dataesr/scientific-paragraphs-categorization huggingface dataset:
The Fusion Lumos precursor charge interquartile spanned +5 to +10 (maximum of +44), while the Q-Exactive HF interquartile range was +4 to +10 (maximum of +56). Four additional experiments from the Q-Exactive HF and four from the Orbitrap Fusion Lumos collected MS scans at low resolution to improve sensitivity for larger masses; these are included in the PXD repository though they are not analyzed here. A Q-Exactive HF-X analyzed twenty-four fractions of a bottom-up TMT multiplex set spanning these and other milk samples. More detailed methods may be found in Supporting Information Text S1. The complete UP000009136 reference proteome contains 37,883 proteins. It was reduced to a subset FASTA of 5388 sequences via MSFragger and IDPicker 3. 1 using the bottom-up TMT data. This database was used for a top-down search with ProSight PD, TopPIC, pTop, and MSPathFinderT, and any accession matched to any spectrum with high confidence by one of those four engines was retained to produce an accession list of 378 entries.
The UniProt Subsetter described below was used to harvest this set of sequences to FASTA and UniProtKB XML databases used in the PTM search by all six algorithms (TopMG joining TopPIC, and ProSight PD employing both FASTA and XML inputs). PXD005420 Human. Delcourt et al. evaluated human serous ovarian tumors through liquid micro-junction (LMJ) and parafilm-assisted microdissection (PAM). 30 The samples included necrotic/fibrotic tumor, tumor, and benign regions of interest. Our PTM characterization included only the tumor and benign LMJ and PAM analyses in technical triplicate, yielding a total of twelve Q-Exactive HCD raw files split among four samples: LB (LMJ-Benign), LT (LMJ-Tumor), PB (PAM-Benign), and PT (PAM-Tumor). The PAM analyses averaged more MS/MS (5728) than did the LMJ analyses (4009).
Unlike the other ThermoFisher data sets, the TopFD deconvolutions of these files contained large numbers of singly charged precursor ions. After excluding those, the four samples yielded a charge interquartile range from +4 or +5 to +10, with a maximum overall of +28. We took advantage of the rapid search engines pTop and ProSight PD to shrink the full-size human reference database (UP000005640: 101,014 entries) to one containing just the accessions matched to any PrSM by either algorithm (558 entries). This reduced database was then used to support a PTM search allowing for up to four PTMs per PrSM. Bruker Q-TOF Data Sets PXD010825 PIG. Brown et al. identified proteins in S. scrofa cardiac material in evaluating the "Azo" surfactant for use in topdown proteomics on a Bruker maXis II instrument.
31 Raw directories containing "analysis. baf" files are available in ProteomeXchange as PXD033208. The three LC-MS/MS experiments were renamed PigHeartAzo-20170429, PigHear-tAzo-20171029, and PigHeartAzo-20171107 to reflect their run dates. The first experiment ran 95 min, while the latter two ran 75 min. After conversion to mzML format in ProteoWizard 3. 0,  32  the three experiments contained 5598, 5155, and 4523 MS/MS scans, respectively. Deconvolved msAlign files were created through a Visual Basic Script for Bruker DataAnalysis 5. 3 described below, yielding precursor charge interquartile ranges of +8 to +23 for the first experiment, +8 to +25 for the second experiment, and +8 to +27 for the third. (The charge distributions reported here for Bruker experiments exclude +1 precursors. ) The UP000008227 reference proteome for pig contained 49,792 proteins when isoform variants were incorporated.
We derived a subset database by using a bottom-up proteome from the same laboratory (MSV000080621  33  ) to find the parsimonious subset of these sequences that could be matched confidently to peptidespectrum matches in MSFragger search followed by IDPicker protein assembly. The subset sequence database contained 3974 sequences. PXD019368 HUMAN. Brown et al. evaluated cloud point extraction and size exclusion chromatography in human embryonic kidney (HEK293T) cells on a Bruker maXis II instrument. 34 Raw directories containing "analysis. baf" files are available in ProteomeXchange as PXD033208. The eight LC-.
Journal of Proteome Research MS/MS experiments were divided equally into Tergitol and Triton cohorts. The Tergitol cohort contained fewer tandem mass spectra (14,365) than did the Triton cohort (16,143). The first two fractions for both cohorts contained far fewer tandem mass spectra (7674) than did the latter two fractions (22,834). Excluding singly charged precursors, the msAlign files created through Bruker DataAnalysis yielded an interquartile precursor charge range from +11 to +27. In order to create a subset database for the identification of these proteoforms, we employed the data set PXD017858,  35  searched in MSFragger and assembled in IDPicker, to produce a sequence database of 15,109 entries. MSV000082070 BOVIN. Vincent et al. evaluated the Bruker maXis I instrument for LC-MS/MS phosphoproteomics using bovine milk samples.
