GlycoBinder

Introduction

This document describes the use of the R script GlycoBinder and its key elements. GlycoBinder allows streamlined data processing of multiplexed glycopeptide quantitative mass spectrometry data. It relies on usage of external tools (s. below) that are not distributed with the script and have to be requested and installed separately. GlycoBinder is a free software and distributed under GNU GPL v3.0 license (for details see the GNU General Public License [https://www.gnu.org/licenses/]). This license does not apply to external software GlycoBinder relies on. For this, different license terms may apply.

Programming Language

GlycoBinder is written using R programming language [https://www.r-project.org/], version 3.5.0. It also relies on freely available R-packages: data.table [https://github.com/Rdatatable/data.table], dplyr [https://github.com/tidyverse/dplyr], future.apply [https://github.com/HenrikBengtsson/future.apply], and stringr [https://github.com/tidyverse/stringr].

External tools

GlycoBinder combines the following external tools for processing mass spectrometry data:

1. RawTools, version 2.0.3 [https://github.com/kevinkovalchik/RawTools]

Kovalchik, K.A., Colborne, S., Spencer, S.E., Sorensen, P.H., Chen, D.D., Morin, G.B. and Hughes, C.S., 2018. RawTools: Rapid and Dynamic Interrogation of Orbitrap Data Files for Mass Spectrometer System Management. Journal of proteome research, 18(2), pp.700-708.

2. msconvert (ProteoWizard), version 3.0.19363 (3a06b8cdd) [https://github.com/ProteoWizard/pwiz]

Chambers, M.C., Maclean, B., Burke, R., Amodei, D., Ruderman, D.L., Neumann, S., Gatto, L., Fischer, B., Pratt, B., Egertson, J. and Hoff, K., 2012. A cross-platform toolkit for mass spectrometry and proteomics. Nature biotechnology, 30(10), p.918.

3. pGlyco, version 2.2.2 [http://pfind.net/software/pGlyco/index.html] (comes together with pParse, version 2.2.1 )

Liu, M.Q., Zeng, W.F., Fang, P., Cao, W.Q., Liu, C., Yan, G.Q., Zhang, Y., Peng, C., Wu, J.Q., Zhang, X.J. and Tu, H.J., 2017. pGlyco 2.0 enables precision N-glycoproteomics with comprehensive quality control and one-step mass spectrometry for intact glycopeptide identification. Nature communications, 8(1), p.438.

4. pParse, version 2.2.1 [http://pfind.net/software/pParse/index.html], comes together with pGlyco (no need to install/configure).

Yuan, Z.F.E., Liu, C., Wang, H.P., Sun, R.X., Fu, Y., Zhang, J.F., Wang, L.H., Chi, H., Li, Y., Xiu, L.Y. and Wang, W.P., 2012. pParse: A method for accurate determination of monoisotopic peaks in high‐resolution mass spectra. Proteomics, 12(2), pp.226-235.

GlycoBinder does not provide those tools and a user needs to request and install the tools by himself prior to working with GlycoBinder. To our knowledge, the tools are freely available upon request.

Setting up the processing environment

GlycoBinder was developed and tested on machines running on 64-bit platforms under Windows 10 and R programming language versions 3.5.0 or higher. It requires an R programming language (versions 3.5.0 or above) to be installed on your machine including data.table, dplyr, future.apply, and stringr packages. In case those packages are not installed, GlycoBinder will make an attempt to install them. Note the location of "Rscript.exe" file which is needed to run R scripts in command line (commonly in C:/Program Files/R/R-3.5.0/bin/x64/)

External tools should be installed and configured prior to using the script. External tools have to be added to the system path of the machine. Later allows calling the tool without specifying an exact path to it. To do so, open windows menu and search for Edit environment variables for your account and then click on it. Under "User Variables" select "PATH" and click the Edit button (make sure you are changing the "PATH" variable for your user account). Select New and then Browse. Navigate to the directory where the executable of the tool is located (e.g. C:\Program Files\RawTools-2.0.3\). Repeat the same procedure for all tools. We also suggest to add the file path to the folder containing "Rscript.exe" file. After the environmental variables are configured, please check if the tools can be accessed from the command line directly. For this, open the command line and type one by one: RScript, rawtools, msconvert, pparse, pglyco. Hit Enter after each command. Make sure that system can find each tool and returns help information to the console. A tutorial how to configure environmental variables can be found here: https://github.com/kevinkovalchik/RawTools/wiki/Download-and-prepare-RawTools-for-Windows

