QuiC 2.1 (Senna) User Manual

QuiC 2.1 (Senna) User Manual

1 Contents 2 General Information... 3 2.1 Computer System Requirements... 3 2.2 Scope of QuiC Software... 4 2.2.1 QuiC Licensing... 5 2.3 QuiC Release Features... 5 2.3.1 QuiC 2 (Senna)... 5 2.4 Supported Data Acquisition Methods... 5 3 Getting Started... 6 3.1 Getting QuiC... 6 3.2 QuiC Activation... 6 3.3 Calibration Kit... 6 3.4 Settings... 6 3.4.1 QC... 7 3.4.2 Global... 8 3.4.3 Event Tags... 11 4 QuiC Usage... 13 4.1 Monitor Perspective... 13 4.2 QC Perspective... 14 4.2.1 History... 14 4.2.2 Mass Spectrometer... 16 4.2.3 irt Peptides... 16 4.2.4 General... 17 4.2.5 Discovery... 18 4.2.6 DDA Advanced... 19 4.2.7 Plots... 20 5 References... 20 Page 2 of 20

2 General Information 2.1 Computer System Requirements Minimal Operating System: CPU: Hard drive: Memory: Software: Windows 7, x64 Intel Core CPU, 2.7 GHz (quad-core) or similar 200 GB free space 8 GB.NET 4.6.1 or higher Recommended Operating System: CPU: Hard drive: Memory: Software: Windows 7 or higher, x64 Intel Core i7 4770, 3.4 GHz (octa-core) or similar 500 GB free space, solid state drive (SSD) 16 GB or more.net 4.6.1 or higher Page 3 of 20

2.2 Scope of QuiC Software QuiC is a software tool for quality control (QC) analysis and visualization of mass spectrometry-based proteomics data. QuiC is especially useful for unifying performance tracking of multiple instruments in a proteomics lab. It supports the analysis of DDA, DIA, MRM and PRM runs from different vendors (to date, ThermoFisher and Sciex). QuiC can help you spot a decline in instrument performance as illustrated in two realworld cases studies depicted in Figures 1 and 2. In the first case, we noted a decrease in mass accuracy over time which was remedied by a recalibration. In the other case, our decrease in identifications was linked to a decrease in peak capacity, ultimately caused by a pump leak. QuiC plots facilitated an early detection of the problems and an accurate insight into their causes. Figure 1. QuiC can detect a drift in your instrument s MS1 and MS2 mass accuracy. Page 4 of 20

Figure 2. On the left, a drop in peptide identifications over time, followed by a restoration to normal that correlates with the peak capacity performance on the right. The drop in peak capacity was attributed to a failing pump. The blue dot indicates the point at which we replaced the pump, returning peak capacity to normal levels. 2.2.1 QuiC Licensing QuiC is free of charge. A free annual license can be requested at info@biognosys.com. QuiC requires the irt Kit or the HRM Calibration Kit to be spiked into each sample. 2.3 QuiC Release Features 2.3.1 QuiC 2 (Senna) QC run analysis pipelines Support for MRM, PRM, DIA and DDA Support for Thermo Fisher and Sciex Automated folder monitoring Various LC and MS proteomics QC readouts based on the irt peptides Support for additional background peptides Event tag handling New plotting framework Peak capacity and MS1/MS2 median intensity plots Export QC report to PDF feature Custom plot sorting 2.4 Supported Data Acquisition Methods QuiC analyzes a large variety of different QC data formats from DDA, DIA, MRM and PRM. Minimal requirements are a reversed phase chromatography with a linear or nonlinear gradient. All samples need to contain the irt calibration mix to perform quality control analysis with QuiC. In case you experience technical problems with the software or if you have feature suggestions please contact support@biognosys.com. Page 5 of 20