36 We selected the "Holstein" and "Jersey" milk experiments from the raw data folders at MassIVE, excluding instrument methods 1, 4, and 12. These 40-min LC-MS/MS experiments averaged 309 MS/MS apiece, with Method 2 producing a low of 135 MS/MS for both types of milk and Method 11 producing a high of 365 MS/MS for both types of milk. Excluding singly charged precursors, the msAlign files created by Bruker DataAnalysis yielded an interquartile precursor charge range from +4 to +23. A 2016 bottom-up proteome by the same author from bovine milk (PXD002529  37  ) was analyzed by MSFragger and IDPicker to generate a FASTA of 276 protein sequences that could then be used to identify proteoforms in the top-down set.
Top-Down Identification Workflows We selected four top-down search engines that were capable of truncation searches and could be installed for use on local computers (see Figure  1  and Table  2 ). Algorithms that did not completely fulfill these criteria (Perceptron,  38  Mascot Top-Down,  39  MetaMorpheus,  14  and PIITA  40  were not included in our comparison. Perceptron requires a high-end nVidia graphics card and several development kits for installation, which were not available to us. We attempted some Mascot Top-Down searches but were held back by having licensed a relatively old version of Mascot Server. MetaMorpheus was very close to inclusion but its truncation search was not completely implemented when searches were performed. Unfortunately, it appears the source code for PIITA is no longer retrievable.
The precursor tolerance, however, was increased from 10 ppm to 1. 1 Da, increasing both identification yield and the time required for each search. In the most recent version of the software, ProSight 4. 2 for Proteome Discoverer 3. 0, a comparable search would instead retain the 10 ppm precursor tolerance, supplementing it by setting the "Number of Off by 1's" to allow a single neutron slip. This newer approach is expected to reduce potential false positives that may be matched with high mass error tolerance. PrSM tables were exported from Proteome Discoverer in text (tab-delimited) format with three alterations from the default settings: "External Top-Down Displays" was disabled, while "Fragmentation Scan(s)" and "Original Precursor Charge" were enabled. Other than the default N-terminal acetylation, variable modifications were configured in the Database Manager at the time of FASTA or XML import.
TopPIC Suite 1. 4. 13. Because TopIndex requires considerable storage space when handling eukaryotic databases, we employed only TopFD (feature detection/deconvolution) and TopPIC (search engine) from the TopPIC Suite. PXD031744-BOVIN and PXD005420-HUMAN also employed the TopMG algorithm for PTM searching. TopFD deconvolved MS/MS from mzML format to msAlign format, using the "--skip-htmlfolder" option to curtail export of text files to represent each MS/ MS. TopPIC matched proteoforms to tandem mass spectra in msAlign format, using the "--skip-html-folder" option to prevent writing text files to represent each PrSM, the "--combined-filename" option to produce conjoint reports for each set of input files, and the "--num-shift" option to specify one gap in spectral alignment for PTM insertion (except in the PTM searches, where two gaps were allowed).
e. proteoforms that represented internal polypeptides, where both N-terminus and C-terminus were truncated could not be identified). The "-tda 0" option specified a search of target sequences only. Precursor and fragment mass tolerance defaulted to 10 ppm (experiments at 20 ppm yielded very similar numbers of PrSMs). The "-mod" option specified the modifications listed below in "PTM Handling" for each experiment, imposing a maximum of three PTMs per proteoform, except that a limit of four PTMs was employed for PTM searches of PXD031744 and PXD005420. Unlike TopPIC or ProSight PD, MSPathFinderT requires the N-terminal acetylation to be explicitly specified as a PTM, and the software accepts chemical compositions for its PTMs rather than explicit masses. PrSM tables were imported from the set of "_IcTda.
tsv" reports, one for each input raw file. FDR filtering was handled inside the ProForma exporter described below, limiting to an E-value of less than 0. 01 and requiring reported PrSM probabilities to be greater than 0. 5. pTop 2. pTop operation produced interesting challenges because the pParseTD incorporated in the pre-release pTop 2  43  produced sparse MS/MS peak lists, and the pTop search engine in pTop 1. 2 failed to produce reasonable sensitivity in the PXD020342-DANRE and PXD031744-BOVIN sets. After configuring searches in the pTop 2 GUI, we executed the pParseTD. cfg using the pParseTD. exe from pTop 1. 2 and executed the pTop. cfg using the pTop. exe from a pre-release of pTop 2. In all cases, we deactivated "Mixture Spectra" to prevent individual MS/MS scans from being assigned to multiple proteoforms.
