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Competitor of Ingenuity, offers manually curated pathways and networks, the tools to analyze those groups in the context of various experiments and powerful network building methods.
Owned by Thomson Reuters
Major Applications:
Access to manually curated databases
Evaluation of pathways, networks, annotations and associations as they relate gene lists. These gene lists could be deferentially expressed genes or any other list of genes.
Construction of networks based on gene lists using a database of interactions.
GeneGO ontologies
Pathway Maps
Process Networks
GO Processes
Disease (by Biomarkers)
Metabolic Networks
High quality documentation is available by following Help -> Help
A link to example data is below. xls files are required, open both and examine the data.
Key structure is:
Identifier FoldChange pvalueNOTE: Raw gene list of genes of interest works fine as well.
From the Start Page, there are 3 ways to access data loading tool:
File-->Upload Data...
Upload Data icon
Upload Page-->Upload Experiments with Gene or Protein IDs
NOTES: Tools emphasize the Activate/Deactivate/Reload requirements.
Choose the file ColonMet_Faked.xls and click Next
Adjust data types as needed. Rename columns and experiments as necessary. Make sure that fold changes and supporting p-value columns are adjacent to each other. Click Next
Specify the species and click Next.
The Background processing status page will indicate when upload is complete. Once processed, the line can be deleted from the table.
Return to the Background processing page from the start page by File-->Background processing item.
Activate only the ColonMet_Faked experiment and select appropriate thresholds.
From the Start Page, select the One-click Analysis button and pick the Pathway Maps tool
Analysis will consider only the Pathway maps
It can be run on multiple experiments as well.
Activate only the ColonMet_Faked experiment and select appropriate thresholds.
From the Start Page, select the One-click Analysis button and pick the Map Folders tool
Analysis will consider functionally related Pathway Map groups resulting in alteration of scoring and statistics.
It can be run on multiple experiments as well.
Clicking on a result folder leads to a results page displaying data for the composite Pathway Maps
Activate only the ColonMet_Faked experiment and select appropriate thresholds.
From the Start Page, select the One-click Analysis button and pick the Process Networks tool
Analysis will consider enrichment in various annotated process networks.
It can be run on multiple experiments as well.
Clicking on a result leads to a page displaying data for the indicated Process Network.
Run a Compare Experiments workflow for ColonMet_Faked_FC and ColonMet_Faked_FCrand1_edit.
Identify and select the common network objects in this comparison (10 Network objects) by clicked the blue/white histogram.
Click Analyze networks to produce a list of networks associated with the list.
Return to the Network options page and click Add network objects and add ITGA5.
Re-run Analyze Networks, using default settings. NOTE: Adding ITGA5 produces and additional network.
There 11 different network building algorithms available.
Clicking on network name opens the highly interactive network viewer. Explore the extensive control over the visualization.
From the Start Page, select the Search and Browse Content link and pick the EZ search button
Click human FN1 from the results list
Results page is outlined according to category, available information includes pathway maps and interactions.
Under interactions page, compare the details for alpha2/beta1 binding and alpha5/beta1 binding.
From the Start Page, select the Search and Browse Content link and pick the Pathway Maps option.
This leads to a hierarchy of GeneGO pathway maps
Select Regulatory maps-->Regulation of cellular processes-->Cell adhesion-->Cell adhesion_Integrin inside-out signaling
NOTE: Data from activated experiments is displayed on the map.
The Overview tab describes details of the map and provides references.
The Processes tab lists significant GO processes in the map.
From the Start Page, select the Search and Browse Content link and pick the Process Networks option.
This leads to a hierarchy of GeneGO process networks
Select Process Networks-->Cell adhesion_ECM remodeling
NOTE: Data from activated experiments is displayed on the network.
The network is highly interactive.
From the Start Page, select the Search and Browse Content link and pick the Protein Groups & Complexes tool.
The tool links to a page of table of results, select Integrin Receptor Family (Human)
The analyze single experiment workflow allows one experiment to be tested. Activate the an experiment with desired thresholds applied and select Analyze Single Experiment from the Workflows & Reports list.
