Olink NPX Manager. User Guide

Transcription

1 Olink NPX Manager User Guide

2 Table of contents INTRODUCTION 3 Process 3 Limitations 3 Requirements for analysis 3 List of abbreviations 3 TO CREATE A HEAT MAP CT CSV FILE 4 OLINK NPX MANAGER STEP BY STEP ANALYSIS 8 1. Import a.csv file 9 2. Enter project information 9 3. Verify sample types and layout 9 4. Calculate NPX values Perform quality controls Export data Create a Certificate of Analysis 12 VIEWS 13 Tree view 13 Selection Information 14 Project 15 Plate View 16 Plate Data 18 Data View 19 Heatmaps 20 QC View 21 LOD View 22 Plate Z-score 23 Event Log 23 QUALITY CONTROL 24 QC 25 Run QC 25 NORMALIZATION METHODS 26 IPC normalization 26 Intensity normalization 26 Control normalization 26 TROUBLESHOOTING 27 Inconsistent results 27 Deviating controls 31 Warning messages 34 INDEX 35 For questions, guidance and support, contact Olink Support on support@olink.com.

3 Introduction Olink NPX Manager is an easy-to-use data import and pre-processing tool. The tool lets you import data, validate data quality and normalize your Olink data for subsequent statistical analysis. Process The Fluidigm Biomark Data Collection software captures images of the processed IFC runs throughout the Real-Time PCR cycling, and those images are imported into the Fluidigm Real-Time PCR Analysis software. The Real-Time PCR Analysis software is a tool for analyzing real-time PCR data and exporting heat maps of Ct values for downstream preprocessing using Olink NPX Manager. Fluidigm software Olink NPX Manager Prepare CSV files Import files Annotate sample types Calculate NPX QC evaluation Export data Save Certificate of Analysis Figure 1. Flowchart describing steps involved in the analysis of Olink data Limitations This manual only contains a step-by-step instruction for exporting heat maps of Ct values in.csv format for analysis in Olink NPX Manager. For additional information and troubleshooting of this step, please see the documentation for Fluidigm Real-Time PCR Analysis software. Requirements for analysis List of abbreviations System requirements Windows 7 or later.net Framework or later Recommended system: Intel Core i5 or higher, 8GB RAM Files and information needed for analysis Data file ID names plate layout Run data (bml-file) PLT files from %CV CoA IFC IPC LOD NPX PCR QC Coefficient of Variance Certificate of Analysis Integrated Fluid Circuits Inter-Plate Control Limit of Detection Normalized Protein expression Polymerase chain reaction Quality Control 3

4 To create a heat map Ct csv file Heat maps exported from Fluidigm Real-Time PCR Analysis are the input data for Olink NPX Manager. The heat maps are exported in.csv format. 1. Open a chip run with Fluidigm Real-Time PCR Analysis software The analysis requires the file ChipRun.bml which is found in the chip run folder. 1. In the Fluidigm Real-Time PCR Analysis software, go to File > Open. 2. Browse to the chip run folder and select the ChipRun.bml file. 2. Add sample information Enter the sample names. To add the sample names in this step ensures maximum traceability and easy annotation in Olink NPX Manager. names must be unique within a project. 1. Prepare a Microsoft Excel spreadsheet with sample names that correspond to the sample plate layout: Table 1. Example plate layout A A1 A2 A3 A4 A5 A6 A7 A8 A9 A10 A11 A12 B B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 C C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 Neg Ctrl D D1 D2 D3 D4 D5 D6 D7 D8 D9 D10 D11 Neg Ctrl E E1 E2 E3 E4 E5 E6 E7 E8 E9 E10 E11 Neg Ctrl F F1 F2 F3 F4 F5 F6 F7 F8 F9 F10 F11 IPC G G1 G2 G3 G4 G5 G6 G7 G8 G9 G10 G11 IPC H H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 IPC 4

5 2. In the Real-Time PCR Analysis software s Chip Explorer pane, select Setup. In the Task pane, click on the New button. Figure 2. Left pane of Fluidigm Real-Time PCR Analysis software with Setup selected 3. Set the container type to SBS Plate and the format to SBS The format is now the same as the sample format created in Microsoft Excel in step 1. Copy the sample names from Microsoft Excel (do not include the column and row headers). 5. Go to the Real-Time PCR Analysis software and select the A1 well in the sample setup. Paste the sample names and set Data Item to Name when prompted: Figure 3. Data Item selection window 6. Click Accept. 7. Map the plate layout to how the samples were loaded in the chip: In the Plate Settings section, go to the Task pane and then the Mapping field. Press the button and select the M96--SBS96.dsp file. NOTE This assumes that the recommended IFC loading was used. 8. Done. You have now entered the information needed to couple a reaction well to a sample. 5

