GeneSpring - Overview and Biological Significance Quick Start Guide
Contents
1. e Figure 3 Toolbar Display Pane The display pane see Figure 1 on page 8 is further divided into six areas Project Navigator Displays the current project and lists all the experiments within the project Experiment Navigator Displays information related to Samples Interpretation Analysis and My Favorites in respective folders related to the selected experiment in the Project Navigator Each experiment within a project has a separate experiment navigator window Agilent GeneSpring Quick Start Guide Desktop Area Displays one or more interactive views associated with the experiments You can configure each view in the desktop area separately Window views can be arranged using Tile Cascade or Tabbed from the Window menu Right clicking anywhere in the active view shows you a menu of options Figure 4 to customize the view copy the view to the system clipboard or export the view in popular image html or text file formats as specified in Table 2 on page 12 Selection Mode Invert Selection Clear Selection Limit To Selection Copy View Print Export As Properties Ctrl C Ctrl P Ctrl Y k Ctrl R Select All Rows Invert Row Selection Clear Row Selection Limit To Row Selection Select Columns Invert Column Selection Clear Column Selection Freeze Columns Before Copy Copy View Ctrl C Print Ctrl P Export As 4 Properties Ctri R Figure 4 The right click options ava2. Project Search View Tools Annotations Windows Help Baa Fa BEA S ac He 8 188 X OS E Project Navigator i HeLa cells treated with compound X Demo Project x Experiments A manes Hj HeLa cells treated with compound X Quick Start Guide E HeLa flags N Experiment Grouping Hela cells treated with compound X 1 Create Interpretation 5 Samples Create New Geneevel 1522502205 251209747382 Untreated txt 152202705 251209747387 Untreated bxt i 1522502705 251209747394 Untreated txt T 0522502705 251209747392 Treated txt lI L 0522502705 251209747393 Treated txt E L us22502705_251209747404_Treated txt L i bem i 7 All Samples ud 4E Treatment Non averaged 8 Treatment E B Analysis 2 Ei X All Entities 1 1 Fitered Flags Detected Nat Detected Sige Experiment Andytis tiii Hierarchical Combined Tree on Treatment No F Sonificant genes that bind both Cadmium anc 5 Multi Omic Analysis 3E Entities similar to A 23 P37983 0 95 lt r lt Export to IPA 3 Fitered on Flags Detected Nat Detected 5 Import IPA Entity List 6 3 Fitered on Flags Detected Nat Detected Export to MetaCore H Fitered on Flags Detected Nat Detected S Fitered on Flags Detected Nat Detected Comect in Oiga E 3f p 0 05 B change gt 2 0 NLP Networks a gt XE
3. specific terms Table 1 GeneSpring specific terminology Term GeneSpring Definition Project Technology Sample Experiment Condition Interpretation A project is the primary workspace which allows analysis between experiments across different technologies and different organisms A technology refers to the microarray type that was used to generate the data For example Agilent Whole Genome and Affymetrix HG U133 PLUS 2 are two different array types Technologies in GeneSpring contain biological information about all the genes on a specific array type Install the appropriate technology for each new array type before you start analyzing data from that array Select the Analysis type depending on the technology used when creating an experiment see Setting up a project on page 15 A sample contains data from an array for a single biological source An experiment contains a group of samples used for a particular research study An experiment consists of multiple interpretations that group these samples by user defined conditions A condition consists of one or more samples that represent a common biological state For example if you have tumor tissues from three different patients these tissues describe the tumor condition A different set of healthy patient tissue samples accordingly represents the normal condition Multiple interpretations can be made from the same experiment data Interpr
4. Report workflow step a Follow the steps described in Setting up a project on page 15 to create a new project and experiment with the Agilent demonstration data set a Review the summary report Review This view depends on the number of b the data export selected data or export the plot to a file using clicking and right clicking features available on your summary report view Click Next gt gt samples in your data A spreadsheet is displayed if you have more than 30 samples A profile plot is displayed if you have 30 or fewer samples 26 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 3 Experiment Grouping Step 2 of 8 Enter the sample grouping with respect to the independent variables and the replicate structure of your experiment in the Experiment Grouping workflow step Click Add Parameter Type a name for your Parameter name in the Add Edit Experiment Parameter dialog box Figure 8 on page 28 Click your replicate Samples that share the first parameter value in your data Select the Parameter type for your grouping Click Assign Value Type the value for your first grouping in the Assign Value dialog box Click OK Click your replicate Samples that share the second parameter value in your data Select the Parameter type for your grouping Click Assign Value Type the value for your second grouping in the Assign Value dialog box
