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Upload OmicSoft Data to IPA
This function allows users to quickly upload data from inference reports into Ingenuity Pathway Analysis (IPA) (if the user has an IPA subscription), and even submit an analysis.
To upload your inference reports (e.g. DESeq2 results) from the Analysis tab, click Integration | IPA | Upload Data
To upload pre-computed inference reports from a Land (e.g. comparisons from DiseaseLand or OncoGEO), switch to the Comparison Table View, and click the IPA button in the task bar:
Input Data Requirements
Any table with at least one set of columns assigned to a Group can be used as input; generally Inference Reports will be used as input.
If User Dataset will be used as the Reference Set (see below), the input dataset should be pre-filtered, or a list of input genes should be prepared as a List.
- Rows: Select the input rows (genes or transcripts) to upload. Can select all rows, Visible rows, Selected rows, or Customized rows (from a List).
Main options are focused on uploading new data to IPA.
- Project Name: Specify the main project (new or existing) to deposit the analysis results in the IPA account.
- Dataset Name: Specify the name of the current dataset (must be unique within the project).
- Dataset description (optional): Describe the dataset to be uploaded.
- Observations to upload: Select one or more grouped results from the selected table, to be used as input for IPA.
- Replace missing raw and adjusted P values with 1: If the input dataset contains missing values for some identifiers, specify whether to replace these with 1.
- Select columns and type IDs: Specify the columns and types used to identify gene/transcript identifiers. By pressing the button the following dialog opens:
User can select up to 5 ID columns / Id types which to be used by IPA for mapping. For each row in the uploaded dataset, IPA will attempt to map IDs starting with first selected ID until an ID successfully maps.
- ID column 1..5: Specify the column used to identify gene/transcript identifiers.
- ID type 1..5: Specify the type of identifiers in the ID column 1..5, such as Ensembl, Entrez Gene, Affymetrix, HUGO Gene Symbol, Pubchem CID, etc.
Advanced Options are focused on parameters for performing IPA Core analysis on the dataset to be uploaded.
- Generate Core Analysis: Select whether to auto-submit a core analysis on the uploaded dataset.
- Use only direct relationships in the analysis: IPA will only look for pathways with direct connections between components.
- Include chemical nodes in the analysis: Include chemicals with evidence for involvement in pathways.
- Analysis name: Specify the name for this core analysis (must be unique within the project)
- Reference Set: Specify which set of genes/transcripts should be used as the "Reference" to calculate enrichment statistics.
- If you have pre-filtered for a background set of expressed or variable genes, use User Dataset for a more accurate statistical test
Cutoffs will use, within each Group columns, the column Mode corresponding to the filter, e.g. FoldChange and RawPValue.
- Fold change focus: Whether to analyze Both up- and down-regulated genes, only Up, or only Down.
- Fold change cutoff: Restrict the analysis to genes/transcripts passing this FoldChange cutoff.
- P value cutoff: Restrict the anlaysis to genes/transcripts passing this RawPValue cutoff.
- Adjusted P value cutoff: Restrict the anlaysis to genes/transcripts passing this AdjustedPValue cutoff.
- Group Max (intensity) cutoff: Use the GroupMax column to restrict to genes/transcripts expressed at least as strongly (in case or control) as this cutoff).
- Measurement for resolving duplicates: Duplicate entries will be consolidated by the specified criterion.
- Consolidate IDs using the value: How to consolidate duplicate entries.
- Analysis description (optional): Describe this analysis.
Data will be automatically submitted to IPA, to the user's account. The uploaded dataset will be found in Dataset Files, and the analysis will be in Analyses.