cannot load the file, skipping

[zhaojinzhi-1992]

diann.exe --f "F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw " --lib "" --threads 12 --verbose 1 --out "C:\DIA-NN\1.8.1\report.tsv" --qvalue 0.01 --matrices --out-lib "F:\ZJZ\G-test12\DIA-NN-report\2.tsv" --gen-spec-lib --predictor --fasta "F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta" --fasta-search --min-fr-mz 200 --max-fr-mz 1800 --met-excision --cut K,R --missed-cleavages 1 --min-pep-len 7 --max-pep-len 30 --min-pr-mz 300 --max-pr-mz 1800 --min-pr-charge 1 --max-pr-charge 4 --unimod4 --reanalyse --relaxed-prot-inf --smart-profiling --peak-center --no-ifs-removal DIA-NN 1.8.1 (Data-Independent Acquisition by Neural Networks) Compiled on Apr 14 2022 15:31:19 Current date and time: Wed Apr 12 14:01:28 2023 CPU: GenuineIntel 12th Gen Intel(R) Core(TM) i7-12700 SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 Logical CPU cores: 20 Thread number set to 12 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 200 Max fragment m/z set to 1800 N-terminal methionine excision enabled In silico digest will involve cuts at K,R Maximum number of missed cleavages set to 1 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 Cysteine carbamidomethylation enabled as a fixed modification 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 WARNING: MBR turned off, two or more raw files are required

1 files will be processed [0:00] Loading FASTA F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta [0:03] Processing FASTA [0:09] Assembling elution groups [0:13] 4909844 precursors generated [0:13] Gene names missing for some isoforms [0:13] Library contains 23777 proteins, and 23394 genes [0:14] Encoding peptides for spectra and RTs prediction [0:20] Predicting spectra and IMs [23:10] Predicting RTs [25:23] Decoding predicted spectra and IMs [25:30] Decoding RTs [25:33] Saving the library to F:\ZJZ\G-test12\DIA-NN-report\2.predicted.speclib [27:16] Initialising library

[27:18] File #1/1 [27:18] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:18] 0 library precursors are potentially detectable [27:18] Processing... [27:18] Using MS1 mass accuracy: 20 ppm [27:18] Using mass accuracy: 20 ppm [27:18] Removing low confidence identifications [27:18] Removing interfering precursors [27:18] Too few confident identifications, neural networks will not be used [27:18] Number of IDs at 0.01 FDR: 0 [27:18] Calculating protein q-values [27:18] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:18] Quantification [27:18] Quantification information saved to F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw.quant.

ERROR: DIA-NN tried but failed to load the following files: F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw [27:18] Cross-run analysis [27:18] Reading quantification information: 1 files [27:18] Quantifying peptides [27:18] Assembling protein groups [27:20] Quantifying proteins [27:21] Calculating q-values for protein and gene groups [27:21] Calculating global q-values for protein and gene groups [27:21] Writing report [27:21] Report saved to C:\DIA-NN\1.8.1\report.tsv. [27:21] Saving precursor levels matrix [27:21] Precursor levels matrix (1% precursor and protein group FDR) saved to C:\DIA-NN\1.8.1\report.pr_matrix.tsv. [27:21] Saving protein group levels matrix [27:21] Saving gene group levels matrix [27:21] Saving unique genes levels matrix [27:21] Stats report saved to C:\DIA-NN\1.8.1\report.stats.tsv [27:21] Generating spectral library: [27:21] 0 precursors passing the FDR threshold are to be extracted [27:21] Saving spectral library to F:\ZJZ\G-test12\DIA-NN-report\2.tsv [27:21] 0 precursors saved [27:21] Loading the generated library and saving it in the .speclib format [27:21] Loading spectral library F:\ZJZ\G-test12\DIA-NN-report\2.tsv [27:21] Spectral library loaded: 0 protein isoforms, 0 protein groups and 0 precursors in 1 elution groups. [27:21] Loading protein annotations from FASTA F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta [27:21] Library contains 0 proteins, and 0 genes [27:21] Saving the library to F:\ZJZ\G-test12\DIA-NN-report\2.tsv.speclib [27:21] Log saved to C:\DIA-NN\1.8.1\report.log.txt Finished