Depending on the number of raw files and their size, GlycoBinder might require a large amount of RAM to process the data. Per default, it will use number_of_available_processors - 2 threads on your machine for processing the data (this number might be different for external tools). We recommend to reserve at least 1GB of free RAM per running process (e.g. for a machine with 8 cores, one should aim for at least 6 GB of free RAM space). If you would like to restrict the number of processors used by GlycoBinder, please, consult the following section regarding additional parameters to the script.

Processing steps in brief

GlycoBinder is designed for processing .raw files acquired on Thermo Fisher Orbitrap instruments. It combines MS2 scans with their dependent MS3 scans. It also extracts reporter ion intensities for subsequent quantification.

In brief, GlycoBinder makes following steps in the data processing:

1. RawTools extracts quantitative information (reporter ion intensities) from Thermo .raw files and assigns MS3 scan to corresponding MS2 scans.

2. msconvert transforms .raw files into .mgf file format and centroids data by applying a vendor-specific peak picking algorithm. MS2 and MS3 scans are preserved in the .mgf file.

3. pParse recalibrates the monoisotopic peaks of precursors and outputs an .mgf file containing MS2 scans.

4. GlycoBinder combines ion intensities of matching MS2 and MS3 spectra as reported by RawTools. MS2 and MS3 spectra are extracted from msconvert-produced .mgf file and merged based on the specified ion tolerance window. GlycoBinder replaces MS2 spectra in the pParse output by combined MS2/MS3 spectra. Modified pParse output file is used as an input for pGlyco 2.0.

5. pGlyco 2.0 uses the combined spectra to search for peptides and associated glycans. After the first pGlyco 2.0-search is finished, results are filtered based on a specified FDR cutoff.

6. Optionally, a second pGlyco 2.0-search is performed on a smaller protein data base. For this, only glycoproteins identified in the first round of pGlyco 2.0-search and passing an FDR threshold are retained in the protein sequence database and used for the second round of glycopeptide search. Please, consult the section about additional parameters to GlycoBinder in order to disable the second pGlyco 2.0 search.

7. GlycoBinder combines pGlyco 2.0 search results and reporter ion intensities extracted by RawTools. Based on the combined pGlyco 2.0 and RawTools output, GlycoBinder organizes quantitative results at different levels: at the levels of glycosylated peptides, glycoforms, glycosites, and glycans. A separate data table is reported for each level that contains unique identifier of the data entry, cross-references to other levels, quantification information in the form of the summed reporter ion intensities and necessary metadata. By re-organizing the combined pGlyco 2.0 and RawTools output, Glycobinder allows to directly address changes happening at the level of glycopeptides, glycoforms, glycosites or glycans since the quantitative information is conveniently structured at each level.

Using GlycoBinder

The easiest way to execute GlycoBinder is to follow the steps:

1. Prepare a working directory containing .raw files to be processed, .fasta file containing amino acid sequences of proteins, and "Glycobinder.R" file
2. Open the command line and set the working directory to the working directory organized above using cd command
3. Specify the path to the Rscript.exe (or just "Rscript.exe" if the file path is set in environmental variables)
4. Specify the path to the GlycoBinder.R file (simply "GlycoBinder.R" if the file is located in the same directory)
5. Specify peptide labeling reagent after --reporter_ion (values supported by RawTools are allowed: TMT0, TMT2, TMT6, TMT10, TMT11, TMT16, iTRAQ4, iTRAQ8, not_labeled), e.g. --reporter_ion TMT6
6. Specify additional arguments (s. below)

Suppose, .raw files, the .fasta file, and GlycoBinder.R script are located in C:/data folder, and peptides were labeled using TMT6plex reagents, the minimum required input would look like:

C:/data>Rscript.exe "GlycoBinder.R" --reporter_ion TMT6 

Additional parameters

Following parameters modify default GlycoBinder behavior if added as command line arguments:

1. --verbose
   Force GlycoBinder to be more chatty.