6 3. Add detector information It is essential for the analysis in Olink NPX Manager that you add the panel and biomarker information required for downstream data processing. The setup is similar to the sample setup, but in this case a template file from the Olink Proteomics webpage is used. 1. Download a Detector Setup template file (in.plt format) from that corresponds to the biomarker panel you have used. 2. In the Real-Time PCR Analysis software, go to the Task pane under the Chip Explorer section. Select Detector Setup, then click the Import button in the Setup section. Figure 4. Left pane of Fluidigm Real-Time PCR Analysis software with Detector Setup selected 3. Browse to the downloaded.plt template file and click the Open button. 4. Done. You have now entered the information needed to couple a reaction well to a biomarker. 6

7 4. Change analysis settings and reanalyze Before data can be exported, some settings must be changed. 1. In the Real-Time PCR Analysis software, go to the Chip Explorer pane and select Analysis Views. 2. In the Task pane under the Analysis Settings section, make sure Quality Threshold is set to 0.5, Baseline Correction to Linear and Ct Threshold Method to Auto (Global) : Figure 5. Analysis Settings section in the Task pane of Fluidigm Real-Time PCR Analysis software 3. In the Analyze section, press the Analyze button. All the analysis settings and the sample and detector settings are now updated. 4. Done. The data is now ready to be exported. 5. Export Ct-values in heatmap format In the Real-Time PCR Analysis software, there are two ways to export data: in a table with each data point on a single row, or as a 96x96 matrix (heat map). In Olink NPX Manager, heat maps must be used. 1. Make sure Inlet-based View is selected in the Layout drop-down menu. This should be the default. 2. Select File > Export. 3. Under File name, name your raw data file. This name is used in the final export from Olink NPX Manager. 4. Under File format, select Heat Map Results (*.csv). Press Save. 7

8 Olink NPX Manager Step by step analysis This section describes how you analyze data in Olink NPX Manager. The following steps are included in the standard operating procedure: 1. Import a.csv file 2. Enter project information 3. Verify sample types and layout 4. Calculate NPX values 5. Perform quality controls 6. Export data 7. Create a Certificate of Analysis Tree view showing Olink panels and chip runs Main work area Information box displaying statistics about the currently selected item Figure 6. Olink NPX Manager main window with Plate View tab selected 8

9 1. Import a.csv file Select File > Import CSV and browse to the heat map file (.csv) exported from Fluidigm Real- Time PCR Analysis software. Multiple files within the same project can be imported at once. You can also import files by dragging and dropping the files from Windows Explorer onto the tree view. During import, Olink NPX Manager checks for duplicate sample names and alerts you if duplicate sample names are found. Unique sample names are strongly recommended and necessary when exporting the data. Each imported run is annotated with the Olink panel specified by the.plt file used in the Real-Time PCR Analysis software, but you must enter the data file version. The data file to be used is specified in the Article and lot configuration sheet found together with the Olink reagents. The imported IFC runs are shown in the tree view to the left, grouped by Olink panel. You can reorganize the IFC runs in the tree view by dragging and dropping them. 2. Enter project information Enter the necessary project information on the Project tab: Project Name is used in later stages and should be entered. Type is shown on the Certificate of Analysis. Customer Information, Business Development Manager and Analysis Lab is shown on the cover page of the Certificate of Analysis. The s Randomized checkbox should be checked if samples are randomized between the sample plates. This determines which normalization method will be used. 3. Verify sample types and layout 1. Click the + sign next to an Olink panel name to expand the tree view and display the imported runs for each Olink panel. Highlight the first run and click the Plate View tab. 2. Verify that the plate layout is correct. You can change the plate layout by right-clicking on a specific well or a selection of wells and changing the well type. Available types are, Control, Negative Control, IPC and Not Used. 3. Make sure that the correct data file version is selected in the drop-down menu above the plate layout. The same data file version will be used for all IFC runs of the same Olink panel in the project. 4. Repeat steps 2 and 3 for all imported IFC runs before continuing. 9