3 Getting Started 3.1 Getting QuiC Free licenses for QuiC software are available for all users. The software package can be downloaded at www.biognosys.com/shop. After successful registration you will receive a download link together with a license key to activate your software. 3.2 QuiC Activation When you start QuiC for the first time, you will be asked to activate your software. You should have received a license key with the download link for QuiC. If you do not have a license key yet, you can obtain one by registering yourself at www.biognosys.com/shop. If your computer has access to the internet, activation will be automatic once you have pasted your license key into the QuiC activation dialogue. In case your QuiC computer does not have an internet connection or the connection is blocked by a firewall, you can also activate your software using email. The respective instructions will appear after a few seconds if online activation was not successful. Save the registration information file on your computer and send this file to support@biognosys.com. You will receive a license file usually within one working day. To activate QuiC using a license file, click on the Browse License File button in the QuiC Activation dialogue. 3.3 Calibration Kit To enable fully automated and sensitive QC with QuiC, we developed the calibration kit (irt kit) that is spiked into each sample before the measurement. The calibration kit contains a mix of non-naturally occurring synthetic peptides. For DDA and DIA a prespecified discovery library is additionally targeted for QC analysis. The default background library bundled with QuiC contains Human (HeLa) peptides. 3.4 Settings It is recommended to pre-configure QuiC after the first start to enable optimal performance. Note: if you ve migrated from version 1.0 to 2.1, you will also need to readjust your settings. Page 6 of 20

3.4.1 QC Figure 3. Analysis schemas can be created to be used and re-used in your analysis pipelines. In the QC page of the Settings perspective, you can define analysis schemas that contain the parameters that will be passed to the QC analysis pipeline. These settings can be saved to be re-used across multiple analyses. You can create as many schemas as you want as well as import/export them. There are two categories pertaining to your schema: Analysis and Batch Processing. Analysis settings affect the results of an analysis of a single run, while batch processing settings control things like what files in a folder should be considered for analysis. The criteria currently available for your schemas are as follows. 3.4.1.1 Batch Processing Age Filter (Days) Only raw files that have been acquired within the specified number of days will be considered. If all are to be considered, this field should be set to -1. Include Subfolder The batch analysis will recursively walk the entire subdirectory hierarchy of the selected folder and add any runs in the hierarchy. Monitor Folder This places a monitor on the folder. Whenever a new run is added to a monitored folder, it will automatically be added to the task queue for processing. Page 7 of 20

Future Runs Only If Monitor Folder is selected, you have the option to analyse all runs retrospectively or analyse future runs only. With this option selected, only runs that have been acquired after the monitor was set up will be analysed. Regex File Filter This allows you to specify a regular expression pattern to consider only files whose names match the pattern to be analyzed. More information regarding regular expressions and their syntax can be found here. Vendor Filter Only runs associated with a particular vendor will be considered. 3.4.1.2 Analysis Background Path For DDA and DIA analyses, the runs are targeted using a predefined spectral library. This is used to generate richer statistics in the Mass Spectrometer and Discovery sections of the QC perspective. By default, this library is a standard HeLa library that is bundled with the software. Currently, we only accept libraries that are in the Biognosys.kit format. Contact us at support@biognosys.com if you would like more information about generating your own kits. 3.4.2 Global Figure 4. The Global page of the Settings perspective allows you to specify options that will apply universally to all QC analyses. Things like analysis task auto-deletion, notification options and storage paths can be set here. Page 8 of 20