2. --wd
   Specify a different working directory (should contain .raw and .fasta files)

3. --tol_unit
   Specify tolerance unit used for matching ions from corresponding MS2 and MS3 spectra. Supported values are ppm and Th, e.g. --tol_unit ppm (default).

4. --match_tol
   Specify tolerance for matching ions from corresponding MS2 and MS3 spectra. Integer numbers are supported, e.g. --match_tol 1 (default). Default tolerance widow for ion matching is 1 ppm. It means, if two ions in the matching spectra have an absolute mass difference smaller than 1 ppm, those peptides will be considered the same and their intensities will be summed.

5. --pglyco_fdr_threshold
   Specify total FDR cutoff for pGlyco 2.0 search results, e.g. --pglyco_fdr_threshold 0.02 (default) sets maximum total FDR to 2%.

6. --no_second_search
   Prevent GlycoBinder from running second pGlyco 2.0 search on reduced data base.

7. --report_intermediate_results
   Forces GlycoBinder to keep intermediate files generated by external tools.

8. --nr_threads
   Specify number of available processors for GlycoBinder processing. It can take values between 1 and the number of available processors - 2 (default).

9. --seq_wind_size
   The parameter specifies the number of amino acids around the modification site. It is applied to extract sequence window around modification site from protein sequences. Sequence windows are needed to combine quantitative information on glycoform level. Default paramter is 7, e.g. --seq_wind_size 7. Seven amino acid before the modified site and seven amino acids after the modified site will be extracted, resulting in the 15 amino acids long sequence window.

10. --skip_marker_ions
    GlycoBinder will not look for oxonium/marker ions in the scans.

11. --parent_area_fun
    Function which will be used to combine parent peak areas. Available options: sum, mean, median, max, and min. sum is used per default.

Default parameters for external tools

Per default, external tools are started using parameters listed below. The majority of these parameters are fixed. However, one can execute those tools outside of GlycoBinder using a different parameter set and then supply the output files into the respective folder within the GlycoBinder working directory (specified after --wd flag while running the script). In this case, GlycoBinder skips execution of a respective tool.

1. RawTools
   rawtools -parse -d [input directory] -out [output directory] -q -r [reporter ions type] -R -u
   RawTools output one _Matrix.txt file per .raw file. Output file names are created by appending _Matrix.txt to the .raw file name including extension (example: "raw_file.raw" becomes "raw_file.raw_Matrix.txt"). RawTools output files are located in ./rawtools_output folder within the specified working directory. One can process raw files externally and then copy the resulting _Matrix.txt files into the ./rawtools_output folder. If every .raw file has a corresponding _Matrix.txt file, GlycoBinder will skip RawTools processing.

2. msconvert
   msconvert [file] --outdir [output directory] --mgf --ignoreUnknownInstrumentError --singleThreaded --filter "peakPicking vendor" --filter "defaultArrayLength 1-" --filter "titleMaker <RunId>.<ScanNumber>.<ScanNumber>.<ChargeState>"
   Output file names are equal to the input file name with .raw extension substituted by .mgf. msconvert output files are located in ./msconvert_ouput folder within GlycoBinder working directory. If GlycoBinder can locate all .mgf files in the ./msconvert_output folder, the msconvert processing step is skipped. For correct processing of .mgf files generated by msconvert, each scan within an .mgf file should contain a line starting with "TITLE=" and containing a scan number flanked by dots, e.g. ".355.".

3. pParse
   pParse.exe -D [file] -O [output directory] -p, 0
   pParse output files are located in ./pparse_output folder and named as original .raw files with .raw file extension substituted by _[Type of Detector, e.g. CDFT or ITFT].mgf. Similarly, GlycoBinder processing is skipped if all output files are found within the ./pparse_output folder. After merging of MS2 and MS3 spectra, MS2 spectra within pParse output files are substituted by the combined MS2/MS3 spectra. The modified pParse output files are renamed to [base_raw_file_name]_pParse_mod.mgf files and saved in the same ./pparse_output folder. If all _pParse_mod.mgf are found in the ./pparse_output folder, pParse processing and merging of the MS2 and MS3 spectra are skipped.