5. Gene Ontology GO category a Review your data change the view or export selected data from the spreadsheet or the visible area of the GO Tree through the available right click options Move the corrected p value cut off slider or type a value to change the p value cut off The default value is 0 1 Adjust the p value cut off until the results displayed are satisfactory to your experiment It is recommended that you adjust the p value cut off several times to develop an understanding of how it affects your results A larger p value passes a larger number of entities through to the final results Click Next gt gt when you have completed the GO Analysis The GO classification scheme allows you to categorize genes by biological process molecular function and cellular component Genespring provides two display options for your results Spreadsheet and GO Tree The Spreadsheet displays all entities satisfying the p value cut off sorted by corrected p value The GO Tree highlights all the GO terms with entities satisfying the p value cut off within the GO Tree hierarchical view Agilent GeneSpring Quick Start Guide 33 Steps Detailed Instructions Comments 9 Single Experiment Pathway Analysis Step 8 of 8 Review which of the entities retained following the Fold Change step have matching entities in pathways for your experiment organism Review your data or export selected data by clicking
6. UP FC ebs Untreated vs Tr 3 DOWN Fc abs IUntreated vs Utilities Y 2 Import Entity List From File Analysis Biol Signi US22502705 2512 822502705 US22502705 522502705 US22502705 15225027052 4 n resa Pam Fiter on Entity List All Samples Global Lists n Legend n My Lists 95 BoxWhisker Plot EB Spreadsheet legend BoxWhikerPlot Displaying 20227 0 selected Figure 11 GeneSpring screen after completing the Analysis Biological Significance workflow using the demonstration data set supplied by Agilent 11 Continue your analysis Perform custom analyses on your data using the operations available in the Workflow Browser Agilent GeneSpring Quick Start Guide 35 Where to find additional information Online help Documents 36 Press F1 To get more information about a menu toolbar window or dialog box place the cursor on the part of the menu toolbar window or dialog box of interest and press the F1 key Help menu Click Help Documentation Index to access the release notes quick start guides and HTML and PDF versions of the GeneSpring manual Online support portal Visit www genespring support com to contact the GeneSpring support team and access additional demo data sets user guides and video tutorials E seminars Visit our e seminar calendar to register for live seminars on available features in GeneSpring Ge
7. and PCA Visualize and compare data and analysis results with a variety of visualization options such as Genome Browser Profile Plots Scatter Plots MvA plots Box and Whisker plots Venn Diagrams and more Interpret your results in a biological context using Gene Ontology GO Analysis Gene Set Enrichment Analysis GSEA Gene Set Analysis GSA or Pathway Analysis Discover new interactions for your entities of interest from the latest published literature using a powerful natural language processing NLP algorithm Import pathway information from many sources and in different formats including native import from the WikiPathways online portal Perform multi omic pathway analysis to integrate your results from genomics transcriptomics proteomics and metabolomics experiments for one or multiple organisms Automate complex analysis tasks using scripts Export data images and analysis reports in standard file formats Overview of GeneSpring GX How do get started with Agilent GeneSpring GX After installation of GeneSpring GX you can get started immediately using the preloaded demonstration experiment The demonstration experiment allows you to familiarize yourself with the software functionality and workflow The project called Demo Project contains an experiment called HeLa cells treated with compound X This experiment consists of six samples of HeLa cells treated with an unknown compound in a can
8. values The Analysis Biological Significance guided workflow helps you identify differential expression in your data The sample exercise in this section of the quick start guide illustrates the steps in the workflow with the same Agilent demonstration data set that was used in Setting up a project on page 15 Following the import of your samples the Analysis Biological Significance workflow guides you through differential analyses between different conditions based on fold change and significance in eight steps Some steps are automatically skipped for your experiment depending on the experiment type experiment grouping and conditions you specify during experiment creation and Step 2 of this workflow 1 Summary Report Displays a summary view of your experiment A box and whisker plot representing the distribution of data in each of the imported samples is displayed If the number of samples is more than 30 GeneSpring displays your data in a spreadsheet view instead of the plot 2 Experiment Grouping Specify independent variables and the attribute values of the independent variables to define grouping of the samples An independent variable is referred to as a parameter name The attribute values within an independent variable are referred to as parameter values Samples with the same parameter values within a parameter name are treated as replicates 3 Quality Control on Samples Presents samples by grouping and the curr
9. 8 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 7 Select your data files and reorder Click Choose Files them if necessary in the Load Data part of the New Experiment dialog Load Data Click to choose either data files or samples to be used in this experiment Click finish when all data files or samples have been added Reorder Choose Samples b The Open dialog box will most likely already point to the samples folder in the main GeneSpring installation folder If not browse to C Program Files Agilent GeneSpring samples and then select the Agilent Expression Single Color Demo folder c Browse for the proper data file types based on your data source selection d Click the sample expression data files to import into the experiment The example HeLa cells data files are US22502705 251209747404 Treated US22502705 251209747393 Treated US22502705 251209747392 Treated US22502705 251209747394 Untreated US22502705 251209747387 Untreated US22502705 251209747382 Untreated This process to load data samples is common to all Workflow types Agilent GeneSpring Quick Start Guide 19 Steps Detailed Instructions Comments us22502705_251209747382_Untreated U522502705 251209747387 Untreated RecentItems us22502705_251209747393 Treated 4 EB Us22502705 251209747394 Untreated Desktop Us22502705 251209747404 Treated M
