Data Upload Workflow

Use Dataset Upload to import your dataset file into IPA.  Once uploaded, many different analysis options exist including Core Analyses, Biomarker, Tox,and Metabolomics. Review the different type of analyses and see which one best fits your needs. For more information on these analyses, click here.
1.To upload a dataset file, Go to File, Upload dataset. 
2. Select the dataset file from your computer and click the Open button. In addition to XLS, XLSX, or TXT format files, IPA can also upload RNA-seq .DIFF files (see Cuffdiff file import article). 
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3. Select Flexible Format from the drop down menu if it not already selected. 
4. Select an Identifier Type from the dropdown menu. IPA supports many identifiers and symbols and will attempt to guess at the type of identifier in your dataset file if the identifiers are in the left-most column. To override the selection, uncheck the option and simply select the most appropriate one. If more than one type of identifier exists in your dataset, select all appropriate ones. But refrain from selecting all identifier types as it can lead to poorer mapping or mis-mapping.
See Data Upload definitions for more detail about the identifier types that are supported.
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5. Select the Array platform used for experiments if that is applicable.
6. Specifying the contents of each column in your dataset either automatically or manually:

Automatically: Click the Infer Observations button to try to automatically map the relevant columns in your dataset. This works best if the identifiers are in the left-most column, and the dataset is not overly complicated with extraneous columns that you plan to ignore.

Manually: If the Infer Observations button does not work well for your particular dataset, then click the button again to toggle back to the manual mode. Use the drop-down menus to define the columns in your file:

  • First, indicate the column that contains the identifiers.
  • Next, group the columns by observation, if there are multiple observations in your file. An observation is a set of related measurements for one condition. For example, if your dataset has data for three time points, that would mean there are three observations. If two columns are a part of one observation (for example a fold change and p-value column), select the same observation number for each of those two columns.
  • Next, assign the measurement value types. A measurement type indicates the type of data you are uploading. If you have fold changes and p-values for expression data, you should assign these to “Expr Fold Change” and “Expr p-value”, respectively, whereas if you had phosphorylation ratios, you should assign these to “Phospho Ratio”. If you have differential metabolomics data, you should assign these values as “expression" (Expr).
  • Follow the same steps for the remaining columns. If the dataset file contains extraneous columns of information, i.e. columns containing notes or information not needed for the analysis, select Ignore in the dropdown menu. 

See Data Upload definitions for more detail on single observation versus multi-observation datasets and on the available measurement value types.

- Ignore: Right-click a column and select Ignore.
- Repeat Selection: Select a column(s), right-click the selected columns and select Repeat Selection. The assignments made for the selected columns will be repeated for the columns to the right of the selected ones. 
- Header Names -> Observation Name: This selection will take the name found in the column header and use it to label the observation. 
- Group In: Select more than one column, right-click the selected columns and select Group In. The selected columns will be grouped as an observation. 

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7. Edit Observation Names. If the dataset file is in either Ingenuity formats, then the column headers are automatically used to label the observations. Click the Edit Observations Names button to rename the observations.
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8. Click the Save or Save & Create Analysis button to proceed. As part of Dataset Upload, the only option is to the save the uploaded dataset to the Project Manager. If you are creating an IPA-Biomarker, Core, IPA-Metabolomics, or IPA-Tox Analysis, clicking the Save & Create Analysis button will take you to the appropriate Create Analysis page.

9. From the Project Manager, if you double click on a dataset, the annotated dataset will open and will display the Mapped IDs, UnMapped IDs, and All IDs. The flags column indicates "duplicate identifiers" and those that are marked as "Override" or "Absent". 

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How can I edit a dataset that I have already uploaded and used it to run an analysis?
Go to Project manager, Select the dataset file and open it.  In the right handside bottom corner you will see the button to Edit Dataset Settings.
This enables you to correct any mistakes made in the original assignment of columns, measurement types, observation names, and identifier types. It does not allow you to actually edit the underlying data.

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The original dataset will be displayed and all the parameters of data upload available for you to make any changes.  Once you make changes select Replace Dataset.

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The original dataset will be replaced with the new one and any analysis, overlay or micro RNA filter created with the original dataset will be affected. 

If you are unsure about proceeding with this step of replacing the original dataset.  Then please cancel and upload the dataset again(instead of Editing original dataset) and set the new parameters for data upload and run a new analysis