4. pGlyco 2.0
   pGlycodb.exe [pglyco configuration file] && pGlycoFDR.exe -p [pglyco configuration file] -r [output file name] && pGlycoProInfer.exe

pGlyco 2.0 workflow consist of three programs, pGlycodb.exe, pGlycoFDR.exe, and pGlycoProInfer.exe that are executed one after another and rely upon configuration file that should be created before run. If GlycoBinder does not find any file with a name pGlyco_task.pglyco in the working directory, it will create a configuration file with default parameters. One can create its own configuration file, e.g. using GUI of pGlyco 2.0, name it as pGlyco_task.pglyco and then copy it to the working directory of pGlyco 2.0. In this case, pGlyco 2.0 will utilize the existing parameter file for glycopeptide search. Following parameters are used per default and can be changed when supplying a GUI-created pGlyco_task.pglyco file to the GlycoBinder working directory:

• enzyme=Trypsin_KR-C
• max_miss_cleave=2
• max_peptide_len=40
• min_peptide_len=6
• max_peptide_weight=4000
• min_peptide_weight=600
• [modification]
fix_total=3
fix1=Carbamidomethyl[C]
fix2=TMT6plex[K]
fix3=TMT6plex[AnyN-term]
max_var_modify_num=3
var_total=1
var1=Oxidation[M]
• [search]
search_precursor_tolerance=10
search_precursor_tolerance_type=ppm
search_fragment_tolerance=20
search_fragment_tolerance_type=ppm

Other parameters are fixed or will be overwritten irrespectively of the origin of the configuration file. Furthermore, same parameter file will be applied in the second pGlyco 2.0 search, with exception that the protein database file will be changed to the reduced version of the .fasta file. The output file is pGlycoDB-GP-FDR-Pro.txt for the first pGlyco 2.0 search and pGlycoDB-GP-FDR-Pro2.txt for the second search, respectively. Both files are located in the ./pglyco_output folder. If the file pGlycoDB-GP-FDR-Pro.txt exists (or pGlycoDB-GP-FDR-Pro2.txt exists and --no_second_search flag was not used), GlycoBinder will skip the first (or first and second) pGlyco 2.0 search, respectively.

Special case: MS2 data

After processing with RawTools, files that were identified as not containing MS3 scans will not be subjected to msconvert processing. The MS2/MS3 spectra merging step is skipped as well. After pParse processing, original pParse output files are renamed to _pParse_mod.mgf files for consistency and used as input for pGlyco directly.

Merging of MS2/MS3 spectra

GlycoBinder combines MS2 and MS3 spectra based on MS2 and MS3 spectra scan number pairs in the RawTools output files (MS2ScanNumber and MS3ScanNumber columns within _Matrix.txt file). First, ions from MS2/MS3 scan pairs are roughly matched using 1 Th tolerance window. Initially matching ions are then tested to satisfy the specified tolerance window (1 ppm per default, it can be changed by specifying --tol_unit and --match_tol arguments). If several ions matches the same ion, the ions with the minimal absolute mass difference are considered as the matching ion pair. Intensities of matched ions are summed. Remaining MS3 ions that do not have matching MS2 ions are simply added to the MS2 spectra. pParse .mgf file will then output merged MS2/MS3 spectra. GlycoBinder matches spectra in the pParse output file to the merged MS2/MS3 spectra based on the scan number. While scan number is unique for merged MS2/MS3 spectra, several spectra in the pParse output can refer to the same scan number. For all of them, the spectrum will be substituted by the respective merged MS2/MS3 spectrum. Spectra that do no share scan number with merged MS2/MS3 spectra will be kept unchanged.

Identifyig oxonium/marker ions

Per deafault (unless --skip_marker_ions was specified), GlycoBinder will look for presence of pre-defined marker ions in the MS2 spectra. The intensities of the identified marker ions is reported as a sum of corresponding marker ion intensities.
Marker ions that should be looked for can be specified specified in a "marker_ions.txt" file and placed in the root folder. If no such file exists, GlycoBinder will generate a default one, which can be used as a template later.