10. Agilent GeneSpring GX Software Overview and Biological Significance Analysis Quick Start Guide This quick start guide gives you an overview of the basic concepts of data analysis and terminology in the GeneSpring GX module of the GeneSpring suite of products It also introduces you to the main elements of the GeneSpring GX user interface The second section of this quick start guide illustrates data analysis in GeneSpring with a sample exercise This sample exercise takes you through the Analysis Biological Significance guided workflow for microarray data in GeneSpring GX The data used for this exercise is an Agilent Single Color Expression data set that is included in your software installation However the steps of this guided workflow are common to many of the other experiment and analysis types available in GeneSpring This quick start guide covers 1 Overview of GeneSpring GX 2 The Analysis Biological Significance guided workflow 3 Where to find additional information RE Agilent Technologies What is Agilent GeneSpring The Agilent GeneSpring suite of products provides powerful accessible tools for statistical analysis and effective visualization of genomics transcriptomics proteomics and metabolomics data The GeneSpring platform is specifically designed for scientists offering an interactive desktop computing environment to analyze and visualize data within a biological context GeneSpring helps scientists identify b
11. Click OK Repeat the value assignment steps until you have assigned a parameter name type and value to all of your samples Review your entries and grouping assignment accuracy in the Add Edit Experiment Parameter dialog box Repeat the value assignments for individual or multiple samples as necessary to make corrections or changes Click OK when the grouping for this parameter is complete To proceed to the next step assign at least one parameter with two values An independent variable is an essential element constituent attribute or quality in a data set that is deliberately controlled in an experiment An independent variable is referred to as a parameter and is assigned a parameter name The attribute values within an independent variable are referred to as parameter values Samples with the same parameter values within a parameter name are treated as replicates Assignment of parameter names and values to the parameters is a process called experiment grouping Parameter type Select Non numeric if the grouping is not based on a quantitative value Select Numeric if the grouping value is quantitative with respect to your parameter Agilent GeneSpring Quick Start Guide 2 Steps Detailed Instructions Comments gt ft Add Edit Experiment Parameter 72 Grouping of Samples Samples with the same parameter values are treated as replicate samples To assign replicate samples their parameter val
12. and right clicking features available To save a selection of the listed pathways select the desired pathways use Ctrl Click to select multiple pathways and click Custom Save Click Finish when you have completed the Single Experiment Pathway Analysis The result of Single Experiment Pathway Analysis is saved in the Experiment Navigator as a pathway list You can filter this list of pathways by p value and number of matching entities after completing this workflow The Single Experiment Pathway Analysis workflow step is only available if you have a license for the GeneSpring Pathway Architect module and you have imported pathways from the WikiPathways portal via Tools gt Import pathways from WikiPathways for the experiment organism before starting the Analysis Biological Significance workflow Single Experiment Pathway Analysis identifies matching entities between the entity list created as a result of Fold Change Analysis Step 5 and pathways for the experiment organism In this step GeneSpring also computes p values to establish the significance of the matching entities in a pathway 34 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 10 Review your results in the a Review your results the The Analysis Biological experiment that GeneSpring box and whisker plot Figure 11 Significance workflow is now creates on completion of the complete guided workflow
13. ays a profile plot of the remaining entities completed filtering the probeset Click Back if you want to adjust settings in a prior step in the workflow 30 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 6 Significance Analysis Step 5 of 8 Assess the differential significance of your samples from the Significance Analysis workflow step Review your data change the plot view export selected data or export the plot to a file by clicking and right clicking the features available Customize the window panes within the view Move the corrected p value cut off slider or type a value to change the p value cut off The default value is 0 05 Adjust the p value cut off until the results displayed are satisfactory to your experiment It is recommended that you adjust the p value cut off several times to develop an understanding of how it affects your results A larger p value passes a larger number of entities through to the final results The last row of data in the Result Summary shows the number of entities that is expected to pass significance analysis by chance for each p value specified in the column header If that number is much smaller than the number of entities expected to pass based on the corrected p value your selection of entities shows significance among the parameter values Highly recommended Click lt lt Back to adjust the settings in a prior step in the