Deconvolution limited precursor charge to +30, using the default for this software. The pTop 2 software defaulted to 15 ppm fragment tolerance for fragments and a wide 5. 2 Da tolerance for precursor masses. Like MSPathFinderT, pTop required that protein N-terminal acetylation be configured as a dynamic modification; the software does not anticipate this modification automatically. We limited PTMs per PrSM to four and used the default FDR threshold of 1%, filtering all PrSMs for a set conjointly rather than per raw file. PrSM tables were imported from the pTop_filtered. csv report. The PXD019247 experiment produced an unusual error for pParseTD. The deconvolution engine recognized the dissociation type as ETD (the experiments were EThcD, but pParseTD 1. 2 does not support EThcD fragmentation), but the software misinterpreted the raw file to perceive the data as "ETDIT" (ion trap measurement) rather than "ETDFT" (Orbitrap measurement).
PTM Handling In addition to protein N-terminal acetylation and Met oxidation, the sets of dynamic modifications employed in searching each sample included the following: • PXD003074 SULIS: Lys + C 1 H 2 • PXD019247 ECOLI: (none) • PXD020342 DANRE: Cys + C 2 H 3 N 1 O 1 • PXD010825 PIG: (none) • PXD019368 HUMAN: (none) • MSV000082070 BOVIN: Ser + H 1 O 3 P 1 , Thr + H 1 O 3 P 1 , Tyr + H 1 O 3 P 1 • PXD031744 BOVIN: Ser + H 1 O 3 P 1 , Thr + H 1 O 3 P 1 , Tyr + H 1 O 3 P 1 • PXD005420 HUMAN: Ser + H 1 O 3 P 1 , Thr + H 1 O 3 P 1 , Tyr + H 1 O 3 P 1 For the final two sets, when ProSight PD was run with a UniProtKB XML rather than a FASTA, only Met oxidation was added; phosphorylations could only be considered if they were annotated in the UniProtKB XML.
Deconvolution Algorithms As shown in Figure  1 , each of the search engines comes prepackaged with its own deconvolution engine. It is not possible to mix-and-match most of these deconvolution and search tools. The output from pParseTD, for example, is not formatted as it would need to be for use in MSPathFinderT, TopPIC, or ProSight PD. Because TopPIC accepts deconvolved spectra in msAlign, a simple text format derived from Mascot Generic Format,  44  we sought to characterize the variability introduced by five deconvolution engines that could be exported to msAlign or MGF format (see Figure  2 ). We emphasize deconvolution in the context of Bruker maXis I and II data because Q-TOF instruments have not been as widely supported by software tools for top-down proteomics. The test of deconvolution impact encompassed three Bruker Q-TOF datasets (PXD010825-PIG, PXD019368-HUMAN, and MSV000082070-BOVIN), as well as one ThermoFisher Orbitrap data set (PXD019247-ECOLI).
Three deconvolution engines could be used on all sets (TopFD, FLASHDeconv, and Mascot Distiller), while two could be used only on data from a particular instrument vendor (ThermoFisher Xtract in ProSight PD or AutoMSn in Bruker DataAnalysis). TopFD and FLASHDeconv accepted data in peak-listed mzML format, writing their output to msAlign files; these could then be identified in the TopPIC identification engine. Mascot Distiller and ProSight PD started from raw mass spectrometry data, recording their outputs to Mascot Generic Format (MGF). The simple MGF2msAlign utility described below could then produce TopPIC-ready msAlign files. A Visual Basic Script for Bruker DataAnalysis (described below) performed feature detection from the raw Q-TOF data, deconvolved MS/MS.
Journal of Proteome Research peak lists, and exported msAlign files. In all cases, TopPIC 1. 4. 13 identified PrSMs from these msAlign deconvolved peak lists. All four sets of msAlign files for the two Bruker maXis II data sets have been posted to ProteomeXchange PXD033208 to accompany their raw data. FLASHDeconv. FLASHDeconv (2. 0 beta version)  45  was used to deconvolute all three Bruker datasets and the ThermoFisher PXD019247-ECOLI experiments. All raw files (". d" directories for Bruker and ". raw" files for ThermoFisher datasets) were centroided with MSConvert (version 3. 0. 20186), employing the vendor peakPicking filter, to produce input mzML files. For all datasets, the allowable charge range was configured to be 2-70, and mass range spanned from 50 to 60,000 Da. FLASHDeconv discarded MS2 spectra with precursors of high interference level (by applying min_pre-cursor_snr threshold of 1.