GlycoBinder output

As a last step in the data processing, GlycoBinder combines peptide information identified by pGlyco 2.0 and reporter ion quantities extracted by RawTools. It combines intensity information at different levels by summing the respective ion intensities. All GlycoBinder output files are located in the ./pglyco_output folder within the GlycoBinder working directory.

1. pglyco_quant_results.txt
   The table represents a combination of pGlyco 2.0 output (pGlycoDB-GP-FDR-Pro.txt or pGlycoDB-GP-FDR-Pro2.txt) and RawTools output files (_Matrix.txt files). Quantitative information from RawTools output is merged with pGlyco 2.0 output file based on the .raw file name and MS2 scan number. Each row represents an identified spectrum (by pGlyco 2.0) with extracted reporter ion intensities (by RawTools). Column names from pGlyco 2.0 and RawTools are preserved and their descriptions can be found in the documentation for pGlyco 2.0 and RawTools.

2. pGlyco_Scans.txt
   Same pglyco_quant_results.txt file filtered based on the total FDR cutoff (lesser than 2% FDR per default, can be changed when specifying --pglyco_fdr_threshold parameter).

3. pGlyco_modified_peptides.txt
   The table is based on pGlyco_Scans.txt.Each row contains information about a modified peptide (glycopeptide) – a peptide with a specific glycan composition. Scans belonging to the same modified peptide are combined and their reporter ion intensities are summed. Additional variable modification of the peptide are not taken into account. Accordingly, reporter ion intensities are combined if the glycopeptide is identified in different .raw files. Glycopeptides carrying a missed cleavage site are considered as individual glycopeptides and not merged with their fully cleaved counter-parts. While combining information from different scans, precursor information is concatenated using default pGlyco 2.0 separator ("/") and is preserved within the columns pGlyco_ids, RawName, Scan, PrecursorMZ, Charge, Mod, ParentPeakArea. pGlyco_ids column refers to id column in the pGlyco_Scans.txt table and can be used to identify original scans contributed to a particular glycopeptide. Columns such as Peptide, GlySite, Glycan(H,N,A,G,F), GlyID, PlausibleStruct, GlyFrag, GlyMass, Proteins, ProSite, keep the information about the glycan structure and possible protein assignment. Leading_Protein and Leading_ProSite columns report the selected protein and corresponding site based on criteria discussed below.

4. pGlyco_glycoforms.txt
   The table is based on pGlyco_modified_peptides.txt. Each row contains information about a glycoform – a glycan attached to a particular site on the protein sequence. Amino acids surrounding the glycosylated site form a sequence window. Sequence window in combination with glycan composition is used to distinguish different glycoforms. Sequence windows are first extracted from the amino acid sequences of corresponding proteins. Per default, +/-7 amino acids are extracted around the modification site (can be changed if specifying --seq_wind_size parameter). Glycopeptides that share the same modification site are grouped together and form a peptide group.Sequence windows are extracted from proteins that contain those peptides and ranked based on the number of peptides each sequence window can explain. Ties are broken by protein ranking (see description below). Peptides shared among several sequence windows are assigned to the sequence window that encompasses the majority of the peptides within the peptide group. If there are peptides that cannot be explained by the leading sequence window, those peptides are distributed between other sequence windows accordingly. Intensity information is then combined based on sequence window and glycan structure (reported in seq_win and Glycan(H,N,A,G,F) columns, respectively). Columns modpept_ids, Scan, pGlyco_ids, Peptide, GlySite, GlyID concatenatinate information from respective columns in the pGlyco_modified_peptides.txt table. ";" is used as a separator by concatenation. modpept_ids refers to the id column in the pGlyco_modified_peptides.txt table. It contains the ids of glycopeptides that contributed to a particular glycoform.