10 Tip: To add or change sample names 1. Create a sample layout in Microsoft Excel and enter the sample names (see Add sample information on page 4). 2. Copy the plate layout from the spreadsheet. Open the Plate View tab in Olink NPX Manager and go to Edit > Paste to paste the copied layout. 4. Calculate NPX values 1. Select an Olink panel in the tree view. 2. Click on Analysis > Calculate NPX. NPX values are calculated for all IFC runs in the selected Olink panel. 3. Make sure NPX Value is selected in the status bar in the lower left corner and click on the Data View tab to view the NPX values. NOTE IPC normalization is used by default for single plate studies or non-randomized studies. For randomized studies of more than one IFC run per Olink panel, intensity normalization is used if the s Randomized checkbox is checked on the Project tab. See Normalization methods on page 26 for more information about the available normalization methods. 5. Perform quality controls 1. Select a plate in the tree view to the left and go to the QC View tab. 2. First perform the quality control on each plate separately, then make an overall assessment. The acceptance criteria for passing QC are described in Table 2. Table 2. Quality Control guidelines Criteria Incubation Control 2 deviation Detection Control deviation Std. Dev. of Incubation Control 1 Std. Dev. of Incubation Control 2 Std. Dev. of Detection Control Number of flagged samples Recommended value < ±0.3 NPX from plate median < ±0.3 NPX from plate median < 0.2 NPX < 0.2 NPX < 0.2 NPX < 1/6 of total number of samples on plate For more information on quality controls, see Quality control on page

11 Performing a quality assessment Apart from variations in the internal controls displayed in the QC View and LOD information in the LOD View, the Selection Information pane highlights any values that are cause for additional review. For more information about the Selection Information pane, see Table 5. Known issues are described in the Troubleshooting section. Other information that may indicate problems with a run are listed in Table 3. Table 3. Quality assessment Information Recommended value Comment Assay LOD LOD < 2.5 NPX If LOD > 2.5 please contact Olink Support for guidance. Assay LOD deviation < 1 NPX If LOD deviates more than 1 NPX between plates, it can cause high inter-plate CV. Plate ANOVA 10 > 10 Row, Column ANOVA < No warning. May be caused by insufficient randomization or other issues. No warning. Possible randomization issue. Re-run plate or prove that this is not the result of a poorly executed run. For high values, investigate the Plate Data view. %CV Intra < 15 % See troubleshooting section on page 27. %CV Inter < 25 % See troubleshooting section on page 27. If all plates pass quality control and assessment, the data analysis is finished and the data is ready for export and reporting. 11

12 6. Export data Data can be exported to a Microsoft Excel.xlsx file or.csv file for use in other applications and for statistical analysis. 1. Select NPX Value in the status bar in the lower left corner of the main window. 2. Go to File > Export Data. Data can be exported for all runs and Olink panels in the project, or for the selected run or Olink panel only. 3. Click Yes to export data for all Olink panels and runs or click No to export data for the selected item only. 4. Enter a filename and location in the Save dialog, select an export format (Excel files *.xlsx or CSV-files *.csv) and click the Save button. NOTE NPX values below LOD are exported as NaN or LOD values, depending on the setting on the Project tab. s that are flagged by the analysis are reported in red text. NPX-values that are below LOD have a red background. s, assays or data points that have been marked as failed in the software show empty cells. The layout is described in Table 4. Table 4. Layout of exported NPX data Project Name NPX data Olink NPX Manager version Panel Panel 1 Panel x Panel 1 Panel x Panel 1 Panel x Assay Plate ID Plate ID QC Warning QC Warning Uniprot ID Olink ID # plate_1.csv plate_x.csv Pass / Warning # plate_1.csv plate_x.csv Pass / Warning #x plate_1.csv plate_x.csv Pass / Warning Max LOD Missing Data freq. (%) Pass / Warning Pass / Warning Pass / Warning 7. Create a Certificate of Analysis Once all data has been thoroughly checked, Olink NPX Manager can generate a Certificate of Analysis (CoA) for the project. The CoA includes information and statistics about the project in an easy-to-read format. Select File > Save Certificate of Analysis to save the CoA as a PDF document. 12

13 Views Tree view The tree view displays the imported IFC runs, grouped by Olink panel. Figure 7. Olink Panels tree view Click on the + next to the Olink panel name to display the imported IFC runs for each Olink panel. Highlight an Olink panel to display information about all runs in that panel. If an Olink panel is highlighted in the tree view, information for the first run is displayed on the run specific tabs. On the LOD View and Plate Z-score tabs, data from all plates in the selected Olink panel are shown. Highlight an individual run to see information about that specific run. Change the order of the plates in the tree view by dragging and dropping a plate to its desired location. Remove a plate or Olink panel from a project by highlighting the item in the tree view and clicking Edit > Delete. A pop-up audit window asks for the reason for removing runs or Olink panels. 13