The Global page of the Settings perspective allows you to specify options that will apply universally to all QC analyses. Things like analysis task auto-deletion, notification options and storage paths can be set here. 3.4.2.1 General All miscellaneous settings can be found in General. They are summarized as follows. Check for Updates on Startup Tick this box if you d like QuiC to automatically check our server for newer versions of QuiC. CPU Affinity Here you can control what cores will be used in your analyses. If you are running multiple compute-intensive applications, for example, you may want to reduce the amount of cores used by QuiC. File Name Parsing Schema The file name parsing schema specifies a pattern that will be matched against your raw file names. We use this behaviour to extract information, called tags, from the file name (e.g. event tags such as recalibration, new column, S-lens cleaned, etc.). In this case, it is up to the users of QuiC to establish a rigorous file naming convention that allows to parse out this information. See the Tag Management section for more information about tags. Clicking on the File Name Parsing Schema field will bring up the Parsing Rule Editor which provides the capability to edit the parsing rule and test it on a sample file name. Figure 5 depicts the Parsing Rule Editor. The top bar is the parsing rule itself. Grey items are called tokens. Tokens delimit a region of text that you want to parse out as single or multiple tags. You can use any of the provided tokens or define some yourself. The white sections are constant text values that you expect to find in the raw file name. These can be typed explicitly in the parsing rule text field. In the figure, you can see that the file name must start with the string Inst- followed by an instrument name, followed by _Date-, followed by a date string, etc. Below the parsing rule text field, you find the token area. Here you can double click a token and it will be inserted into the position in the parsing rule field where the cursor is currently positioned. Below the token area, you can define your own custom tokens by providing a token name in the Parsing Token text field and, optionally, a delimiter in the Token Separator field. The delimiter splits up a string into multiple elements as in the case of the [EVENTS][-] token which will split the string up based on the - character. In our example, if a file name contains the string Recal-Equil-Slens between the _Evts- and _Meth- strings, the event tags assigned to that run will be Recal, Equil and Slens. In the Parsing Preview field, you can paste a test raw file name to check that all of the tags are correctly extracted. Below that, you will see what tags are assigned to what categories based on your pattern. We encourage our users to pick a naming convention that is consistent so that the parsing schema always extracts the right tags. Page 9 of 20

Figure 5. The Parsing Rule Editor allows you to design your own custom file name parsing rule that will extract tag metadata from the raw file names. Instrument Acquisition Buffer [mins] If you are monitoring a folder into which the mass spectrometer is actively writing files, you may need to tune this parameter. Some instruments will leave a certain amount of time between the writing of the spectral data into the file and the addition of the final footer data at the end of acquisition. This duration is difficult to detect and so we leave it as a parameter for the user to control. NOTE: At the time of writing this manual, QuiC has only been thoroughly tested on a live Thermo setup. It has not been tested in a setting where a monitor is set on a folder having files that are partially written by a Sciex instrument. QC Plot History Length To minimize clutter, you can set the maximum number of runs that will be displayed in the plots, regardless of which runs are selected. The most recent runs (according to the user defined order) will be used. QC Run Storage Path You can select where you d like permanent QC history data to be stored. This can be useful if you d like to store your history on a network so that multiple PCs can view it. Skip Duplicate Runs QuiC allows you to analyse the same run multiple times. However, if you have set up a monitor for a particular folder which contains some runs you ve already analysed, you can skip these runs in the analysis with this option. Also, if your plot contains duplicated runs, use this option to only display the most recently analysed duplicate. Temporary Directory QuiC s internal pipelines write large intermediate files to disk. If disk space is limited, you can set the path to which temporary files are written to a separate drive or partition. Page 10 of 20

3.4.2.2 Messaging You can opt for desktop notifications of important events in the analysis pipeline. Here you can specify whether you want notifications when an error occurs during a task, when a task was successfully completed, or when a task completed successfully but warnings were triggered. 3.4.2.3 Task Queue Task Queue options pertain to how individual run processing tasks are automatically handled in the Monitoring perspective. The parameters to be set are described as follows. Automatic Task Removal If you expect the task queue to grow substantially over time, you can opt to have tasks removed automatically. Note that removing a task does not remove your QC run data that is displayed in the QC perspective. Task removal will simply keep your analysis queue cleaner and easier to navigate. It also will keep memory usage to a minimum. Periodic task removal will remove all completed tasks at user-defined time increments. Cleanup can occur every N days, hours, or minutes where N is specified in the Value field. You can specify whether you would like successfully completed tasks, skipped tasks or erroneous tasks to be removed. Tasks can also be removed immediately, meaning as soon as completed. Again, successful, skipped and/or erroneous tasks can be selected from removal. Setting Automatic Task Removal to Never will prevent any tasks from being removed. Select Running Task The currently running task in the queue will be selected automatically, guaranteeing that you will always see the most recent runs in the queue. 3.4.3 Event Tags 3.4.3.1 Tag Management Before describing the Event Tags page, it makes sense to give an overview of tags in QuiC. Tags were introduced in QuiC 2.1 to serve as metadata that the user can encode via the file name. A tag can belong to any category, including user defined categories. Currently, all tags are simply stored into the processed QC run files and are not used for any purpose, with two major exceptions: event tags and condition tags. Event tags can be used to describe what interventions occurred before or during that run. For example, we can encode calibration and cleaning as event tags. Once your runs are processed and visible in the plots, you will be able to see your event tags as visual indicators. Figure 10 shows some tags visualized in a QC plot. Condition tags can be used to distinguish runs belonging to separate conditions (e.g. healthy and sick ). This is useful if you want to order your runs in a plot based on condition rather than time. QuiC maintains a database of all tags, including event tags. QuiC also maintains a repository of all instruments for which runs have been analysed. Each instrument is associated with zero or more tags. We limit each instrument to have no more than 10 tags. This design was chosen to avoid clutter in the plots. When a run is analysed, QuiC will automatically try to assign its event tags to the appropriate instrument for that run, unless the 10 tag cutoff is reached. Page 11 of 20