DIA-NN exited DIA-NN-plotter.exe "C:\DIA-NN\1.8.1\report.stats.tsv" "C:\DIA-NN\1.8.1\report.tsv" "C:\DIA-NN\1.8.1\report.pdf" PDF report will be generated in the background

diann.exe --f "F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw " --f "F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw " --f "F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw " --lib "" --threads 12 --verbose 1 --out "C:\DIA-NN\1.8.1\report.tsv" --qvalue 0.01 --matrices --out-lib "F:\ZJZ\G-test12\DIA-NN-report\2.tsv" --gen-spec-lib --predictor --fasta "F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta" --fasta-search --min-fr-mz 200 --max-fr-mz 1800 --met-excision --cut K,R --missed-cleavages 1 --min-pep-len 7 --max-pep-len 30 --min-pr-mz 300 --max-pr-mz 1800 --min-pr-charge 1 --max-pr-charge 4 --unimod4 --reanalyse --relaxed-prot-inf --smart-profiling --peak-center --no-ifs-removal DIA-NN 1.8.1 (Data-Independent Acquisition by Neural Networks) Compiled on Apr 14 2022 15:31:19 Current date and time: Wed Apr 12 15:21:41 2023 CPU: GenuineIntel 12th Gen Intel(R) Core(TM) i7-12700 SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 Logical CPU cores: 20 Thread number set to 12 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 200 Max fragment m/z set to 1800 N-terminal methionine excision enabled In silico digest will involve cuts at K,R Maximum number of missed cleavages set to 1 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 Cysteine carbamidomethylation enabled as a fixed modification 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

3 files will be processed [0:00] Loading FASTA F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta [0:03] Processing FASTA [0:09] Assembling elution groups [0:14] 4909844 precursors generated [0:14] Gene names missing for some isoforms [0:14] Library contains 23777 proteins, and 23394 genes [0:14] Encoding peptides for spectra and RTs prediction [0:20] Predicting spectra and IMs [23:35] Predicting RTs [25:45] Decoding predicted spectra and IMs [25:53] Decoding RTs [25:55] Saving the library to F:\ZJZ\G-test12\DIA-NN-report\2.predicted.speclib [27:41] Initialising library

[27:43] First pass: generating a spectral library from DIA data [27:43] File #1/3 [27:43] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:43] 0 library precursors are potentially detectable [27:43] Processing... [27:43] Using MS1 mass accuracy: 20 ppm [27:43] Using mass accuracy: 20 ppm [27:43] Removing low confidence identifications [27:43] Removing interfering precursors [27:43] Too few confident identifications, neural networks will not be used [27:43] Number of IDs at 0.01 FDR: 0 [27:43] Calculating protein q-values [27:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:43] Quantification [27:43] Quantification information saved to F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw.quant.

[27:43] File #2/3 [27:43] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:43] 0 library precursors are potentially detectable [27:43] Processing... [27:43] Using MS1 mass accuracy: 20 ppm [27:43] Using mass accuracy: 20 ppm [27:43] Removing low confidence identifications [27:43] Removing interfering precursors [27:43] Too few confident identifications, neural networks will not be used [27:43] Number of IDs at 0.01 FDR: 0 [27:43] Calculating protein q-values [27:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:43] Quantification [27:43] Quantification information saved to F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw.quant.

[27:43] File #3/3 [27:43] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:43] 0 library precursors are potentially detectable [27:43] Processing... [27:43] Using MS1 mass accuracy: 20 ppm [27:43] Using mass accuracy: 20 ppm [27:43] Removing low confidence identifications [27:43] Removing interfering precursors [27:43] Too few confident identifications, neural networks will not be used [27:43] Number of IDs at 0.01 FDR: 0 [27:43] Calculating protein q-values [27:43] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:43] Quantification [27:43] Quantification information saved to F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw.quant.