14 Selection Information The Selection Information pane in the lower left corner displays information about the currently selected item in the tree view: all sample plates for an Olink panel or an individual sample plate. This information gives you a first indication of the data quality. Figure 8. The Selection Information view The three ANOVA fields indicate the number of assays where the variation between plates/rows/columns is larger than the variation within the plates/rows/columns. A high number indicates systematic variation. For more information, see Troubleshooting on page 27. The number of flagged samples (samples that did not pass the quality control) is displayed below the ANOVA fields. %CV is the average %CV of all assays based on linear NPX values. %CV will only be calculated if control samples are included on the sample plate and annotated as Control in the Plate View. See Table 5 for a description of all content in the Selection information pane. Table 5. Description of Selection Information Item Description # Plates Number of IFC runs in selected Olink panel. # s Number of samples, excluding control samples, in selected Olink panel or IFC run. # Plate ANOVA (p < 0.05) # Row ANOVA (p < 0.05) # Column ANOVA (p < 0.05) Number of assays where the variation between plates/rows/columns is larger than the variation within the plates/rows/columns. The p-value is calculated using the selected display unit ( Ct Value or NPX Value ). For specific limits, see Perform quality controls on page 10. # Flagged Positions Number of flagged positions (including control samples) in the selected Olink panel or plate. # Proteins detected > 75% Number of proteins detected in more than 75% of the samples. %CV (Inter) %CV (Intra) Normalization method Mean inter-plate CV for all assays. Mean intra-plate CV for all assays. Displays the normalization method used for NPX calculation. IPC normalization is default for single plate runs. Intensity normalization is default for randomized studies. 14

15 Project The Project tab contains fields for entering project information. The information entered on this tab is saved in the project and some of it is displayed on the Certificate of Analysis. Figure 9. The Project tab Project Name The project name is displayed in the NPX data output file and the Certificate of Analysis. Type This field is used to describe the sample matrix, e.g. Plasma or Serum. The information is displayed on the Certificate of Analysis. Customer Information, Analysis Lab and Business Development Manager Information entered in these fields is displayed on the first page of the Certificate of Analysis. Comments This field can be used for any comments and is not included in Certificate of Analysis or data export. Click on the Comments header to open the comments field in a separate window for easy access from other views. 15

16 Comments for report Information entered in this field is displayed on the Certificate of Analysis. This field can be used for project information that is not covered by the default Certificate of Analysis. Click on the Comments for report header to open the comments field in a separate window for easy access from other views. Flagged Positions This field shows the Olink panel, sample names and plate name for flagged samples. The list is populated when the NPX values have been calculated. If a sample is flagged in the QC, every assay in that Olink panel is flagged for that sample. Project Options s Randomized Check this box if the samples are randomized across plates and intensity normalization can be used instead of IPC normalization. For more information about what this means, see Normalization methods on page 26. Display NPX values < LOD As Select how Olink NPX Manager should display NPX values below the Limit of Detection (LOD): NaN (Not a Number): NaN is displayed for values below LOD. LOD: Calculated LOD is displayed for values below LOD. This is the default. Plate View The Plate View tab shows the sample plate setup for the selected run, and general information about the Fluidigm run. Figure 10. The Plate View tab 16

17 On the Panel drop-down menu, select the data file version of the current panel. The data file version is linked to the lot number of the reagent kit for the Olink panel that was used. The lot number can be found in the Article and lot configuration sheet. The same data file version must be used for all runs/sample plates analyzed with the same Olink panel within a project. Each plate position is automatically annotated to one of the following content types: Control Negative Control IPC Not Used If a position has been annotated incorrectly: 1. Click on the cell or click and drag over several cells to select the cells. Select multiple cells by holding the ctrl key or shift key. 2. Right-click on the selection and select the correct content type from the contextual menu. Flagged samples A red flag is displayed next to samples that did not pass the quality control. Flagged samples can be removed from QC calculations by right-clicking a sample and selecting Exclude Flagged From QC, or removed by right-clicking and selecting Mark as Failed. The software then automatically calculates new QC values without the flagged samples and the plate QC data can be reviewed again. Data for flagged samples that have been excluded from the QC analysis are exported to the NPX file. For samples marked as failed, no data is shown in the NPX file. 17

18 Plate Data The Plate Data tab by default shows heat maps of the four internal control assays, Incubation Control 1, Incubation Control 2, Extension Control and Detection Control. This view is useful for identifying position effects within a plate (e.g. if one column of samples deviates from the rest, this could indicate a pipetting error). Figure 11. The Plate Data tab The heat map displays the deviation from plate median for the control assay on a blue white red color scheme. Blue values are below median and red values above median. The values displayed in the view are either Ct-values or NPX-values depending on the selection in the pop-up menu in the lower left corner of the main window. Use the assay drop-down menu to change which assay is displayed in the heat map. 18