14. cer screening program Three samples are treated biological replicates control and the other three are untreated biological replicates You are encouraged to explore this demonstration project to familiarize yourself with GeneSpring Basic concepts of data analysis and terminology This part of the quick start guide explains the basic concepts of data analysis and terminology in GeneSpring It also describes the main elements of the GeneSpring user interface Basic concepts In GeneSpring data is organized in terms of projects which can hold multiple experiments of different experiment and analysis types and differing organisms In addition to naming the projects and experiments you can also provide a short description of your project or experiment in the form of notes see Setting up a project on page 15 This combination of a name and descriptive notes allows you to get a quick view into your project or experiment when you return to it at a later date GeneSpring also uses the name and notes to find a particular project or experiment when you use the Search functionality 4 Agilent GeneSpring Quick Start Guide For creating experiments GeneSpring offers a choice of two workflow types 1 A guided workflow Analysis Biological Significance that Agilent GeneSpring Quick Start Guide provides data import and biological significance analysis of your data based on default parameter settings For data import GeneSpring pres
15. e Analysis 6 Fold Change 7 GO Analysis 8 Single Experiment An Experiment Grouping Experiment parameters define the grouping or replicate structure of your experiment To enter experiment parameters click Add Parameter You can enter as many parameters as you want but only the first two parameters are used for analysis in this Guided Workflow Other parameters can be used when analyzing your data with the features available from the Workflow Browser You can also edit and re order parameters and parameter values here Displaying 6 sample s with 1 experiment parameter s To change use the button controls below 3 NS E 8 0522502705 251209747382 Untreate Untreated US22502705_251209747387_Untreate Untreated US22502705 251209747394 Untreate Untreated US22502705 251209747392 Treated Treated US22502705 251209747393 Treated Treated US22502705 251209747404 Treated Treated Delete Parameter lt lt Back Next gt gt Finish cance Figure 9 Agilent demonstration data experiment grouping with one parameter and two parameter values per parameter a Review your data change the 3D PCA Scores plot view export selected data or export the plots to a file through clicking and right clicking features available Good quality samples form discrete groups in the 3D PCA Scores view based on their parameter assi
16. elects the most appropriate parameters for your experiment type These parameters are predefined and you cannot modify them You can review these settings by inspecting the experiment after it is created During the guided analysis steps you are able to modify some of the preselected parameters for example p value cut off or flag filters On completion of the workflow GeneSpring creates an experiment with all the workflow results You can now continue your analysis by choosing any of the advanced quality control filtering analysis and biological interpretation steps from the Workflow Browser This guided workflow option is described in detail in this quick start guide from page 24 onwards A data import only option Data Import Wizard This option is only recommended if you have advanced knowledge of the data import options in GeneSpring It allows you to adjust flag settings as well as data alignment and normalization parameters for importing your data No further analysis steps are performed automatically like in the guided workflow GeneSpring immediately creates the experiment using your inputs You can then select the appropriate experiment grouping quality control filtering analysis and biological interpretation steps from the Workflow Browser Terminology Some terms commonly used in the general biological research community have a more specialized use in GeneSpring The following table explains the most important GeneSpring
17. ent Principal Component Analysis PCA PCA calculates all the possible principal components and visually represents them in a 3D scatter plot The scores shown by the scales of the axes are used to check data quality The scatter plot shows one point Agilent GeneSpring Quick Start Guide per sample color coded by the experiment grouping Additional quality metrics present in the imported feature extraction data files are displayed as a table and line plot 4 Filter Probesets Filtered removes entities from further analysis based on the presence of certain flag values across samples and parameter values now referred to as a condition In the absence of flags entities are filtered based on signal intensity 5 Significance Analysis The entities are filtered based on their p values calculated from a statistical analysis The statistical analysis performed depends on the samples and experiment grouping 6 Fold Change Filters entities based on their abundance ratios or differences between a treatment and a control that are greater than a specified cut off or threshold value 7 GO Analysis Finds enriched Gene Ontology terms for entities in the entity list resulting from Step 6 8 Single Experiment Pathway Analysis This is the last step in the guided workflow It identifies matching entities between the entity list resulting from Step 5 and previously downloaded pathways for the experiment organism Before creating your experim
18. ent with the guided workflow select Tools Import Pathways from WikiPathways from the main menu to download pathways for the experiment organism from WikiPathways You require a license for the Pathway Architect module to perform this last step If you do not have a license or do not want to download the required pathways follow the workflow until Step 7 and click Finish to complete the guided workflow The Analysis Biological Significance workflow allows you to proceed through each step by clicking Next gt gt A summary of your analysis is presented in each subsequent step After Agilent GeneSpring Quick Start Guide 25 Sample exercise reviewing your analysis progress you can return to a previous step and change the analysis parameters by clicking lt lt Back Frequently use the lt lt Back and Next gt gt options to become more familiar with the analysis parameters and how the parameters affect your data To exit the wizard and skip the later steps in the wizard click Finish at any step When you click Finish the All Entities entity list and all the entity lists resulting from the analysis steps performed so far are saved in the Experiment Navigator You can now continue your analysis using the advanced operations available in the Workflow Browser Steps Detailed Instructions Comments 1 Start GeneSpring and create a new project and experiment 2 Summary Report Step 1 of 8 Review your data in the Summary