ERROR: DIA-NN tried but failed to load the following files: F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw, F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw, F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw [27:43] Cross-run analysis [27:43] Reading quantification information: 3 files [27:43] Quantifying peptides WARNING: not enough peptides for normalisation [27:43] Assembling protein groups [27:45] Quantifying proteins [27:45] Calculating q-values for protein and gene groups [27:45] Calculating global q-values for protein and gene groups [27:45] Writing report [27:46] Report saved to C:\DIA-NN\1.8.1\report-first-pass.tsv. [27:46] Saving precursor levels matrix [27:46] Precursor levels matrix (1% precursor and protein group FDR) saved to C:\DIA-NN\1.8.1\report-first-pass.pr_matrix.tsv. [27:46] Saving protein group levels matrix [27:46] Saving gene group levels matrix [27:46] Saving unique genes levels matrix [27:46] Stats report saved to C:\DIA-NN\1.8.1\report-first-pass.stats.tsv [27:46] Generating spectral library: [27:46] 0 precursors passing the FDR threshold are to be extracted [27:46] Saving spectral library to F:\ZJZ\G-test12\DIA-NN-report\2.tsv [27:46] 0 precursors saved [27:46] Loading the generated library and saving it in the .speclib format [27:46] Loading spectral library F:\ZJZ\G-test12\DIA-NN-report\2.tsv [27:46] Spectral library loaded: 0 protein isoforms, 0 protein groups and 0 precursors in 1 elution groups. [27:46] Loading protein annotations from FASTA F:\ZJZ\G-test12\fasta\Fasta-Merged_mouse-yeast-IRT-Review_10090-Total_559292-iRT_Fusion-20211103.fasta [27:46] Library contains 0 proteins, and 0 genes [27:46] Saving the library to F:\ZJZ\G-test12\DIA-NN-report\2.tsv.speclib

[27:49] Second pass: using the newly created spectral library to reanalyse the data [27:49] File #1/3 [27:49] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:49] 0 library precursors are potentially detectable [27:49] Processing... [27:49] Using MS1 mass accuracy: 20 ppm [27:49] Using mass accuracy: 20 ppm [27:49] Removing low confidence identifications [27:49] Removing interfering precursors [27:49] Too few confident identifications, neural networks will not be used [27:49] Number of IDs at 0.01 FDR: 0 [27:49] Calculating protein q-values [27:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:49] Quantification

[27:49] File #2/3 [27:49] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:49] 0 library precursors are potentially detectable [27:49] Processing... [27:49] Using MS1 mass accuracy: 20 ppm [27:49] Using mass accuracy: 20 ppm [27:49] Removing low confidence identifications [27:49] Removing interfering precursors [27:49] Too few confident identifications, neural networks will not be used [27:49] Number of IDs at 0.01 FDR: 0 [27:49] Calculating protein q-values [27:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:49] Quantification

[27:49] File #3/3 [27:49] Loading run F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [27:49] 0 library precursors are potentially detectable [27:49] Processing... [27:49] Using MS1 mass accuracy: 20 ppm [27:49] Using mass accuracy: 20 ppm [27:49] Removing low confidence identifications [27:49] Removing interfering precursors [27:49] Too few confident identifications, neural networks will not be used [27:49] Number of IDs at 0.01 FDR: 0 [27:49] Calculating protein q-values [27:49] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [27:49] Quantification

ERROR: DIA-NN tried but failed to load the following files: F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_2.raw, F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_3.raw, F:\ZJZ\G-test12\DIA\HF_20210517_M200-Y800_DIA_4.raw [27:49] Cross-run analysis [27:49] Reading quantification information: 3 files [27:49] Quantifying peptides WARNING: not enough peptides for normalisation [27:49] Quantifying proteins [27:49] Calculating q-values for protein and gene groups [27:49] Calculating global q-values for protein and gene groups [27:49] Writing report [27:49] Report saved to C:\DIA-NN\1.8.1\report.tsv. [27:49] Saving precursor levels matrix [27:49] Precursor levels matrix (1% precursor and protein group FDR) saved to C:\DIA-NN\1.8.1\report.pr_matrix.tsv. [27:49] Saving protein group levels matrix [27:49] Saving gene group levels matrix [27:49] Saving unique genes levels matrix [27:49] Stats report saved to C:\DIA-NN\1.8.1\report.stats.tsv [27:49] Log saved to C:\DIA-NN\1.8.1\report.log.txt Finished

DIA-NN exited DIA-NN-plotter.exe "C:\DIA-NN\1.8.1\report.stats.tsv" "C:\DIA-NN\1.8.1\report.tsv" "C:\DIA-NN\1.8.1\report.pdf" PDF report will be generated in the background

[vdemichev]

MSFileReader needs to be installed, please see the docs

[li-jiamiao]