19 Data View The Data View tab displays data (Ct or NPX) in a grid view, depending on the selection in the lower left corner of the screen. If NPX values are displayed, the plate LOD is also displayed after each IFC run in the list. Figure 12. The Data View tab Use the Display drop-down menu to select if you want to display data for all sample types or for samples, controls, Negative Control or IPC only. Click on an assay header to open a web page on Olink s web site describing the selected assay. Use the Grid size slider to decrease or increase font and cell size of the grid to make it easier to read or to see patterns between IFC runs. You can define samples, assays or data points as failed by right-clicking on the failed entity and select Mark /Assay/Datapoint as Failed from the popup menu. A pop-up audit window asks for the reason for the change. This information is displayed on the Certificate of Analysis. The exported data output file displays empty cells for data points or samples marked as Failed. To undo this operation, select Mark / Assay/Datapoint as Valid from the popup menu. 19

20 Heatmaps The Heatmaps tab contains a color coded view for all assays and samples in the selection. The heat map displays the deviation from median on a blue white red color scheme per assay. Blue values are below median and red values above median. Displayed values are either Ct or NPX values, depending on which is selected in the menu in the lower left corner of the main window. This view is useful for finding patterns, such as samples or plates where many proteins are higher or lower expressed, or outlier samples, for specific assays. Figure 13. Heatmaps view showing samples deviation from mean per assay Use the drop-down lists to display data for specific Olink panels or individual plates. Use the Display drop-down list to select the sample type to display (, IPC, NegCtrl, Control). Use the Grid size slider to increase or decrease the size of the heat map to make it easier to read or to see patterns between plates. For an example, see Extreme outlier samples on page

21 QC View The QC View tab displays quality control data for the plate selected in the tree view. The quality control is performed individually for each plate during NPX calculation. No data is displayed on this tab until NPX has been calculated. Figure 14. The QC View tab with one flagged sample highlighted The top table displays the number of flagged samples on the selected sample plate and the standard deviation for the internal control assays: Incubation Control 1 and 2 and Detection Control. The scatter plot displays the NPX signal deviation from median for Incubation Control 2 and Detection Control for all samples. If either of these values exceed the +/- 0.3 NPX threshold, the sample is marked as flagged. Flagged samples can be removed by right-clicking on the flagged sample and selecting Exclude Flagged From QC Analysis. The QC data is then recalculated without the excluded samples. The table below the scatter plot shows the value for the deviation from median for Incubation Control 2 and Detection Control for each sample. Flagged samples are highlighted in red. For more information about the QC process, see Quality control on page

22 LOD View The LOD View (Limit of Detection) contains a bar chart showing frequency of missing data for all plates in the selected Olink panel or for a specific plate only. When multiple plates are analyzed, the maximum LOD is used as data cutoff. The table below the bar chart shows the Limit of Detection for all plates in the selected Olink panel or for an individual plate. LOD is calculated using the following formula: Figure 15. The LOD View tab Maximum LOD value for each assay is highlighted in red when a panel with more than one plate is selected. An assay name highlighted in red signifies an assay for which the LOD deviation is greater than 1 NPX value between plates. This indicates increased background variation. An assay value highlighted in yellow signifies an assay with LOD higher than +/ A high LOD means that the signal for the negative controls is higher than what was measured during validation of the panel. If a high LOD results in low detectability, you might want to investigate whether the LOD affects the data. If LOD on one plate removes more data on other plates, the affected assay can be marked as failed to exclude the plate from LOD calculation and its data points from the exported data. 22

23 Plate Z-score The Plate Z-score tab displays a scatter plot which represents the deviation of total intensity of each sample from mean. Use this plot to detect systematic variance in total intensity between plates or to identify samples with deviating total intensities. Figure 16. The Z-score tab displaying z-score plot for the sum of all assays per plate The sum of NPX for each sample is calculated and converted to Z-scores. This means that a sample at +1 on the plot has one standard deviation higher NPX values overall than the average of all samples. Use the Assay drop-down menu to determine if the plot should visualize the Z-score distribution for all assays or for an individual assay in the panel. Event Log The Event Log tab displays all events for the current project. Figure 17. The Event Log tab displaying all changes performed on the project 23

24 Quality control Olink has built-in quality controls in all multiplex panels. Each 92-plex panel contains 96 assays. Four of those are internal controls that allow for an in-process quality control designed to monitor different steps of the protocol: immuno reaction, extension and amplification/ detection. The controls included are illustrated in Figure 18. IMMUNO REACTION EXTENSION REACTION AMPLIFICATION/DETECTION 2 INCUBATION CONTROLS 1 EXTENSION CONTROL 1 DETECTION CONTROL Figure 18. Outline of Olink internal controls The two incubation controls consist of two different non-human antigens measured with PEA assays: Incubation Control 1 and 2. These controls monitor potential variation in all three steps of the reaction. The Extension Control is an antibody coupled to both DNA-tags (hence always in proximity). This control monitors the extension and amplification/detection step. The Detection Control is a complete double stranded DNA amplicon which does not require any proximity binding or extension step. This control monitors the amplification/ detection step. The internal controls are used for both sample and run QC as described below. The quality control of data is performed separately for each sample plate. 24

