] Training the neural network: 32603 targets, 58207 decoys [70:48] Number of IDs at 0.01 FDR: 17760 [70:49] Calculating protein q-values [70:49] Number of protein isoforms identified at 1% FDR: 1839 (precursor-level), 1718 (protein-level) (inference performed using proteotypic peptides only) [70:49] Quantification [70:51] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S1.wiff.quant. [70:51] File #14/18 [70:51] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S2.wiff [75:30] 68709 library precursors are potentially detectable [75:30] Processing... [75:41] RT window set to 2.18253 [75:41] Recommended MS1 mass accuracy setting: 26.0849 ppm [76:06] Removing low confidence identifications [76:06] Removing interfering precursors [76:10] Training the neural network: 31960 targets, 56818 decoys [76:13] Number of IDs at 0.01 FDR: 17233 [76:13] Calculating protein q-values [76:13] Number of protein isoforms identified at 1% FDR: 1814 (precursor-level), 1659 (protein-level) (inference performed using proteotypic peptides only) [76:13] Quantification [76:15] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S2.wiff.quant. [76:15] File #15/18 [76:15] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S3.wiff [80:54] 68709 library precursors are potentially detectable [80:54] Processing... [81:05] RT window set to 2.57217 [81:05] Recommended MS1 mass accuracy setting: 35.8992 ppm [81:31] Removing low confidence identifications [81:31] Removing interfering precursors [81:34] Training the neural network: 31846 targets, 58553 decoys [81:37] Number of IDs at 0.01 FDR: 17214 [81:37] Calculating protein q-values [81:37] Number of protein isoforms identified at 1% FDR: 1804 (precursor-level), 1665 (protein-level) (inference performed using proteotypic peptides only) [81:37] Quantification [81:39] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample5_S3.wiff.quant. [81:40] File #16/18 [81:40] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S1.wiff [86:52] 68709 library precursors are potentially detectable [86:52] Processing... [87:02] RT window set to 2.50451 [87:02] Recommended MS1 mass accuracy setting: 24.4024 ppm [87:30] Removing low confidence identifications [87:30] Removing interfering precursors [87:33] Training the neural network: 33850 targets, 56504 decoys [87:36] Number of IDs at 0.01 FDR: 19333 [87:37] Calculating protein q-values [87:37] Number of protein isoforms identified at 1% FDR: 1963 (precursor-level), 1781 (protein-level) (inference performed using proteotypic peptides only) [87:37] Quantification [87:39] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S1.wiff.quant. [87:39] File #17/18 [87:39] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S2.wiff [92:44] 68709 library precursors are potentially detectable [92:44] Processing... [92:55] RT window set to 2.68479 [92:55] Recommended MS1 mass accuracy setting: 27.0798 ppm [93:22] Removing low confidence identifications [93:22] Removing interfering precursors [93:26] Training the neural network: 32187 targets, 57151 decoys [93:28] Number of IDs at 0.01 FDR: 18828 [93:29] Calculating protein q-values [93:29] Number of protein isoforms identified at 1% FDR: 1927 (precursor-level), 1788 (protein-level) (inference performed using proteotypic peptides only) [93:29] Quantification [93:31] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S2.wiff.quant. [93:31] File #18/18 [93:31] Loading run D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S3.wiff [98:25] 68709 library precursors are potentially detectable [98:25] Processing... [98:35] RT window set to 2.51112 [98:35] Recommended MS1 mass accuracy setting: 33.9365 ppm [99:02] Removing low confidence identifications [99:02] Removing interfering precursors [99:06] Training the neural network: 32171 targets, 57226 decoys [99:09] Number of IDs at 0.01 FDR: 18295 [99:09] Calculating protein q-values [99:09] Number of protein isoforms identified at 1% FDR: 1895 (precursor-level), 1758 (protein-level) (inference performed using proteotypic peptides only) [99:09] Quantification [99:11] Quantification information saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\EC_CY_sample6_S3.wiff.quant. [99:12] Cross-run analysis [99:12] Reading quantification information: 18 files [99:12] Quantifying peptides [99:17] Assembling protein groups [99:18] Quantifying proteins [99:18] Calculating q-values for protein and gene groups [99:18] Writing report [99:33] Report saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.tsv. [99:33] Saving precursor levels matrix [99:33] Precursor levels matrix (1% precursor and protein group FDR) saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.pr_matrix.tsv. [99:33] Saving protein group levels matrix [99:33] Protein group levels matrix (1% precursor FDR and protein group FDR) saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.pg_matrix.tsv. [99:33] Saving gene group levels matrix [99:33] Gene groups levels matrix (1% precursor FDR and gene group FDR) saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.gg_matrix.tsv. [99:33] Saving unique genes levels matrix [99:33] Unique genes levels matrix (1% precursor FDR and unique protein FDR) saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.unique_genes_matrix.tsv. [99:34] Stats report saved to D:\Data\niwa_DIANN\230608CY_EC_SWATH6x2\230608CY_EC_SWATH6_rep1.stats.tsv