5. pGlyco_glycosites.txt
   The table is based on pGlyco_modified_peptides.txt table. Each row contains information about a glycosite – a glycosylated site on a protein sequence irrespective of particular glycan structure. Since there might be certain ambiguity in assignment of peptides to proteins, sequence windows are used to define the glycosite in practice. Accordingly, the table contains seq_win column with sequence window information, modpept_id column that refers to id column in the pGlyco_modified_peptides.txt. Columns Scan, pGlyco_ids, Peptide, GlySite, GlyID, Glycan(H,N,A,G,F), GlyMass are concatenaions of respective columns in pGlyco_modified_peptides.txt using ";" as a separator. Leading_Protein and Leading_ProSite are selected according to protein rank. Proteins are ranked based on the number of unique peptides (highest priority), number of all peptides, number of glycoforms assigned to the protein, whether it is a Swiss-Prot entry, and whether it is a canonical sequence or is an isoform (lowest priority). Proteins that have greater number of unique peptides/total peptides/glycoforms, annotated in Swiss-Prot data base and represent a canonical sequence, receive a higher rank. The highest rank is 1. The rank is unique and ties, if occur, are broken by alphabetic order.

6. pGlyco_glycans.txt
   The table is based on pGlyco_modified_peptides.txt table. Each row contains information about a unique glycan composition identified in the data set. The information about the peptide sequence is not taken into account. The information is combined based on glycan composition only (Glycan(H,N,A,G,F) column). modpept_id column refers to id column in the pGlyco_modified_peptides.txt. Columns pGlyco_ids, Scan, Leading_Protein, Leading_ProSite are concatenations of respective columns in pGlyco_modified_peptides.txt using ";" as a separator.

7. marker_ions_identified.txt
   The table contains intensities of all identified marker ions per scan/raw file.

8. pGlyco_glycotope.txt summarizes the intensities for each non-conflicting glycotope (s. description below).

Defining Glycan Type/Glycan antenna types

GlycoBinder reports putative glycan type / glycan antenna type in GlycanType and GlycanAntennaType, respectively.
The types are deduced based on the glycan composition reported in Glycan(H,N,A,G,F) by pGlyco. Following glycan type//antenna types were defined:
Paucimannose//Paucimannose: HexNAc(2)Hex(1-4)NeuAc(0)Fuc(x);
High-mannose//High-mannose: HexNAc(2)Hex(5-9)NeuAc(0)Fuc(0);
Initiation//Initiation: HexNAc(2)Hex(10-12)NeuAc(0)Fuc(0);
(Hybrid/A1)//(Hybrid/A1): HexNAc(3)Hex(>=3)NeuAc(x)Fuc(x);
Complex//(A2/A1B): HexNAc(4)Hex(>=3)NeuAc(x)Fuc(x);
Complex//(A3/A2B): HexNAc(5)Hex(>=3)NeuAc(x)Fuc(x);
Complex//(A4/A3B): HexNAc(>=6)Hex(>=3)NeuAc(x)Fuc(x),
where x is any amount; HexNAc = N, Hex = H, NeuAc = A, Fuc = F.
Other compositions are marked as Other.

Determining core fucosylation

Output tables pGlyco_glycoforms.txt, pGlyco_glycosites.txt, and pGlyco_glycans.txt contain following columns that help to assess whether the glycan is of a core fucose composition:

1. CoreFuc corresponds to CoreFuc output of pGlyco. Values (0, 10, 11, 12) for each scan are separated by ";". Refer to a pGlyco manual for a detailed description of values.
2. FucoseStruct contains TRUE if the anticipated structure determined by pGlyco contains a fucose (F). FALSE otherwise.
3. CoreFucoseOnly "Yes" if all corresponding scans are of "11" or "12" CoreFuc type. "No" if all scans are of "0" type. "Ambiguous" in other cases.

Determining glycotope

Based on the presence of the specific marker ions, Glycobinder will also attempt to determine one of the "basic" glycotopes: HN(F), AHN, HN(A), H(F)N(F), AHN(F), AHN(A), AAHN, AAHN(A), AAAHN, AHNorHN(A), AHN(A)orAAHN, AAAHNorAAHN(A). Potential conflicts with glycan composition reported by pGlyco are marked as "+".

Parent peak area

Corresponding parent peak areas are reported as ParentPeakArea column in the output tables.
Function that is used for the parent peak area aggregation can be specified via --parent_area_fun parameter.
Per default, ParentPeakArea is the sum of the corresponding parent peak areas. Relative parent peak area is reported based on the relative intensities of the reporter ions.
The total reporter ion intensity is reported in the TotalRepIonIntensity column.
Relative reporter ion intensities are reported as percentages in {ReporterIon}IntensityPercent columns, e.g., 126IntensityPercent for a TMT-126 reporter ion. Relative parent peak area is then calculated as 0.01*{ReporterIon}IntensityPercent*ParentPeakArea and reported as {ReporterIon}IntensityParentPeakArea.