Confirm Network object count and threshold settings and click Apply.
Results are returned by ontology, statistics are -log(pValue) (1.3 = 0.05)
Results can be examined by clicking on the name. See Legend for more information about maps and networks. Note: network objects included in filtered sets display expression results in image.
Different results link to different types of data.
Pathway maps are nice interactive maps
Process networks and network statistics produce editable network maps.
GO Processes produce lists that can be used to draw networks.
Diseases link to disease pages.
This workflow requires at least 2 active experiments. Activate all 3 ColonMet experiments and refresh the browser page to confirm.
Select the Enrichment Analysis link to launch the workflow. Ensure the correct experiments are activated and click Next.
Fold change, p-value signal directionality can be adjusted on the next page. NOTE: the number of Network objects that meet threshold criteria are indicated. Clicking Apply launches the analysis.
Results are returned by ontology, statistics are -log(pValue) (1.3 = 0.05)
Results can be examined by clicking on the name. See Legend for more information about maps and networks. Note: network objects included in filtered sets display expression results in image.
Different results link to different types of data.
Pathway maps are nice interactive maps
Process networks produce editable network maps.
GO Processes produce lists that can be used to draw networks.
Diseases link to disease pages.
This workflow requires at least 2 active experiments. Activate all 3 ColonMet experiments and refresh the browser page to confirm.
Select the Compare Experiments link to launch the workflow. Ensure the correct experiments are activated and click Next.
Fold change, p-value signal directionality can be adjusted on the next page. NOTE: the number of Network objects that meet threshold criteria are indicated. Clicking Apply launches the analysis.
Genes passing thresholds in each experiment are compared and grouped in 3 categories:
Unique
Similar - present in more than one list
Common - present in all lists
Results are returned by ontology, statistics are -log(pValue) (1.3 = 0.05)
Results can be examined by clicking on the name. See Legend for more information about maps and networks. Note: network objects included in filtered sets display expression results in image.
Different results link to different types of data.
Pathway maps are nice interactive maps
Process networks and produces editable network maps.
GO Processes produce lists that can be used to draw networks.
Diseases link to disease pages.
Histograms can be sorted according to statistics
Statistically significant
Deferentially effected
Similarity by
Particular
Histogram are interactive, network statistics panel reports results.
Select an experiment, right click and activate Properties...
The page displayed indicates information about that experiment. There is a place to enter notes or descriptions, the number of IDs in play are also listed as is the Threshold and P-Threshold.
Threshold refers to the fold-change or log ration cutoff that is in play.
Select all three experiments in the ColonMet_Faked folder and activate Tools-->Set Threshold and Background List. Next to General, Enter 1 in the Threshold and 0.1 in the P Threshold. Leave background option at default and click OK.
If an array is the source of the data, the background list can be set to the gene content of the array, otherwise the default behavior is to use everything.
Use the right-click, properties function to confirm that threshold settings have been set for each experiment.
Activate the ColonMet_Faked_FC experiment and refresh the page so that it is visible in the Active Data panel.
Select the experiment in the active data panel and click Tools-->Set Threshold and Background List. Click the statistics button. Counts of pass-threshold items in various categories are displayed. The signal distribution button will show the data for these faked values.
The upper left panel of the Start Page hosts the data management functions.
Click the "Start Page" icon or your browsers "refresh" button to make sure that the displayed data is current.
Double-click the "Experiments" folder. You should see "ColonMet_Faked" inside the folder.
Right-Click on the My Data folder and select Create Folder... Create a folder called May1Training
Drag ColonMet_Faked into the new folder. Right-click on the original folder to delete. Note: folders can also be renamed.
Data can also be shared. Right-click on May1Training and select Share..., enter charliew and search. select username and click Add Selected to List. Note: Types of permissions can be controlled.
The lower left panel of the Start Page displays the active data. Active data is available for analysis and can be controlled by the Activate/Deactivate icon, right clicking or drag-and-drop.