Figure 6. The Event Tags settings page allows you to edit and add new event tags. 3.4.3.2 Event Tags Settings Page Event tags are special tags that can be used to indicate interventions in the plots. Event tags that were automatically extracted from analysed runs using your parsing rule will show up here. You can select event tags you want to customize by browsing the list on the left. File tag string The text displayed here in the selection list on the left is the literal text that was matched as a substring in the file name. You cannot change this value. Instruments Event tags are only displayed in a plot if runs in the plot come from an instrument to which those tags are associated. The instruments field allows you to associate your tag to any number of instruments, unless the instrument is full. To assign an instrument to a tag, click in the instruments field and start typing the name of the instrument. An autocomplete field should be displayed, allowing you to select any instrument detected by QuiC. To remove instruments, click the x in their text area. Plot Annotation This is the actual text that will be displayed in a plot. This can be used in case you use code names or abbreviations for tags in your file name. Description This not only serves as a useful description for the user, but will also appear in the tag s hover dialog in the plots. Page 12 of 20

4 QuiC Usage QuiC can perform QC analyses in near real time by monitoring the folder in which mass spectrometric data is stored. Alternatively, files can actively be added to perform QC analysis. 4.1 Monitor Perspective The Monitor perspective in QuiC allows you to manage the QC analysis of different files from DDA, DIA, MRM and PRM from ThermoFisher and Sciex. Figure 7. The monitor perspective allows you to set up a task queue of QC runs. As runs are processed, extracted metadata and visualizations will be made available on-the-fly in QC perspective. You can add individual files or entire folders to the queue. Page 13 of 20

Figure 8. One powerful feature of QuiC is the ability to monitor folders. Files that are newly added to a monitored folder will automatically be added to the task queue. 4.2 QC Perspective QuiC stores all of the necessary information of the QC analysis and provides the review of the summarized extracted values. This data review step is done in the QC Perspective in the form of run-based visualizations. We start with a description of the History panel which allows you to select one or multiple runs to be visualized. Then, we describe each plot category. Tables 1 through 5 describe the scope of each of the plots. Specifically, whether the plot is identification-based (computed based on peptide precursor identifications) and, if so, whether peptides from the background library and/or irt kit are included in the numbers. The tables also indicate what methods are supported for each plot. 4.2.1 History Under History, all of the mass spectrometers from which the data was acquired serve as root elements of the run history hierarchy. Each instrument node can be expanded to reveal the different workflows used. The data is further subdivided into acquisition month, analysis time and, finally, individual run. By modifying your selection in the History tree, the displayed data in the plotting panel on the right changes dynamically. You can select multiple nodes in the tree by control-clicking or shift-clicking. Right-clicking on nodes and selections of nodes brings up a context menu of several options. You can assign custom event tags, comments, create sub-folders, or delete nodes. Page 14 of 20