MSFileReader needs to be installed, please see the docs

I have installed it. But I still got the same error message. Could you help me? THANKS! Skyline found: Skyline-Daily (64 bit) 24.1.1.202 MSFileReader found: MSFileReader Core 31

diann.exe --f "F:\ljm\20240722-plasma-219.raw " --f "F:\ljm\20240722-plasma-233.raw " --f "F:\ljm\20240722-plasma-a09.raw " --f "F:\ljm\20240722-plasma-a38.raw " --lib "" --threads 14 --verbose 1 --out "F:\ljm\DIA-NN/report.tsv" --qvalue 0.01 --matrices --out-lib "F:\ljm\DIA-NN\report-lib.parquet" --gen-spec-lib --predictor --fasta "F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta" --fasta-search --min-fr-mz 200 --max-fr-mz 1800 --met-excision --min-pep-len 7 --max-pep-len 30 --min-pr-mz 300 --max-pr-mz 1800 --min-pr-charge 1 --max-pr-charge 4 --cut K,R --missed-cleavages 1 --unimod4 --individual-mass-acc --individual-windows --peptidoforms --reanalyse --relaxed-prot-inf --rt-profiling DIA-NN 1.9.1 (Data-Independent Acquisition by Neural Networks) Compiled on Jul 15 2024 15:40:36 Current date and time: Mon Jul 29 17:55:40 2024 CPU: GenuineIntel Intel(R) Xeon(R) CPU E5-2630L v3 @ 1.80GHz SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 Logical CPU cores: 16 Thread number set to 14 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 DIA-NN will carry out FASTA digest for in silico lib generation Min fragment m/z set to 200 Max fragment m/z set to 1800 N-terminal methionine excision enabled 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 In silico digest will involve cuts at K,R Maximum number of missed cleavages set to 1 Cysteine carbamidomethylation enabled as a fixed modification Mass accuracy will be determined separately for different runs Scan windows will be inferred separately for different runs 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 DIA-NN will optimise the mass accuracy separately for each 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

4 files will be processed [0:00] Loading FASTA F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [0:11] Processing FASTA [0:41] Assembling elution groups [1:05] 8129368 precursors generated [1:05] Gene names missing for some isoforms [1:05] Library contains 52050 proteins, and 31320 genes [1:17] Encoding peptides for spectra and RTs prediction [1:40] Predicting spectra and IMs [73:49] Predicting RTs [82:26] Decoding predicted spectra and IMs [82:55] Decoding RTs [82:59] Saving the library to F:\ljm\DIA-NN\report-lib.predicted.speclib [84:13] Initialising library [84:57] Loading spectral library F:\ljm\DIA-NN\report-lib.predicted.speclib [85:41] Library annotated with sequence database(s): F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [85:46] Spectral library loaded: 52050 protein isoforms, 88364 protein groups and 8129368 precursors in 2530385 elution groups. [85:46] Loading protein annotations from FASTA F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [85:49] Annotating library proteins with information from the FASTA database [85:49] Gene names missing for some isoforms [85:49] Library contains 52050 proteins, and 31320 genes [86:11] Encoding peptides for spectra and RTs prediction [86:39] Predicting spectra and IMs [158:03] Predicting RTs [166:38] Decoding predicted spectra and IMs [167:07] Decoding RTs [167:10] Saving the library to F:\ljm\DIA-NN\report-lib.predicted.speclib [168:01] Initialising library

First pass: generating a spectral library from DIA data

[168:30] File #1/4 [168:30] Loading run F:\ljm\20240722-plasma-219.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [168:30] 0 library precursors are potentially detectable [168:30] Processing... [168:30] Using MS1 mass accuracy: 20 ppm [168:30] Using mass accuracy: 20 ppm [168:31] Removing low confidence identifications [168:32] Removing interfering precursors [168:32] Too few confident identifications, neural networks will not be used [168:32] Number of IDs at 0.01 FDR: 0 [168:32] Calculating protein q-values [168:32] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [168:32] Quantification [168:32] Quantification information saved to F:\ljm\20240722-plasma-219.raw.quant

[168:32] File #2/4 [168:32] Loading run F:\ljm\20240722-plasma-233.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [168:32] 0 library precursors are potentially detectable [168:32] Processing... [168:32] Using MS1 mass accuracy: 20 ppm [168:32] Using mass accuracy: 20 ppm [168:33] Removing low confidence identifications [168:33] Removing interfering precursors [168:34] Too few confident identifications, neural networks will not be used [168:34] Number of IDs at 0.01 FDR: 0 [168:34] Calculating protein q-values [168:34] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [168:34] Quantification [168:34] Quantification information saved to F:\ljm\20240722-plasma-233.raw.quant