Special case: use of another search engine

Currently, pGlyco 2.0 is the only search engine supported by the GlycoBinder workflow. However, GlycoBinder reports merged MS2/MS3 spectra in mgf format that are located in ./pparse_output folder and marked with the _mod.mgf suffix. These mgf files can be used with any other search engine compatible with the mgf format. The search engine output then has to be integrated with the quantitative data from RawTools output (_Matrix.txt files in ./rawtools_output folder). Scan numbers and raw file names can be used to integrate qualitative and quantitative information, respectively.

Demonstration data set

As a test data set, we provide an IgM_TMT0.raw file. It is a tryptic digest of a purified IgM sample labeled with TMT0 reagent. The file is located in the demo/ folder together with a Human_IgM.FASTA file containing amino acid sequences of the two human proteins, IgM and IgJ, respecitvely. To test the performance of the GlycoBinder, download the contents of the demo/ folder (e.g. into C:/data/Glycobinder/demo), copy the current version of GlycoBinder into it and execute in the command line using following parameters:

C:/data/Glycobinder/demo>Rscript.exe "GlycoBinder.R" --wd "C:/data/Glycobinder/demo" --reporter_ion TMT0 --no_second_search

If you download files from GitHub using git bash, please first install git lfs (https://git-lfs.github.com/) that is aimed at handling large files (e.g. the example raw file). If you use web interface for downloading (“download ZIP”), you will download a placeholder for IgM_TMT0.raw file. To download the actual file, find it in the GitHub repository and click on “View raw”. Save the file in your local demo/ folder.
The execution takes around 5 min on a desktop computer running Windows 10 and equipped with Intel Core i7-6700 CPU (64 bit) and 32 Gb of RAM. Beware that the execution time will scale up with the complexity of the data set provided.
GlycoBinder output is located within pglyco_output folder. There are 67 glycoforms (pGlyco_glycoforms.txt), 45 unique glycan compositions (pGlyco_glycans.txt) and 4 glycosylation sites (pGlyco_glycosites.txt) identified in the data.

Potential Problems / Special use cases

1. GlycoBinder does not find one of the external tools or cannot execute it
   Check that the tool is accessible through the command line. If not, check if the path to the tool is saved in the system paths (s. Requirements for the processing environment section). Try to process the files using command line and same arguments as described for that tool. If correct output is created, copy it to a respective output folder within the GlycoBinder working directory. Re-run GlycoBinder. It should skip the problematic step and continue with the next one. If the tool does not return a correct output, consult the help page of the tool.

2. GlycoBinder is suspended in one of the steps and does not continue with other steps
   First, make sure that you gave GlycoBinder enough time to finish the task. Check, if external tools have created a proper output. If the output is created, stop GlycoBinder by closing the command line window and try to restart it. If the output is not complete, try to use the the tool outside of GlycoBinder, as described in the point 1.

3. GlycoBinder cannot find working directory
   Check that the file path specified after --wd argument does not contain white spaces or properly enquoted. Same applies when specifying the location of the script itself.

4. GlycoBinder cannot find .raw files
   Make sure that .raw files are located in the specified working directory and have .raw extension.

5. Minimal requirements to run GlycoBinder are:

• Installed and properly configured environment (R and respective packages, external tools, configured file paths)
• Working directory containing .raw files and a .fasta file. The path to the directory is specified after --wd flag in the command line
• Specifying which labeling reagent was used for quantification by using --reporter_ion.

6. Use of external tools with different parameters
   Output of all external tools can be created outside of GlycoBinder workflow and then copied into respective output folder within the GlycoBinder working directory. In this case, GlycoBinder will skip the respective processing step if it can find respective files.
   For pGlyco 2.0 there is an option to pre-configure a parameter file by using pGlyco 2.0 GUI and save the file in the GlycoBinder working directory under the name "pGlyco_task.pglyco". GlycoBinder will utilize it instead of default settings.