0). To maximize the signal-to-noise ratio of tandem mass spectra in all datasets, Gaussian weighted moving averaging was carried out using the SpectraMerger tool in OpenMS software. 46 Briefly, an MS/MS scan is collected with a precursor m/z value of x and inferred charge of c. The software computes the neutral mass of the precursor by subtracting a proton and multiplying by charge: c(x-1. 00727647). These neutral masses can then be compared among MS/MS scans to determine which have neutral masses within a precursor mass threshold (specified as 10 ppm for these experiments). Then the collected MS/MS scans are multiplied with Gaussian weights centered at the input MS/MS and summed to generate the output averaged MS/MS. Averaging is performed automatically within FLASHDeconv by setting the -merging_method option to 1.
The version of FLASHDeconv employed in the time trial was from a pre-release build of Open MS 3. 0, built on February 16, 2023. Mascot Distiller 2. 8. 0. 1. Mascot Distiller 47 was able to deconvolve tandem mass spectra from the Bruker Q-TOF datasets (PXD010825 PIG, PXD019368 HUMAN, and MSV000082070 BOVIN); its results on PXD019247 ECOLI, however, were of insufficient PrSM yield to be comparable to other deconvolution paths. The software operated on the Bruker ". d" directories containing "analysis. baf" files (made available at PXD033208). It was configured to allow a maximum charge of +40 (the highest value available for this software), with a default charge range of +10 to +20. Output was specified to be "fragment ions in MS/MS peak lists as MH+. " See configuration options in Supporting Figure  S1.
ThermoFisher Xtract in Proteome Discoverer 2. 5. To generate an msAlign that represents Xtract deconvolutions, we opened each pdResult file representing a completed ProSight PD run to export complete peaklists (not just the spectra that were successfully identified) to MGF format (the File → Export → Spectra menu item). The MGF2msAlign script described below then converted the MGF file to msAlign. The maximum charge configured by the "High/high cRAWler" was +80. Bruker DataAnalysis 5. 3 msAlign Exporter. ProteomeXchange PXD033208 holds the msAlign files exported by a Visual Basic Script in Bruker DataAnalysis. Scripts are available via the GitHub named at the top of the "Formatting and Exporting Tools" section below or via https://github. com/dtabb73/ Bruker-msAlign-exporter. Screenshots showing the configuration of the SNAP peakfinder and the AutoMSn compound detector appear in Supporting Figure  S2.
UniDec 6. 0. 0. b3. The UniDec MS1 deconvolution engine has gained popularity for native and denatured proteoform data in recent years. 48 It was included only in time trials because it does not currently support MS/MS deconvolution. Algorithm defaults were employed in a test script supplied by the Michael Marty, allowing a ceiling of +100 for ions in the MS scans. ThermoFisher Xtract in FreeStyle 1. 8 SP2. Starting with version 1. 8 of FreeStyle,  49  the "Xtract All" option can automatically deconvolve all MS and MS/MS scans in a raw file. It was included only in time trials because it did not support easy integration with the TopPIC search engine. The signal-tonoise requirement was reduced from a threshold of 3. 0 to 1. 0. The required number of detected charges was reduced to 1, and the charge range under consideration was set to +1 through +50.
Formatting and Exporting Tools This study could only be conducted by creating support tools for reformatting PrSM outputs, extracting subsections of databases, and adapting between spectrum formats. All these tools have been made available under a common URL: https://gitlab. pasteur. fr/MSBio/TDP_comparative_tools. ProForma Exporters. We created four software utilities in the C# language to export the following fields from each table of PrSMs: experiment filename, scan number, PrSM precursor charge, stripped UniProtKB accession, truncated sequence for PrSM without PTMs, integer sum of rounded PTM masses ("MassAdded)," ProForma v2 string representing sequence and PTMs,  42  and negative log E-Value for PrSM. These tools are available at the above GitLab hub or via https://github. com/ In order to characterize variation introduced by deconvolution, we generated output from five different deconvolution pathways for the same input data, directing these outputs to msAlign format for identification by TopPIC.