25 QC Each of the internal controls are spiked into the samples in the same concentration. The signal for these are therefore expected to be the same over the plate. QC is performed using the Detection Control and Incubation Control 2. Within each run, the levels of these controls are monitored for each sample and compared against the median of all samples. If either of the controls deviate more than the acceptance criteria allow (see below), the sample is flagged. The Extension Control is used in the normalization step and in generation of NPX, and hence not included in the quality control of data. Acceptance criteria for passing a sample: Incubation Control 2 and Detection Control deviates < +/- 0.3 NPX from plate median. Deviating values for the internal controls can be caused by, for example, errors in pipetting or pre-analytical factors in the samples that affect the performance of the controls. For more information on troubleshooting flagged samples, see Troubleshooting on page 27. Run QC The internal controls are used also in the run QC. This QC assesses the variation over the plate for each of the Incubation Controls 1 and 2 and the Detection Control. If the variation for one of the controls is too large (see below) the entire run is considered unreliable. Acceptance criteria for passing a run: Standard deviation of Incubation Control 1 & 2 and Detection Control: < 0.2 NPX. Number of flagged samples: 1/6 of total number of samples (i.e. 16 in a full plate). If a too large variation is observed for either of the controls, go to the Plate View tab to evaluate the data. For example, if individual samples show extreme values or if a certain sample column is affected, these samples can be marked as failed and the QC redone and re-evaluated. For more information on troubleshooting of this step, see Troubleshooting on page 27. In addition to passing or failing individual plates, ensure that no systematic bias is present in the data. The Selection Information pane in the bottom left corner alerts you to such issues. %CV is calculated using control samples if present in duplicates on each sample plate. The reported %CV is the mean %CV over all assays, and this is only calculated using data over LOD. A high %CV does not fail a run automatically, but should be a cause for further investigation. Reference value for Inter %CV: < 25% Reference value for Intra %CV: < 15% 25

26 Normalization methods Olink NPX Manager has three available methods for data normalization and minimization of systematic biases between sample plates. These methods are described below. An important concept when deciding on normalization procedure is randomization, which in this context applies to the sample placement across the plates. For randomized studies with more than one plate, intensity normalization is the default normalization. For other studies, IPC normalization is default. IPC normalization Three inter-plate controls (IPC) are included on each plate and run as normal samples. The inter-plate control is a pool of 92 antibodies, each with one of the pairs of unique DNA tags on it positioned in fixed proximity (i.e. 92 Extension Controls). The median of the three IPCs is used as normalizer for each assay, and this compensates for potential variation between runs/plates. This method is completely independent on the samples included on the plate and is therefore recommended for projects where complete randomization of samples cannot be guaranteed. Once the data is ready for NPX calculation, go to the Analysis > Calculate NPX to perform the normalization. Intensity normalization The intensity normalization adjusts the data so that the median NPX for a protein on each plate is equal to the overall median. Each plate is adjusted so that the median of all assays is the same on all plates. This method requires that the true median of each plate is the same. One way of ensuring this is to randomize the samples beforehand. If there is total randomization, this method outperforms other normalization methods. If there are specific types of samples that are only available on certain plates, this normalization method should not be used. Control normalization The control normalization works in the same way as the IPC normalization, but with one addition. While the IPC adjusts each protein to the level of a reference, the control normalization also adjusts the total intensity of entire plates. This is useful if you have plates or projects that differ on average in a way that cannot be explained biologically. Control normalization can be used to reduce systematic variation in non-randomized studies. This normalization method requires the addition of at least two control samples on each plate. NOTE This is an optional normalization method that should only be used when standard normalizations are not sufficient. 26

27 Troubleshooting Inconsistent results Variation between plates Issue: The total NPX varies between plates. The Plate ANOVA value in the Selection information box (Figure 19) shows a high value. This indicates that most assays are associated with the column on the plate they are located in. The variation is also shown on the Plate Z-score tab (Figure 20). Figure 19. The Selection information window, with a Plate ANOVA value that indicates variation between plates Figure 20. Plate variation that should be solved by intensity normalization Explanation: If the samples are completely randomized, check the s Randomized checkbox on the Project tab (Figure 21), in order to use intensity normalization during the analysis. The results will then look like the example in Figure 22. Figure 21. The s Randomized checkbox on the Project tab Figure 22. The same results as in Figure 20, after intensity normalization 27

