Core, Tox and Metabolomics Analyses

What does it mean to "Run an Analysis"?

Analyses in IPA return the following:
  • Signaling and metabolic pathways expected to be impacted by molecules in the uploaded data
  • Upstream molecules predicted to be activated or inhibited based on the pattern of expression changes in your dataset*
  • ​Diseases and biological functions predicted to be increased or decreased^
  • Regulator Effects which finds upstream regulators predicted to drive outcomes on downstream diseases and functions
  • (Optional) Networks of interactions among the uploaded molecules as well as additional molecules from the QIAGEN Knowledge Base
  • (Optional) Overlap of the dataset molecules with My Lists or My Pathways that you may have created
 
*Activation or inhibition z-scores for upstream molecules are only computed for expression data uploaded as Expr Fold change, Expr Ratio, Expr Log Ratio, or Expr Other.
^Increase or decrease z-scores require a "directional" measurement type in your dataset, where some molecules are considered increased in activity in your dataset and some decreasing, for example Expr Fold change, Phospho Log Ratio, or Variant Loss/Gain.
 

Analysis Type

Description

Identifiers Supported

Order of Top Results in
Analysis Summary

Molecules added from the Ingenuity Knowledge Base

Available for Comparison Analysis

Core

Rapid assessment of the signaling and metabolic pathways, upstream regulators, molecular networks, and disease and biological functions that are most likely to be perturbed in the dataset of interest.

Gene/Protein

Analysis Settings
Canonical Pathways

Upstream Regulators
Diseases and Bio Functions
Tox Functions
Regulator Effects Networks
Networks
Tox Lists
My Lists
My Pathways
​Analysis-ready Molecules

Genes (automatic)

Endogenous Chemicals (if selected)

Yes

Tox

Assess toxicity and safety of compounds.

Understand the relevant toxicity phenotypes and clinical pathology endpoints associated with a dataset.

Gene/Protein

Analysis Settings
Tox Functions
Tox Lists

Canonical Pathways
Upstream Regulators
Diseases and Bio Functions
Regulator Effects Networks
Networks
My Lists
My Pathways
​Analysis-ready Molecules

Genes (automatic)

Endogenous Chemicals (if selected)

Yes

Metabolomics

Overcomes the metabolomics data analysis challenge by providing the critical context necessary to gain biological insight into cell physiology and metabolism from metabolite data.

Chemical

Analysis Settings
Canonical Pathways

Diseases and Bio Functions
Tox Functions
Networks
Tox Lists
My Lists
My Pathways
​Analysis-ready Moleculess

Endogenous Chemicals (automatic)

Genes (if selected)

Yes

 

How to Create an Analysis

1)  To start a Core Analysis, click File > New > Core Analysis.  To start a Metabolomics Analysis, click File > New > Metabolomics Analysis. To start a Tox Analysis, click File > New > Tox Analysis.
 
2)  Select the dataset you wish to analyze. You may either upload a new dataset from your computer or select a previously uploaded dataset.
 
For an existing dataset, select the dataset, click the Next button, and skip to Step 4.
 
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3)  To upload a new dataset: 
 
Note: For more information on uploading datasets, click here.
 
a)  Specify the file format, identifier type, and other details.
 
b)  Identify the ID column, Observation column(s) and expression type(s). 
 
c)  Click the Save & Create Analysis button.
 
A Save Dataset dialog appears:
 
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d)  Choose an existing project from the dropdown menu or click New to create a New Project in which to store your dataset file.
 
e)  Name your dataset, and (optional) add notes.
 
f)  Click the Save button.
 
The Create Analysis window opens:
 
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4)  In the Create Analysis window, you can specify a variety of parameters to apply to your analysis. Set the Filters and General Settings for Analysis.
 
General Settings:  
 
Reference Set specifies which molecule set (Reference Set) should be viewed as the complete universe of possible molecules when computing statistical significance in the analysis. For very small datasets, for example a PCR array or other panel, select the user dataset as the reference set. In such a case, the entire panel should be uploaded, and then a cutoff set to analyze the perturbed subset of the panel.

Relationships to consider 
  • Direct and Indirect Relationships: Uses findings that refer to both direct and indirect relationships between molecules. Direct relationships are physical interaction between two molecules, such as between a kinase and its known substrate. Indirect relationships are effects that may occur through intermediates such as the relationship between a chemical and a gene whose expression is induced by it downstream. 
  • Direct Relationships Uses only findings about direct physical interactions between molecules, for example between a drug and its protein target.
For Core and Tox Analyses:  You can specify whether you want endogenous chemicals (metabolites) to be included in your networks. When endogenous chemicals are included, the network analysis will also include relevant specific metabolic reactions involving input/focus chemical or enzyme (group) molecules.
 
For Metabolomics Analyses:  You can specify whether you want genes also included in your networks. For example, running an analysis with a list of metabolites will return networks that indicate reactions that convert between the metabolites, enzymes that catalyze those reactions, and other regulators.
 
Networks: Network generation is optional in IPA. If you choose to generate interaction networks, you can choose the types of interactions (direct and/or indirect) you would like to include in your network analysis. For more information, click here.
Network Size: The network size can be customized to 35, 70, or 140 nodes per network. (Resetting this parameter will change the networks generated not only in size, but also in the actual molecules that are included within the networks.)
Number of Networks: The number of networks generated can also be customized. IPA can display 10, 25, or 50 networks. 
 