MSPathFinderT output was filtered in the utility to limit PrSMs to an E-value below 0. 01 and a reported probability above 0. 5. Of the four algorithms, only TopPIC routinely reported ambiguity of PTM localization and unknown mass shift modifications; the format converter forced placement of the PTM at only the most Cterminal position to make the output more comparable to the other search engines. The utility's "--suppress" option for TopPIC was used throughout to remove all PrSMs containing any unknown mass shift (resulting in a substantial sensitivity reduction for TopPIC: see Supporting Information Text S2). UniProt XML Subsetter. While many tools exist to choose a subset of FASTA sequences from a comprehensive proteome database, we needed to select a subset of entries from a UniProtKB XML.
We therefore developed a Python script in two different modes: (1) to extract XML sequences corresponding to those in a subset FASTA file or (2) to extract both XML sequences and FASTA sequences based on a provided list of UniProtKB accessions. MGF2msAlign. Since the MGF files from Xtract and Mascot Distiller contain singly charged monoisotopic masses for fragment ions, we created a script to convert these ion masses into uncharged monoisotopic masses by subtracting the mass of a proton from them. Normally, MGF files record precursor charge and monoisotopic precursor m/z values in the header for each MS/MS. Computing an uncharged intact mass for the proteoform (a necessary field in the msAlign format) required that we subtract the mass of a proton from the precursor m/z and then multiply the result by the precursor charge.
For example, determining that a particular MS/MS identified by TopPIC matches an identification from pTop requires that we can compare the raw file name and scan number attributed to those PrSMs, and each of those tool's records that information in a different format. The search engines also abbreviate UniProtKB accessions differently. The formats by which they communicate proteoforms (implying sequence truncations, the identities of PTMs, and their localizations) are inconsistent. Finally, MSPathFinderT in Informed Proteomics outputs all PrSMs to its output tables, so filtering criteria must be applied to those PrSMs before comparison to other search engines. We created ProForma Exporters in the C# programming language to output identification data from all four search engines in identical formats, using the ProForma v2 specification from HUPO-PSI to communicate proteoforms.
Most top-down identification algorithms were originally developed and tuned for handling ThermoFisher Orbitrapclass data. The data sets used here to evaluate these identification algorithms, include 6 ETD and 6 HCD LC-MS/ MS experiments for S. islandicus (PXD003074-SULIS), 6  EThcD experiments for E. coli (PXD019247-ECOLI), and the 18 HCD runs for D. rerio (PXD020342-DANRE) (see Table  1 ). The D. rerio set differed from the S. islandicus and E. coli sets in more ways than just the complexity of its genome. It was the only experiment that employed iodoacetamide to alkylate Cys Journal of Proteome Research residues, it was the only one to employ CE rather than LC upstream of the instrument, and it was generated by a ThermoFisher Q-Exactive HF while the other two were produced in either an Orbitrap Fusion (PXD003074-SULIS) or an Orbitrap Fusion Lumos (PXD019247-ECOLI).
Estimated Yield All search configurations, original search outputs, and filtered ProForma outputs can be downloaded as Supporting Information File S1. In each of the four test sets shown in Figure  3 , either MSPathFinderT or pTop yields the highest number of confident PrSMs. In PXD020342-DANRE, the difference between the highest yield and lowest yield is considerably smaller. The first three tests all employed a sequence database spanning the complete reference proteomes in FASTA format for both ECOLI and SULIS, but only the SULIS tests incorporated methylation of Lys as a PTM. TopPIC and MSPathFinderT both automatically processed the ECOLI EThcD data as if they were produced via ETD rather than EThcD (considering only c-z fragments rather than a mix of c-z and b-y fragments). In pTop2, both ETD and EThcD modes were tested with the ECOLI set, and ETD mode produced the larger yield.
FDR Estimation For S. islandicus and E. coli experiments, we used a single FASTA database that contained all 2591 proteins from the SULIS reference proteome (UP000013006) and all 4450 proteins from the ECOLI reference proteome (UP000000625). Any match to an E. coli protein in S. islandicus experiments would be Figure  3. In panels A-C, each color signifies the identifications yielded from one of six different raw files. ProSight PD has been abbreviated "PSPD," while MSPathFinderT (part of the Informed Proteomics suite) has been abbreviated "MSPT. " In PXD020342-DANRE, the triplicates for each fraction of each sex were combined to a single color (18 raws become six samples). The ability to produce many PrSMs for a given raw file varies due to many factors, particularly in how one threshold "good" from "bad" identifications.