28 Issue: High Inter-CV value > 25% Explanation: The Control samples differ between sample plates. Check annotation of the control samples and that they pass Quality Control. If Intensity normalization has been used, ensure that randomization assumption is valid by comparing with IPC normalization. Variation within a plate Issue: High Intra-CV value > 15% Explanation: The Control samples differ within the sample plate. Check annotation of the control samples and that they pass Quality Control. Issue: Areas of a plate (rows and/or columns) have systematically higher or lower values (Ct and/or NPX) than the rest of the plate. The columns or row ANOVA in the Selection Information box show high values if there is variation caused by the sample position on the plate. The effects are visualized in the Plate Data tab. Explanation: Within-plate effects are often caused by laboratory mistakes. Some examples are found in Table 6. NOTE Make sure that the deviation cannot be explained with biological variation, i.e. that a unique sample group is placed on one column/row. Table 6. Common problems and reasons for within-plate effects Problem Possible cause Figure reference First column different than the rest of the plate (observed for internal controls) The pipette was not preconditioned. A specific column or columns is different than for the rest of the plate (observed for internal controls) A mistake when the incubation solution, extension solution, detection solution or samples were pipetted. Figure 23 One row consistently different from the rest of the plate (observed for internal controls and/or samples) The pipette tip in that specific position was not tight enough. A gradient from row A to row H Pipetting was done at an angle The samples were not sufficiently vortexed Both usually occur during the dilution step for diluted panels. Figure 26 Deviating Z-score distribution for single assays on one plate Primer contamination The primer solution was contaminated. Figure 25 28

29 Figure 23. Ct-values that show results of laboratory mistakes. See Table 7 for a description of errors performed on this IFC run. Figure 24. NPX values that show results of laboratory mistakes. See Table 7 for a description of errors performed on this IFC run. 29

30 Table 7. Explanation of columns in Figure 23 and Figure 24. Red numbers indicate laboratory mistakes Column 4 (correct) Column 7 Column 8 Column 9 Column 10 Column 11 Column 12 Incubation mix (µl) volume (µl) Extension mix (µl) Detection mix (µl) PCR product (µl) Figure 25. Ct values that show primer contamination of Incubation Control 2 Figure 26. Within plate effects due to incorrect or insufficient vortexing of the sample plate during sample dilution 30

31 Deviating controls If the normalized value for a specific sample deviates from the rest of the sample set, the sample is flagged. Flagged samples Issue: A sample is flagged. Explanation: A sample is flagged when one or several internal controls deviate for that specific sample. The behavior of the internal controls makes it possible to understand why the sample is flagged. Flagged samples are shown on the Project tab in the table Flagged Positions. For more detailed information about the flagged samples, go to the QC View tab (Figure 27) and the Plate Data tab (Figure 28). Figure 27. The QC View tab, where sample 20 is flagged by the Incubation Control, and sample 34 is flagged by the Detection Control Figure 28. The Plate Data tab for the QC View tab in Figure (the top flag) has a higher CT for the Incubation Controls. 34 (lower flag) has a higher CT for the Incubation Controls and the Extension Control. 31

32 High LOD Issue: More than 10 assays report high LOD. Explanation: This could be caused by using the wrong datafile number or not annotating negative controls or IPCs correctly. If correcting these issues does not resolve the problem, contact Olink Proteomics support or re-run the plate. Deviating incubation controls Issue: A sample is flagged by Incubation Control. Explanation: If a sample is flagged by Incubation Control, the incubation controls deviate. If the two incubation controls deviate, but not the extension and detection controls, this is an indication that something is affecting only the incubation controls. Table 8. Common reasons for deviating Incubation Controls Possible cause Explanation Solution matrix If the sample matrix for the flagged sample is different from the others on the same plate, the incubation environment can be different. This can make the reaction slightly more or less efficient. Do the QC evaluation for one sample type at a time. volume or concentration The sample volume is too high or too low. Change sample type in the Plate View to Not Used. Run the sample again and make sure the correct volume is used. See figure 23, column 10, or figure 29 for examples. quality If the sample is stored in a freezer for long periods of time, it can evaporate. A more concentrated sample can increase possible matrix effects, and thus make the internal controls more or less efficient. type Olink assays are validated for serum and plasma. Other sample matrices can contain factors that interfere with the immunoassay step. Standardize samples as much as possible. (E.g.: for lysed cells and tissue, use similar amount of protein in each sample) 32