[168:34] File #3/4 [168:34] Loading run F:\ljm\20240722-plasma-a09.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [168:34] 0 library precursors are potentially detectable [168:34] Processing... [168:34] Using MS1 mass accuracy: 20 ppm [168:34] Using mass accuracy: 20 ppm [168:34] Removing low confidence identifications [168:35] Removing interfering precursors [168:35] Too few confident identifications, neural networks will not be used [168:35] Number of IDs at 0.01 FDR: 0 [168:35] Calculating protein q-values [168:35] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [168:35] Quantification [168:35] Quantification information saved to F:\ljm\20240722-plasma-a09.raw.quant

[168:35] File #4/4 [168:35] Loading run F:\ljm\20240722-plasma-a38.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [168:36] 0 library precursors are potentially detectable [168:36] Processing... [168:36] Using MS1 mass accuracy: 20 ppm [168:36] Using mass accuracy: 20 ppm [168:36] Removing low confidence identifications [168:37] Removing interfering precursors [168:37] Too few confident identifications, neural networks will not be used [168:37] Number of IDs at 0.01 FDR: 0 [168:37] Calculating protein q-values [168:37] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [168:37] Quantification [168:37] Quantification information saved to F:\ljm\20240722-plasma-a38.raw.quant

ERROR: DIA-NN tried but failed to load the following files: F:\ljm\20240722-plasma-219.raw, F:\ljm\20240722-plasma-233.raw, F:\ljm\20240722-plasma-a09.raw, F:\ljm\20240722-plasma-a38.raw [168:37] Cross-run analysis [168:37] Reading quantification information: 4 files [168:38] Averaged recommended settings for this experiment: Mass accuracy = 20ppm, MS1 accuracy = 20ppm, Scan window = 10 [168:41] Quantifying peptides WARNING: not enough peptides for normalisation WARNING: not enough peptides for normalisation [168:41] Assembling protein groups [168:45] Quantifying proteins [168:45] Calculating q-values for protein and gene groups [168:48] Calculating global q-values for protein and gene groups [168:48] Protein groups with global q-value <= 0.01: 0 [168:48] Compressed report saved to F:\ljm\DIA-NN/report-first-pass.parquet. Use R 'arrow' or Python 'PyArrow' package to process [168:48] Writing report [168:48] Report saved to F:\ljm\DIA-NN/report-first-pass.tsv. [168:48] Saving precursor levels matrix [168:48] Precursor levels matrix (1% precursor and protein group FDR) saved to F:\ljm\DIA-NN/report-first-pass.pr_matrix.tsv. [168:48] Manifest saved to F:\ljm\DIA-NN/report-first-pass.manifest.txt [168:48] Stats report saved to F:\ljm\DIA-NN/report-first-pass.stats.tsv [168:48] Generating spectral library: [168:49] 0 precursors saved [168:49] Spectral library saved to F:\ljm\DIA-NN\report-lib.parquet

[168:51] Loading spectral library F:\ljm\DIA-NN\report-lib.parquet [168:51] Spectral library loaded: 0 protein isoforms, 0 protein groups and 0 precursors in 1 elution groups. [168:51] Loading FASTA F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [169:52] WARNING: no protein information found in the library. Annotating library precursors with information from the FASTA database [169:52] 0 precursors generated [169:52] Library contains 0 proteins, and 0 genes [169:53] Initialising library [169:53] Saving the library to F:\ljm\DIA-NN\report-lib.parquet.skyline.speclib

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

[169:53] File #1/4 [169:53] Loading run F:\ljm\20240722-plasma-219.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [169:53] 0 library precursors are potentially detectable [169:53] Processing... [169:53] Using MS1 mass accuracy: 20 ppm [169:53] Using mass accuracy: 20 ppm [169:53] Removing low confidence identifications [169:53] Removing interfering precursors [169:53] Too few confident identifications, neural networks will not be used [169:53] Number of IDs at 0.01 FDR: 0 [169:53] No protein annotation, skipping protein q-value calculation [169:53] Quantification

[169:53] File #2/4 [169:53] Loading run F:\ljm\20240722-plasma-233.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [169:53] 0 library precursors are potentially detectable [169:53] Processing... [169:53] Using MS1 mass accuracy: 20 ppm [169:53] Using mass accuracy: 20 ppm [169:53] Removing low confidence identifications [169:53] Removing interfering precursors [169:53] Too few confident identifications, neural networks will not be used [169:53] Number of IDs at 0.01 FDR: 0 [169:53] No protein annotation, skipping protein q-value calculation [169:53] Quantification