19. etations group samples into different conditions if applicable to the study and therefore allow alternative analysis approaches Agilent GeneSpring Quick Start Guide Table 1 GeneSpring specific terminology Term GeneSpring Definition Entity An entity is a discrete feature measured by microarray analysis such as a probe probeset gene or protein The term entity used in this guide appears infrequently in GeneSpring itself GeneSpring features context sensitive terminologies for lists pathways and trees Therefore the term entity in this guide represents any one of eight possible entity types displayed in GeneSpring Exon Feature Gene Probe Probe Set Protein Splice Event 8 Transcript Probe A probe is a discrete feature on a microarray used to capture biological measurements A probe can be an oligonucleotide or cDNA complimentary to a region of genomic DNA or a protein which interacts with other proteins Agilent GeneSpring Quick Start Guide User Interface Main functional areas The main functional areas of GeneSpring are shown in Figure 1 Gen p ng GX MPP NGS PA Hela cells treated with compound X Seas Project Search View Tools Annotations Windows Help PLAS EX EXEC IE Experiments Hj HeLa cells treated with compound X Experiment Setup I Quick Start Guide i HeLa cells treated with compound X l ix Experiment Groupi
20. for the experiment in Experiment name This name can be different from the name previously entered for the project b Select Expression for Analysis type Select Agilent Expression Single Color for Experiment type Select Analysis Biological Significance for Workflow type You can also access the Analysis Biological Significance workflow from the Utilities section of the Workflow Browser in any open experiment that supports the guided workflow The Workflow type Data Import Wizard is only recommended for those with advanced knowledge of data import settings in GeneSpring e lypeAgilent demonstration data in Experiment notes New Experiment Experiment description Enter a name analysis type experiment type and a desired workflow type Analysis will guide you through a statistical significance test and fold change analysis Data Import will guide you through experiment creation only Class Prediction will guide you through the creation and testing of a prediction model using imported training data Experiment name HeLa cells treatment Analysis type Expression Experiment type Agilent Expression Single Color Workflow type Analysis Biological Significance Experiment notes Agilent demonstration data f Click OK Your new project is now set up You are immediately guided through importing your data files in the Load Data part of the New Experiment dialog 1
21. gilent GeneSpring samples Agilent Expression Single Color Demo You can substitute the demo information with information for your data Steps Detailed Instructions Comments 1 Start GeneSpring a Double click the GeneSpring shortcut This opens the Startup dialog box icon Re on your desktop or click Start gt All Programs gt Agilent gt GeneSpring gt GeneSpring Agilent GeneSpring Quick Start Guide 15 Steps Detailed Instructions Comments 2 Create a new project in the a Select Create new project Create new project allows you to Startup dialog box b Click OK create a new project and new experiments or import existing Startup mm experiments into the new project S Welcome to GeneSpring Select what you would like to do from the options below then dick on OK to continue Options Ereate new project Open existing project Open recent project Select recent project Demo Project E Do not show this dialog again LE 3 Alternatively if you have already a Close the open project n GeneSpring only one project can been working in GeneSpring b Create a new project from the be open at any given time create a new project via the main main menu by selecting menu or the toolbar Project gt New Project or Toolbar by clicking the New project icon E 4 Type the descriptive information a TypeAgilent Demo Projectin You can view and edit the projec
22. gnments Highly recommended click Back to adjust settings in a prior step in the workflow to improve the QC on samples results Click Next gt gt when you have completed the QC on samples QC on samples provides you with the first view of the data using a Principal Component Analysis PCA PCA allows you to assess the data by viewing a 3D scatter plot of the calculated principle components The Quality Control Metrics plot and report produced for this demo experiment are specific to Agilent Feature Extraction data files If you used a different technology to generate your data this plot and spreadsheet tab vary according to the QC related information present in your data files Agilent GeneSpring Quick Start Guide 29 Steps Detailed Instructions Comments 5 Filter Probesets Step 4 of 8 Select values that filter entities in your samples based on the quality of their presence in specified samples and conditions in the Filter Probesets workflow step a Review your data change the plot view export selected data or export the plot to a file by clicking and right clicking features available on the plots b Click Re run Filter to select acceptable flags in the Filter Parameters dialog box Figure 10 Ex Filter Parameters Acceptable Flags V Detected V Not Detected E Compromised Figure 10 box c Select the Detected and Not Detected options under Acceptable Flags d Un