Figure 9 depicts the Tag Editor. This form allows you to assign tags beyond the ones that were extracted from the file name. Double clicking tags on the right will annotate all selected runs with those tags. If you don t see your tag on the right, you may need to associate it with the correct instrument. Double clicking tags on the left will delete all custom occurrences of this tag from the runs. This will only remove the tag from the run if it was added via the Assign Event Tags option. Tags extracted from the run file name will still be associated with that run. Figure 9. The tag editor lets you assign custom event tags to your selected runs. QuiC also provides histograms for individually selected runs or ribbon plots to compare distributions across multiply selected runs. Depending on which method is selected in History, the following plots can be viewed. Figure 10. You can select one or multiple runs in the History tree. Runs are organized by instrument, method, acquisition date, and analysis date. Selecting multiple runs allows you to compare the runs within a single QC plot. For example, here we see the MS2 mass accuracy represented as a single box plot per run. Page 15 of 20

4.2.2 Mass Spectrometer Instrument QC is displayed in this category for all peptides in the background library. MS1 (MS2) Mass Accuracy Uncalibrated mass errors that were averaged in the Mass Calibration plot below. QuiC Mass Calibration Absolute MS1 and MS2 mass accuracy (systematic shift) in ppm before QuiC s calibration as compared to the precision (noise) after calibration. The average is computed across identified peptides in the background library. Note that the calibration is used in Biognosys other products and has shown to provide a substantial boost to our identification power. Plot MS1 Mass Accuracy MS2 Mass Accuracy QuiC Mass Calibration Identificationbased Background Peptides irt Peptides DDA DIA SRM/MRM PRM yes yes yes yes yes no no yes yes yes yes yes no no yes yes yes yes yes no no Table 1. Mass Spectrometer. 4.2.3 irt Peptides Plots in this category only display QC data extracted from the identified irt kit peptides. The plot types are summarized as follows. Delta irt Delta irt as given by the difference between the peptide s theoretical irt and its empirical irt, computed from the linear irt/rt regression function. Delta RT Delta RT as given by difference between the peptide s theoretical RT, computed from the linear irt/rt regression function, and its empirical RT. FWHM The full width at half maximum (FWHM) precursor peak width. Fragment ion intensities are summed up across fragments at every RT increment to create a single peak. FWHM is computed on this peak by taking half of the apex intensity and calculating the difference between two RTs associated with this intensity. irt Empirical irts computed from the irt/rt regression. MS1 Area The sum of all isotopic peak areas. MS2 Area Page 16 of 20

The sum of all fragment ion peak areas. RT Measured apex retention times. Plot Identificationbased Background Peptides irt Peptides DDA DIA SRM/MRM PRM Delta irt yes no yes yes yes yes yes Delta RT yes no yes yes yes yes yes FWHM yes no yes yes yes yes yes irt yes no yes yes yes yes yes MS1 Area yes no yes yes yes no no MS1 Mass Accuracy yes no yes yes yes no no MS2 Area yes no yes no yes yes yes MS2 Mass Accuracy yes no yes yes yes no yes RT yes no yes yes yes yes yes Table 2. irt peptides. 4.2.4 General General QC information. Gradient Length LC gradient lengths estimated from the data. MS1 (MS2) Scan Intensity [Box] Each run is represented as a distribution of total scan intensity values computer per scan. MS1 (MS2) Scan Intensity [Median] The median values depicted in the scan intensity box plot. Peak Capacity LC peak capacity computed by the following formula: g/( 1 1.695 FWHM n i i) Where g is the gradient length, n is the number of identified peptide precursors, and FWHM i is the peak width at half-maximum of the i-th precursor. TIC Total Ion Chromatogram (TIC), which provides insight into instrument stability and amount of sample injected. Page 17 of 20