[169:53] File #3/4 [169:53] Loading run F:\ljm\20240722-plasma-a09.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [169:53] 0 library precursors are potentially detectable [169:53] Processing... [169:53] Using MS1 mass accuracy: 20 ppm [169:53] Using mass accuracy: 20 ppm [169:53] Removing low confidence identifications [169:53] Removing interfering precursors [169:53] Too few confident identifications, neural networks will not be used [169:53] Number of IDs at 0.01 FDR: 0 [169:53] No protein annotation, skipping protein q-value calculation [169:53] Quantification

[169:53] File #4/4 [169:53] Loading run F:\ljm\20240722-plasma-a38.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [169:53] 0 library precursors are potentially detectable [169:53] Processing... [169:53] Using MS1 mass accuracy: 20 ppm [169:53] Using mass accuracy: 20 ppm [169:53] Removing low confidence identifications [169:53] Removing interfering precursors [169:53] Too few confident identifications, neural networks will not be used [169:53] Number of IDs at 0.01 FDR: 0 [169:53] No protein annotation, skipping protein q-value calculation [169:53] Quantification

ERROR: DIA-NN tried but failed to load the following files: F:\ljm\20240722-plasma-219.raw, F:\ljm\20240722-plasma-233.raw, F:\ljm\20240722-plasma-a09.raw, F:\ljm\20240722-plasma-a38.raw [169:53] Cross-run analysis [169:53] Reading quantification information: 4 files [169:53] Averaged recommended settings for this experiment: Mass accuracy = 20ppm, MS1 accuracy = 20ppm, Scan window = 10 [169:53] Quantifying peptides WARNING: not enough peptides for normalisation WARNING: not enough peptides for normalisation [169:53] Quantifying proteins [169:53] Calculating q-values for protein and gene groups [169:53] Calculating global q-values for protein and gene groups [169:53] Protein groups with global q-value <= 0.01: 0 [169:53] Compressed report saved to F:\ljm\DIA-NN/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process [169:53] Writing report [169:53] Report saved to F:\ljm\DIA-NN/report.tsv. [169:53] Saving precursor levels matrix [169:53] Precursor levels matrix (1% precursor and protein group FDR) saved to F:\ljm\DIA-NN/report.pr_matrix.tsv. [169:53] Saving protein group levels matrix [169:53] Saving gene group levels matrix [169:53] Saving unique genes levels matrix [169:53] Manifest saved to F:\ljm\DIA-NN/report.manifest.txt [169:53] Stats report saved to F:\ljm\DIA-NN/report.stats.tsv

The following warnings or errors (in alphabetic order) were detected at least the indicated number of times: ERROR: DIA-NN tried but failed to load the following files: F:\ljm\20240722-plasma-219.raw, F:\ljm\20240722-plasma-233.raw, F:\ljm\20240722-plasma-a09.raw, F:\ljm\20240722-plasma-a38.raw : 2 ERROR: cannot load the file, skipping : 8 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 : 1 WARNING: no protein information found in the library. Annotating library precursors with information from the FASTA database : 1 WARNING: not enough peptides for normalisation : 4 Finished

How to cite: using DIA-NN: Demichev et al, Nature Methods, 2020, https://www.nature.com/articles/s41592-019-0638-x analysing Scanning SWATH: Messner et al, Nature Biotechnology, 2021, https://www.nature.com/articles/s41587-021-00860-4 analysing PTMs: Steger et al, Nature Communications, 2021, https://www.nature.com/articles/s41467-021-25454-1 analysing dia-PASEF: Demichev et al, Nature Communications, 2022, https://www.nature.com/articles/s41467-022-31492-0 analysing Slice-PASEF: Szyrwiel et al, biorxiv, 2022, https://doi.org/10.1101/2022.10.31.514544 plexDIA / multiplexed DIA: Derks et al, Nature Biotechnology, 2023, https://www.nature.com/articles/s41587-022-01389-w CysQuant: Huang et al, Redox Biology, 2023, https://doi.org/10.1016/j.redox.2023.102908 using QuantUMS: Kistner at al, biorxiv, 2023, https://doi.org/10.1101/2023.06.20.545604 [169:53] Log saved to F:\ljm\DIA-NN/report.log.txt

DIA-NN exited DIA-NN-plotter.exe "F:\ljm\DIA-NN\report.stats.tsv" "F:\ljm\DIA-NN/report.tsv" "F:\ljm\DIA-NN\report.pdf" PDF report will be generated in the background

[vdemichev]

Does DIA-NN load fine some publicly available .raw runs, e.g. Fig2HeLa-0-5h_MHRM_R01_T0.raw from https://ftp.pride.ebi.ac.uk/pride/data/archive/2017/10/PXD005573/?