33 Deviating detection control Issue: A sample is flagged by Detection Control. Explanation: If a sample is flagged by Detection Control, this means that the normalized value for the Detection Control for this specific sample deviates from the rest of the sample set. One example can be seen in Figure 27 and Figure 28. Data is normalized using the Extension Control. Since both Incubation Controls and the Extension Control display increased Ct-values, the normalization step will adjust the data. The Detection Control that did not show increased Ct-values will be overcompensated by normalization against the Extension Control and thereby deviate from the rest of the sample set after normalization. This type of flag is generally caused by the same reasons as flagged Incubation Controls as described above. It is not uncommon that both the Incubation Control 2 and Detection Control flags at the same time, with opposite direction in the QC View. This is seen when the flagged sample affects both the extension and immunoassay step, but to different extent. Extreme outlier samples Extreme outliers can be discovered in different views (Plate Z-score, Plate Data, Heatmap). In this example, only technical outliers are illustrated. In Figure 29 below, two types of outliers are illustrated. Figure 29. Heatmap view NPX values from a single plate run which contains two outliers. 25 (blue) has the lowest NPX values for all assays and 71 (red) has the highest NPX values for all assays. 25 in this example is extremely low for all assays except the internal controls. By looking at the NPX data it is obvious that all values are below the LOD and the obvious conclusion for this outlier is that there is no biological sample present in that well. 71 in this example is roughly 3 NPX higher than the rest of the samples. This can arise from poor dilution of a sample when running one of the high abundant panels. 33

34 Missing sample data in exported NPX file Issue: Data for some samples are not exported. Explanation: This can be caused by not using unique sample names. Ensure that sample names are unique or change sample type to Control for non-unique samples to force export of data for these samples. Warning messages The following warnings can be displayed during import of Fluidigm csv files: Could not identify panel This warning indicates that the assay names and order does not correspond to any Olink panel. This could be caused by using an incorrect.plt-file or wrong layout when creating the.csv file in Fluidigm Real-Time PCR Analysis software. Quality Threshold does not meet specified criteria 0.5. This warning indicates that the settings for Quality Threshold was not set to 0.5 in the Fluidigm Real Time PCR software. See Change analysis settings and reanalyze on page 7. Baseline Correction Method is not set to Linear. This warning indicates the settings for Baseline Correction Method was not set to Linear in the Fluidigm Real Time PCR software. See Change analysis settings and reanalyze on page 7. Some sample names were not unique This indicates that there are samples with identical names within the project. It is recommended that all samples within the project have unique names, e.g. by adding plate number and position to sample name. The following warnings can be displayed during analysis: Please note that you need to perform the NPX calculation again When adding or removing a Negative Control or IPC from the sample layout, this message will be displayed as a reminder to perform the NPX calculation again. No negative controls found on plate This indicates that no samples on the plate have been annotated as Negative Controls. Switch to the Plate View tab to assign the positions where the Negative Control samples are located. 34

35 Index Symbols %CV See Coefficient of Variance A ANOVA 11, 14, 27, 28 C Certificate of Analysis 3, 9, 12, 15, 16, 19 Coefficient of Variance 3, 11, 14 Control 9, 19 Control Normalization 26 D Data file 9 Detection Control 18, 21, 24, 25, 33 E Extension Control 18, 24 F Flagged s 16, 25 Fluidigm 3, 4, 9, 16, 34 Fluidigm Biomark runs 9 I Incubation Control 10, 18, 21, 24, 25 Intensity Normalization 16, 26 IPC 9, 19, 26, 34 IPC Normalization 16, 26 L Limit of Detection 12, 16, 19, 22 LOD See Limit of Detection N Negative Control 9, 19, 34 Normalization method 10, 14, 16, 26 Q QC See Quality Control Quality Control 10, 11, 14, 17, 21, 24, 25 S 9 Z Z-score 23 35

36 For research use only. Not for use in diagnostic procedures. This product includes a license for non-commercial use. Commercial users may require additional licenses. Please contact Olink Proteomics AB for details. There are no warranties, expressed or implied, which extend beyond this description. Olink Proteomics AB is not liable for property damage, personal injury, or economic loss caused by this product. Olink is a registered trademark of Olink Proteomics AB. Biomark and Fluidigm are trademarks of Fluidigm Corporation. Excel, Microsoft, Windows and.net are trademarks of Microsoft Corporation. Intel and Intel Core are trademarks of Intel Corporation or its subsidiaries in the U.S. and/or other countries Olink Proteomics AB. All third party trademarks are the property of their respective owners. 1078, v1.0, Olink Proteomics Dag Hammarskjölds v. 52B SE Uppsala, Sweden