23. he selected sample or samples Repeat the reordering steps as often as necessary to obtain your order Click OK Select a continuous range of files with a click on a first file and a Shift click on a last file that includes the range of files you want to select To select multiple samples that do not appear in sequence Ctrl click any sample name 22 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments k Click OK in the New Experiment Load Data dialog box in step f on page 21 What happens next depends on the workflow type that you chose in the New Experiment dialog box on page 18 Analysis Biological Significance GeneSpring immediately launches the wizard driven guided workflow GeneSpring imports thresholds aligns and normalizes your data in the background based on a number of default settings The steps of the workflow are described in Analysis Biological Significance guided workflow on page 24 Data Import Wizard The New Experiment dialog continues after sample import is complete In the remaining steps you can determine the flag settings alignment and normalization parameters for your data Agilent GeneSpring Quick Start Guide 23 Analysis Biological Significance guided workflow 24 In GeneSpring independent variables are referred to as parameter names Attribute values within an independent variable are referred to as parameter
24. ilable on plots or spreadsheets Agilent GeneSpring Quick Start Guide 11 12 Table 2 File export options for active views the desktop area Image HTML Text jpg html txt png tsv beg bmp tiff Legend The Legend Figure 5 shows the key scale to the use of color in the active desktop view Right click the window title to copy and export the legend as described in the desktop area description Legend n Legend Profile Plot Color By 522502705 251209747382 LUntreated txt gProcessedsignal aame 4 0 11 8 Description Launched on interpretation All Samples Figure 5 Legend Workflow Browser The Workflow Browser Figure 6 on page 13 is organized into sequential groups of operations for the analysis of your data Experiment Setup Quality Control Analysis Class Prediction Results Interpretations Pathway Analysis optional NLP Networks optional Utilities Agilent GeneSpring Quick Start Guide Single Experiment Analysis Multi Omic Analysis Export to IPA Import IPA Entity List Export to MetaCore Figure 6 Agilent GeneSpring Quick Start Guide Workflow Browser 13 14 Global Lists The Global Lists folder holds entity lists that you want to be able to use across different projects rather than just in their original project Status The status bar Figure 7 has three informative areas Status Area Displays high level informat
25. iological entities such as genes proteins and cellular pathways that are significant to a biological hypothesis The following four modules are available for GeneSpring GeneSpring GX for data from microarray technologies GeneSpring NGS for data from next generation sequencing platforms Mass Profiler Professional for mass spectrometry data Pathway Architect to perform pathway and network analysis across data types and organisms With GeneSpring you can Normalize experimental data using various methods like percentile shift normalization quantile normalization or Lowess normalization Easily create experiments that link trends in data to various test parameters Therefore GeneSpring allows you to test complex hypotheses by running previously defined analyses against different combinations of samples Assess data quality across samples using correlation analysis and Principal Components Analysis PCA and filter out bad quality data Identify biologically significant entities using powerful statistical algorithms such as t test ANOVA multiple testing corrections false discovery rate prediction Tukey and Student Newman Keuls post hoc tests Agilent GeneSpring Quick Start Guide Agilent GeneSpring Quick Start Guide Find similarities across entities and conditions with clustering algorithms and visualization techniques such as hierarchical clustering K means clustering Self Organizing Map SOM
26. ion of the current view For example the number of rows and columns in table views and the number of entities or conditions selected in plot views Ticker Area Displays the coordinates of the cursor in active plot views or the entity identification and value in table views Memory Monitor Displays the total memory being used and the total memory allocated by GeneSpring You can click the garbage can icon at any time to reduce memory usage I Status Area Ticker Area Displaying 20227 0 selected 2 22 US22502705_251209747392_Treated txt gProcessedSignal 86M of 95M Memory Monitor Figure 7 Status Bar Agilent GeneSpring Quick Start Guide Setting up a project GeneSpring guides you through four steps to create a new project and experiment to receive imported data 1 Startup Select creation of a new project 2 Create New Project Type descriptive information about the project 3 Experiment Selection Select Create new experiment as part of the project 4 New Experiment Type and select custom information to store with the experiment and import your data files Follow the steps described in this section to set up your new project The Agilent Expression Single Color demo data set is used to illustrate each step The sample files you need are located in the samples folder of the main installation folder If you did not specify another folder during installation the location is C Program Files A