[li-jiamiao]

Does DIA-NN load fine some publicly available .raw runs, e.g. Fig2HeLa-0-5h_MHRM_R01_T0.raw from https://ftp.pride.ebi.ac.uk/pride/data/archive/2017/10/PXD005573/? Hi， I am so sorry I failed again. I reinstalled the MSFileReader through the link you gave me yesterday. It still shows the version is Core 31. Today, I loaded the publicly available file to try again. Unfortunately, it doesn't work. What should I do next? Here is the error message. Thank you so much.

Skyline found: Skyline-Daily (64 bit) 24.1.1.202 MSFileReader found: MSFileReader Core 31

F:\ljm\DIA-NN\DiaNN.exe --f "F:\ljm\Fig2HeLa-0-5h_MHRM_R01_T0.raw " --lib "" --threads 14 --verbose 1 --out "F:\ljm\DIA-NN/report.tsv" --qvalue 0.01 --matrices --out-lib "F:\ljm\DIA-NN\report-lib.parquet" --gen-spec-lib --predictor --fasta "F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta" --fasta-search --min-fr-mz 200 --max-fr-mz 1800 --met-excision --min-pep-len 7 --max-pep-len 30 --min-pr-mz 300 --max-pr-mz 1800 --min-pr-charge 1 --max-pr-charge 4 --cut K,R --missed-cleavages 1 --unimod4 --reanalyse --relaxed-prot-inf --rt-profiling DIA-NN 1.9.1 (Data-Independent Acquisition by Neural Networks) Compiled on Jul 15 2024 15:40:36 Current date and time: Tue Jul 30 17:19:38 2024 CPU: GenuineIntel Intel(R) Xeon(R) CPU E5-2630L v3 @ 1.80GHz SIMD instructions: AVX AVX2 FMA SSE4.1 SSE4.2 Logical CPU cores: 16 Thread number set to 14 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 DIA-NN will carry out FASTA digest for in silico lib generation Min fragment m/z set to 200 Max fragment m/z set to 1800 N-terminal methionine excision enabled 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 In silico digest will involve cuts at K,R Maximum number of missed cleavages set to 1 Cysteine carbamidomethylation enabled as a fixed modification 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 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 WARNING: MBR turned off, two or more raw files are required

1 files will be processed [0:00] Loading FASTA F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [0:12] Processing FASTA [0:41] Assembling elution groups [1:04] 8129368 precursors generated [1:04] Gene names missing for some isoforms [1:04] Library contains 52050 proteins, and 31320 genes [1:17] Encoding peptides for spectra and RTs prediction [1:40] Predicting spectra and IMs [70:58] Predicting RTs [78:33] Decoding predicted spectra and IMs [79:02] Decoding RTs [79:04] Saving the library to F:\ljm\DIA-NN\report-lib.predicted.speclib [79:55] Initialising library [80:27] Loading spectral library F:\ljm\DIA-NN\report-lib.predicted.speclib [81:03] Library annotated with sequence database(s): F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [81:07] Spectral library loaded: 52050 protein isoforms, 88364 protein groups and 8129368 precursors in 2530385 elution groups. [81:07] Loading protein annotations from FASTA F:\ljm\MaxQuant_v2.6.3.0\uniprotkb_human_AND_reviewed_true_2024_07_23.fasta [81:09] Annotating library proteins with information from the FASTA database [81:09] Gene names missing for some isoforms [81:09] Library contains 52050 proteins, and 31320 genes [81:26] Encoding peptides for spectra and RTs prediction [81:50] Predicting spectra and IMs [152:17] Predicting RTs [160:14] Decoding predicted spectra and IMs [160:43] Decoding RTs [160:45] Saving the library to F:\ljm\DIA-NN\report-lib.predicted.speclib [161:36] Initialising library