Nodes Per Network

 Number of Networks

35

10, 25 (default), 50

70

10 (default), 25

140

10 (default), 25

Optional Analyses:
 
My Pathways: IPA will run an analysis against any custom pathways you have saved and approved. For more information, click here.
My List Analysis: IPA will run an analysis against any custom Lists you have saved.  For more information, click here.

 
Filters can be applied to the analysis:
  • Data Source enables you to choose which curated data sources (used for findings) you would like to include for your analysis
  • Node types enables you to choose what types of nodes are used to create various types of networks in the analysis, and is often used to eliminate groups and complexes from networks.
  • Confidence enables you to include lower confidence microRNA to mRNA targeting relationships from TargetScan.
  • Species enables you to choose which species you would like to include for your analysis. For example, if a Mouse-Stringent filter is chosen, then all networks in the resulting analysis will contain only orthologs that include Mouse and all relationships will involve Mouse molecules.
  • Tissue and Cell Lines enables you to choose which tissue types and cell lines you would like to include for your analysis.
  • Mutations enables you to fine tune the analysis to remove particular classes of findings based on mutations if desired.
5)  If you have more than one observation in your dataset file, you have the option to run all of the observations or a subset of them. To specify which observations to run an analysis on, click the Advanced button.
 
6)  Specify one or more Measurement Value Cutoffs. This cutoff value determines which molecules are included in the analysis. For example, you might only be interested in molecules with a p-value of 0.05 or less; here, you would enter 0.05 into the p-value cutoff field.
 
In situations where you have multiple measurement value types associated with molecules, a cutoff may be specified for each. In such cases, molecules meet ALL cutoff criteria that have been set in order to be eligible for the analysis.
 
Focus On: This parameter allows you to limit your analysis to Up-regulated, Down-regulated, or Up- and Down-regulated molecules. Use the pull-down menu to select. Note that z-score calculations in IPA expect both up and down-regulated molecules, so we advise you to use the default "both" option when evaluating the resulting z-scores.
 
Advanced Settings: The advanced settings allows you more options to customize your analysis.  To set your advanced settings, click the Advanced button. 
 
Resolve Duplicates: If a dataset contains more than one identifier for the same molecule, the identifier with the highest measurement Value (lowest when the Expression Value is a p-value), by default, is used in the analysis. When there are multiple Expression Value types, you can determine which type should be used to resolve duplicates. In the absence of Expression Values, the first instance of the molecule is used in the analysis.
 
You can also select how the application should resolve duplicate identifiers in your dataset file. Select the Expression Value type and the preferred value (maximum, average, median or minimum) to be used in the analysis if the dataset contains duplicate identifiers for the same molecule. For example, if you choose Fold Change and Maximum for this parameter, then the identifier with the highest fold change value (absolute value) will be used for the analysis. For Ratio and Fold Change expression values, Minimum and Maximum refer to the lowest and highest magnitudes, respectively (absolute values), and the application uses Maximum as the default setting. For p-values, the application defaults to the Minimum setting.
 
Color Molecules: You can also select the preferred Expression Value type to use color the node that graphically represent the molecules. Node colors signify the up or downregulation of Network Eligible molecules in Network Explorer. The default view displays upregulated nodes as red and downregulated nodes as green. Please note that if the Expression Value type is a p-value or Intensity, then the expression values are always positive (p-values: between 0 and 1; Intensity: between 0 and ?), so all nodes will have a single base color (default color: red).
 
Recalculate: Use the Recalculate button after setting your analysis parameters to see the number of Eligible molecules you have for your analysis. For networks, we suggest that for the best results, you should have < 3000, preferably closer to 1000-2000. This ensures that IPA is not analyzing noise in your dataset. If you have >3000 molecules eligible for analysis, try increasing the stringency of your cutoff values.
 
We suggest that before running the analysis, you review the mapped molecules. If you have multiple observations, you can view each in the table by selecting them from the Observation dropdown menu.
 
7)  Run the Analysis. Once you are satisfied with your analysis parameters, click the Run Analysis button. You will automatically be taken back to the Project Manager window. In the Project Manager window, the new analysis will appear in the Analyses folder. If it is still running, it will be shown with a spinning icon. Once it has completed, the spinner will disappear and the analysis name will be in bold type. 
 
Note: Running an analysis may take up to 30 min to complete, but is generally down in just a few minutes. This depends on the number of analysis-ready molecules and whether you opted to generate interaction networks. When the analysis is complete, you will receive an email informing you.
 
8)  To open your complete Core Analysis, double-click the file name in the Project Manager. Once open, the Analysis Summary page appears. This page contains the most statistically significant results from the analysis
 
9)  If you have multiple datasets that represent multiple timepoints or dosage treatments, use Comparison Analysis to understand which biological processes and/or diseases are relevant to each timepoint or dose. To start a Comparison Analysis, select New Core, Tox Or Metabolomics Comparison Analysis from the right click menu.
 
10)  Select and add the Core Analysis results to the Analyses to Compare box by clicking the Add >> button.
 
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11)  Click View Comparison to display the results of the Comparison Analysis. 
 
12)  To save your results to the Project Manager, click the Save & Exit button at the bottom of the window.