27. ll Samples _ se lt 5 SE Legend 1 l My Lists 4 1 Displaying 20227 0 selected 99M of 157M Figure 1 The main functional areas of the GeneSpring software 4 11 8 l The main GeneSpring window consists of four parts Menu Bar Toolbar Display Pane Status Bar 8 Agilent GeneSpring Quick Start Guide Menu The menu bar shown in Figure 2 provides actions that are used for managing your projects experiments pathways and display pane views Project Search View Tools Annotations Windows Help Figure 2 Menu Bar Toolbar The toolbar shown in Figure 3 on page 10 is located below the menu bar and contains four sections of icons providing fast access the following commonly used tasks Project section New project Open project and Close project Experiment section New experiment and Add experiment Entity List section Create entity list from selection Inspect selected entity and Import entity list from file Views section Scatter Plot shows a 2 D scatter of all entities in a selected entity list along the first two conditions of the active interpretation MvA Plot plots the difference of probe measurements between two samples against the average as a scatter plot Profile Plot plots normalized expression values against the selected interpretation Histogram shows the frequency or number of entities across equal intervals of the normalized signal va
28. lues for the first condition in the selected interpretation Matrix Plot shows a matrix of pairwise 2 D scatter plots for conditions in the selected interpretation Venn Diagram illustrates commonalities between entity lists or pathway lists in or across experiments Agilent GeneSpring Quick Start Guide 9 10 Box and Whisker represents the distribution of the conditions in the selected interpretation with respect to the selected entity list in the experiment Heatmap visualizes the normalized signal values for all the entities in the selected entity list by the conditions in the active interpretation using a color range Spreadsheet presents a tabular view of your data Summary Statistics presents a summary of common statistical measurements for example mean standard deviation etc for the selected entity list grouped by the conditions in the selected interpretation Create new Pathway opens a new view with options to create your own interaction network or pathway Launch Genome Browser visualizes entities in a selected entity list against the reference genome for the experiment organism Hide Sidebars hides the Project and Experiment Navigator Global Lists Workflow Browser and Legend and extends the Desktop Area to occupy the entire GeneSpring window Project Experiment Entity List Views Plots Statistics Pathways BBe Se Babe SHR S88 ee HRA
29. nal value For example when an entity changes from a value of 60 to a conditions sign color coded red for positive and value of 15 the fold change is 4 blue for negative fold change by The quantity experienced a default four fold decrease Fold change is Move the Fold change cut off slider or the ratio of the final value to the type a value to change the Fold initial value change cut off The default value is Fold change analysis is used to 2 0 identify entities with abundance Adjust the Fold change cut off until ratios that are in excess of a the results displayed are satisfactory specified cut off or threshold value to your experiment Fold change is calculated between It is recommended that you adjust two conditions where Condition 1 the Fold change cut off several and another condition Condition 2 times to develop an understanding are treated as a single group of how the Fold change cut off affects your results A larger Fold change cut off passes a smaller number of entities through to the final results Highly recommended click Back to adjust the settings in a prior step in the workflow to improve the Fold Change results Click Next gt gt when you have completed the Fold Change step 32 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 8 GO Analysis Step 7 of 8 Assess which of the entities retained following the Fold Change step show significance for a particular
30. neSpring manual Agilent GeneSpring User Manual Agilent publication n a August 2012 Agilent GeneSpring Quick Start Guide References 1 Pico AR Kelder T van Iersel MP Hanspers Conklin BR Evelo C 2008 WikiPathways Pathway Editing for the People PLoS Biol 6 7 Agilent GeneSpring Quick Start Guide 37 www agilent com In this guide This guide gives you an overview of the GeneSpring GX module of the GeneSpring suite of products It also describes the Analysis Biological Significance guided workflow for microarray data Agilent Technologies Inc 2012 Printed in United States of America 10 2012 G9220 90002 a Agilent Technologies
31. ng o Samples Create Interpretation us22502705_251209747382_Untreated txt Create New Gene devel Exp 0522502705 251209747387 ntes i Workflow Browser us22502705 251209747394 Untrd 1 Twp MANT l us22502705_251209747392_Treat Project Navigator Quality Control Y I 0522502705 251209747393 Treated txt Quality Control on Samples e US22502705 251209747404 Treated txt Filter Probesets by Expression loa f AN Filter Probesets by Flags E mi Filter Probesets on Data Files I 4X Treatment 3 Filter Probesets by Error I c1 y Analysis gt a I Filtered on Flags Detected Not Dected c 3E T test lt 0 05 5 8 Fold change gt 2 0 3E ue FC ebs Untreated vs I Neted s o 3E DOWN FC abs Untreated vs INeated E 5 GO Analysis p molecular gt S E cadmium o SEA cadmium ion binding 3E copper ion binding a amp C cellular_component biological process Z 49 4 k means on Treatment 5 Legend a _ E RE Fold change gt 5 0 Legend Profie l I cf Hierarchical Combined Tree on Treatment Non averaged Color By US22502705_251209747382_U lf l 3 Significant genes that bind both Cadmium and Copper US2250270 US22502705 US22502705 US22502705 US22502705 0522502705 E 3E Entities similar to A_23_P37983 0 95 lt r lt 1 0 8 C3 Favorites All Samples CEciption I Global Lists a Launched on interpretation A