[162:05] File #1/1 [162:05] Loading run F:\ljm\Fig2HeLa-0-5h_MHRM_R01_T0.raw No MS2 spectra: aborting ERROR: cannot load the file, skipping [162:06] 0 library precursors are potentially detectable [162:06] Processing... [162:06] Using MS1 mass accuracy: 20 ppm [162:06] Using mass accuracy: 20 ppm [162:07] Removing low confidence identifications [162:07] Removing interfering precursors [162:07] Too few confident identifications, neural networks will not be used [162:07] Number of IDs at 0.01 FDR: 0 [162:07] Calculating protein q-values [162:07] Number of genes identified at 1% FDR: 0 (precursor-level), 0 (protein-level) (inference performed using proteotypic peptides only) [162:07] Quantification [162:07] Quantification information saved to F:\ljm\Fig2HeLa-0-5h_MHRM_R01_T0.raw.quant

ERROR: DIA-NN tried but failed to load the following files: F:\ljm\Fig2HeLa-0-5h_MHRM_R01_T0.raw [162:07] Cross-run analysis [162:07] Reading quantification information: 1 files [162:10] Quantifying peptides [162:10] Assembling protein groups [162:14] Quantifying proteins [162:15] Calculating q-values for protein and gene groups [162:16] Calculating global q-values for protein and gene groups [162:16] Protein groups with global q-value <= 0.01: 0 [162:16] Compressed report saved to F:\ljm\DIA-NN/report.parquet. Use R 'arrow' or Python 'PyArrow' package to process [162:16] Writing report [162:16] Report saved to F:\ljm\DIA-NN/report.tsv. [162:16] Saving precursor levels matrix [162:16] Precursor levels matrix (1% precursor and protein group FDR) saved to F:\ljm\DIA-NN/report.pr_matrix.tsv. [162:16] Saving protein group levels matrix [162:16] Saving gene group levels matrix [162:16] Saving unique genes levels matrix [162:17] Manifest saved to F:\ljm\DIA-NN/report.manifest.txt [162:17] Stats report saved to F:\ljm\DIA-NN/report.stats.tsv [162:17] Generating spectral library: [162:17] 0 precursors saved [162:17] Spectral library saved to F:\ljm\DIA-NN\report-lib.parquet

The following warnings or errors (in alphabetic order) were detected at least the indicated number of times: ERROR: DIA-NN tried but failed to load the following files: F:\ljm\Fig2HeLa-0-5h_MHRM_R01_T0.raw : 1 ERROR: cannot load the file, skipping : 1 WARNING: MBR turned off, two or more raw files are required : 1 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 : 1 Finished

How to cite: using DIA-NN: Demichev et al, Nature Methods, 2020, https://www.nature.com/articles/s41592-019-0638-x analysing Scanning SWATH: Messner et al, Nature Biotechnology, 2021, https://www.nature.com/articles/s41587-021-00860-4 analysing PTMs: Steger et al, Nature Communications, 2021, https://www.nature.com/articles/s41467-021-25454-1 analysing dia-PASEF: Demichev et al, Nature Communications, 2022, https://www.nature.com/articles/s41467-022-31492-0 analysing Slice-PASEF: Szyrwiel et al, biorxiv, 2022, https://doi.org/10.1101/2022.10.31.514544 plexDIA / multiplexed DIA: Derks et al, Nature Biotechnology, 2023, https://www.nature.com/articles/s41587-022-01389-w CysQuant: Huang et al, Redox Biology, 2023, https://doi.org/10.1016/j.redox.2023.102908 using QuantUMS: Kistner at al, biorxiv, 2023, https://doi.org/10.1101/2023.06.20.545604 [162:17] Log saved to F:\ljm\DIA-NN/report.log.txt

DIA-NN exited DIA-NN-plotter.exe "F:\ljm\DIA-NN\report.stats.tsv" "F:\ljm\DIA-NN/report.tsv" "F:\ljm\DIA-NN\report.pdf" PDF report will be generated in the background

[vdemichev]

OK, this means the correct MSFileReader not installed. So I would suggest to uninstall the version you have and try again installing the one by the link in the docs (3.0 SP3).

To test, don't need to predict a large library, can do with absolutely any library

[li-jiamiao]

OK, this means the correct MSFileReader not installed. So I would suggest to uninstall the version you have and try again installing the one by the link in the docs (3.0 SP3).

To test, don't need to predict a large library, can do with absolutely any library

Thank you! I will try again.

[li-jiamiao]

OK, this means the correct MSFileReader not installed. So I would suggest to uninstall the version you have and try again installing the one by the link in the docs (3.0 SP3).

To test, don't need to predict a large library, can do with absolutely any library

It is very strange. The version (3.0 SP3) is the core 31. @。@！