Plot Background Peptides irt Peptides DDA DIA SRM/MRM PRM Gradient Length no no no yes yes yes yes MS1 Scan Intensity [Box] MS1 Scan Intensity [Median] MS2 Scan Intensity [Box] MS2 Scan Intensity [Median] no no no yes yes no no no no no yes yes no no no no no yes yes no yes no no no yes yes no yes Peak Capacity yes yes no yes yes yes yes TIC no no no yes yes no no Table 3. General 4.2.5 Discovery These plots provide QC for discovery-based acquisitions. Identifications The number of identified background precursors and protein groups per run. NOTE: Because our analysis pipelines evolve over time, we allow the user the ability to normalize identifications across QuiC version updates. This is to attempt to mitigate visible increases or decreases in identifications in the plot due simply just a change in our algorithms. If the user thinks his IDs changed due to a QuiC software update, he can right-click anywhere in the Identifications plot and select Normalize Across QuiC Versions. The formula for the normalized ID is given as follows ID normalized = ID median ID unnormalized ID version_median Where ID unnormalized is the original identifications value, ID version_median is the median ID value among all other ID values computed from the same version of QuiC as ID unnormalized, and ID median is the median ID overall. Note these values are only computed on the selected runs and not the entire set of runs. We suggest to use this option only when you have a sufficient number of IDs per version. Plot Identificationbased Identificationbased Background Peptides irt Peptides DDA DIA SRM/MRM PRM Identifications yes yes no yes yes no no Table 4. Discovery Page 18 of 20

4.2.6 DDA Advanced These plots pertain only to DDA data and were first presented in (Ma et al., 2012). Max Scan Frequency The fastest frequency [scans per minute] for MS1 (MS2) collection in any minute. MS1 Density The RT at which each quartile of the MS1 scan peaks have occurred. MS1 Events per RT-duration The RT interval for each quartile of all MS1 events divided by RT-Duration. MS2 Density The RT at which each quartile of the MS2 scan peaks have occurred. MS1 Events per RT-duration The RT interval for each quartile of all MS2 events divided by RT-duration. PSM Charge Profile A breakdown of all of the peptide spectrum matches (PSMs) with a clear feature having charges 1, 2, 3, 4, 5, >5. Also considered are peaks originating from the precursor window that lack known charge but appear to have charge 1 or charge >1. Scans The number of MS1 (MS2) scans that were collected. TIC Change Ratio The TIC Change Ratio is computed as follows: For each consecutive scan pair, the TIC fold change is computed. These fold changes are then sorted in increasing order. The TIC Change Ratio for quartile N is given as the ratio of the N-th quartile fold change to the (N-1)-th quartile fold change. TIC per RT-duration The RT interval for which each quartile of the TIC accumulates divided by RT-duration. TIC Ratio The TIC ratio for the N-th quartile is given as the log ratio of the area under N-th intensitysorted quartile to that of the (N-1)-th quartile. Page 19 of 20

4.2.7 Plots QuiC provides custom options for the plots via a right-click context menu. This menu provides options to copy, print, save as, sort by various criteria, normalize, and change various visualization characteristics. Plot Max Scan Frequency MS1 Density MS1 Events per RTduration MS2 Density MS Events per RTduration PSM Charge Profile Identificationbased Background Peptides irt Peptides DDA DIA SRM/MRM PRM no no No yes no no no no no no yes no no no no no no yes no no no no no no yes no no no no no no yes no no no yes yes yes yes no no no Scans no no no yes no no no TIC Change Ratio TIC per RTduration no no no yes no no no no no no yes no no no TIC Ratio no no no yes no no no Table 5. DDA Advanced. 5 References Escher, C., Reiter, L., MacLean, B., Ossola, R., Herzog, F., Chilton, J.,... & Rinner, O. (2012). Using irt, a normalized retention time for more targeted measurement of peptides. Proteomics, 12(8), 1111-1121. Ma, Z. Q., Polzin, K. O., Dasari, S., Chambers, M. C., Schilling, B., Gibson, B. W.,... & Tabb, D. L. (2012). QuaMeter: multivendor performance metrics for LC MS/MS proteomics instrumentation. Analytical chemistry, 84(14), 5845-5850. http:// http://pubs.acs.org/doi/pdf/10.1021/ac300629p Page 20 of 20