32. select Compromised under Acceptable Flags This flag is useful when you want to identify entities that are missing in the samples Click OK f The number of entities displayed above the profile plot is expected to decrease in value as you progress through the workflow Review the profile plot You are encouraged to repeat these Re run Filter steps until you obtain the best results for your experiment g Click Next gt gt when you have Filter Parameters dialog If flags are detected in your data Filter Probesets filters your data based on flags If at least one of the imported samples has acceptable values GeneSpring retains entities that have either a Detected or Not Detected flag value by default A flag is a term used to denote the quality of an entity within a sample For Agilent microarray technologies a flag indicates whether the entity was detected in each sample as follows Detected the entity was detected Compromised the entity was not detected and Not Detected the signal for the entity was saturated For non Agilent technologies a flag indicates whether the entity was detected in each sample as follows Present the entity was detected Absent the entity was not detected and Marginal the signal for the entity was saturated Inthe absence of flags your data is filtered based on signal intensity values By default the filter removes entities in the lowest 20 percentile and displ
33. t in the New Project Details area Name name and notes in the Project of the Create New Project dialog b Type Project containing the Inspector at any time Click Project box Agilent HeLa cells demo gt Inspect Project from the menu experiment in Notes bar to open the inspector c Click OK 16 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments Create New Project New Project Details Name Agilent Demo Project Notes Project containing the Agilent HeLa cells demo experiment 5 Select the option to create Select Create new experiment f you select Open existing experiment in the Choose b Click OK experiment you can select an Experiment area of the existing experiment to be added to Experiment Selection Dialog the new project dialog box Alternatively you can create a new experiment to add to an existing open project as follows From the main menu select Choose whether you would like to be guided through Project gt New Experiment or the creation of a new experiment or if you would like to in the toolbar click open an existing experiment from a previous project the New experim ent icon E Open existing experiment Agilent GeneSpring Quick Start Guide 17 Detailed Instructions Comments 6 Type and select information that guides the experiment creation in the New Experiment dialog Type the descriptive name HeLa cells treatment
34. ues select the samples and dick on the Assign Values button and enter the value for the group Set the Parameter type to numeric to interpret the parameter values as numbers Parameter name Treatment Parameter type Non Numeric z Samples Parameter Values 522502705 251209747382 Untreated txt Untreated 522502705 251209747387 Untreated txt Untreated 22502705 251209747394 Untreated txt Untreated US22502705 251209747392 Treated xt US22502705_251209747393_Treated txt US22502705 251209747404 Treated txt Assign Value Enter a value for the selected samples Treated Assign Value o Figure 8 Add Edit Experiment Parameter and Assign Value dialog box q If your data has more than one independent variable repeat the Add Parameter steps The experiment grouping for the Agilent demonstration data is shown in Figure 9 on page 29 r Click Next gt gt when you have completed the experiment grouping Click lt lt Back if you want to adjust settings in a prior step in the workflow 28 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments 4 QC on samples Step 3 of 8 Assess the sample quality of your experiment using the 0 on samples workflow step 5 Workflow Analysis Biological Significance Step 2 of 8 4 Steps 1 Summary Report 3 QC on samples 4 Filter Probesets 5 Significanc
35. workflow to improve the Significance Analysis results Click Next gt gt when you have completed the Significance Analysis Significance Analysis filters the entities based on their p values calculated from statistical analysis The statistical analysis is either a T test or an Analysis of Variance ANOVA based on the samples and experiment grouping f any parameter value is associated with only one sample p values cannot be calculated and the Significance Analysis step is not displayed Volcano Plot Display of the Volcano Plot or other plot depends on the samples and experiment grouping for analysis Entities that satisfy the p value cut off appear in red color and the remaining entities appear in gray color The Volcano Plot draws negative log10 of the p value vs log of the fold change Probesets with large fold change and low p value can easily be identified on this view Agilent GeneSpring Quick Start Guide 31 Steps Detailed Instructions Comments 7 Fold Change Step 6 of 8 Enter values that filter the remaining entities in your samples based on their relative abundance ratios among the samples and a Review your data change the plot view export selected data or export the plot to a file by clicking and right clicking features available The fold change values for each entity are Fold change is a signed value that describes how much an entity changes from its initial to its fi
36. y Documents Intreated US22502705_25 TXT files txt e Click Open to load the selected files for progress indicator is displayed further preparation while the files are being imported into GeneSpring 20 Agilent GeneSpring Quick Start Guide Steps Detailed Instructions Comments f Ifthe samples do not appear in the NOTE This step represents the only required order click Reorder opportunity to reorder your samples If you want your samples to appear in a different order after you completed this step you have to create a new experiment Click to choose either data files or samples to be used in this experiment Click finish when all data files or samples have been added Type Selected files and samples 522502705 251209747382 Untreated txt 522502705 251209747387 Untreated txt J522502705 251209747392 Treated txt 22502705 251209747393 Treated txt J522502705 251209747384 Untreated txt 22502705 251209747404 Treated txt Choose Samples Reorder Remove Agilent GeneSpring Quick Start Guide 21 Steps Detailed Instructions Comments US22502705 251209747382 Untreated txt 0522502705 251209747387 Untreated txt 0522502705 251209747392 Treated txt 0522502705 251209747393 Treated txt Click one or more samples that you want to reorder in the Reorder Samples dialog box Click jorDown buttons to reorder t
Download Pdf Manuals
Related Search