Enter Study

Overview

The Study overview screen will display the following Study Information:

Information	Description
Date Created	The date and time the study was created.
Created By	The user who created the study.
Date Modified	The last date and time the study was modified. This date updates whenever a user performs an action within the study, such as adding data, creating a sample group, starting a new analysis, etc.
Modified By	The user who last modified the study.
ICA Project	The ICA project the study imports data from.
Description	The description of the study, provided by the user during study creation.

You will also see the following Data Metrics:

Information	Description
Sample Files	The number of sample files within the study, including both manually added and auto-ingested sample files. Please see the File Extensions table for a list of possible sample file extensions.
Metadata Files	The number of metadata files within the study, identified by the .tsv file extension.
Samples	The number of samples within the study. Note that multiple protein samples can come from a single ADAT file, whereas a single spatial or scRNA sample is created for each set of spatial/scRNA files. Please see the File Extensions table for more information.
Analyses	The number of analyses within your study, including both in-progress and completed analyses.
Attributed Sample Count	The number of samples in the study with linked metadata.
Metadata Entry Count	The number of metadata attributes displayed in the study. This corresponds with the number of metadata columns shown next to your samples.

If there are analyses in your study, you will see the "Recent Analyses" section at the bottom of the Overview screen. For more information on analyses, see the Analyses section.

Update Study

To update any details of your study, click the gear icon in the top right. This will open a popup where you can edit the study name, description, and auto-ingestion options. Note that the ICA project from which the study receives data cannot be changed.

If you remove any omic types for auto-ingestion, output files from the pipelines associated with the omic types you've removed will no longer be automatically imported into the study upon pipeline completion. On the other hand, if you add a new omic type, output files from the corresponding pipelines will now be automatically imported into the study upon pipeline completion.

Click to save the changes.

Add Data

To add data, click the button in the top right. This will open a new screen where you can upload your data. At the top of the screen, you'll see the name of your study. On the top left, you'll see the name of the ICA project you're loading data from.

Select the omic type from the dropdown menu. For each omic type, you will only be able to select data with file extensions that match the specified extension for that omic type. Refer to the File Extensions table below to see which file extensions are accepted for each omic type. TSV metadata files can always be selected. For example, if you choose "Protein" as the omic type, you will only see ADAT files and TSV files as options for upload.

File Extensions Table

Omic Type	File Extensions	Samples per File	Extra Information
Protein	.adat	Multiple samples per file
scRNA	.matrix.mtx[.gz] .(features|genes).tsv[.gz] .barcodes.tsv[.gz]	One sample per set of files	Any additional descriptors prior to main extensions are supported (eg .scRNA.filtered.matrix.mtx).
Bulk RNA	.sf .sf.gz	Multiple samples per file
Spatial	.h5ad .ome.tiff	One sample per set of files	At least one .ome.tiff and multiple .h5ad files are required.
Metadata	.tsv	Multiple samples with metadata attributes per file

You can use the "Columns" tab on the right to add or remove columns and use the "Filters" tab to filter data. Each column also has a filter icon and three dots which you can click on to find more options.

If you want to upload a metadata file from your local folder, click in the top right. This will add the metadata file directly to your study, rather than ingesting it from an ICA project.

Once you've selected your data, click to add the data to your study. Upon submitting, you'll be redirected to the "Samples" tab, and a message will indicate your data ingestion was successful.

Now, if you click back to the "Overview" tab, you'll see that the "Date Modified" was updated and the "Data Metrics" reflect the newly added files and samples.

Repeat the process to add data for additional omic types.

Samples

In the "Samples" tab, you'll see a list of samples that were added to the study from the ingested sample files, along with their associated metadata attributes. The number at the top indicates how many samples are included in your current view. You can search for a sample using the search bar on the right.

The "Columns" tab on the right-hand side allows you to customize which columns you want to view. Click on a column to add it to the table, and click again to remove it. Click the refresh icon to refresh the sample view after adding more data or to clear your filters and reset to the default view.

The "Filters" tab on the right-hand side lets you filter your list based on metadata attributes. This is useful when creating sample groups based on specific attributes.

You can also drag and drop columns to reorder them, and click on the filter icons or the three dots next to each column name for additional filtering options.

Sample Naming

Proteomic Data

Sample IDs for proteomic data will be extracted from the sample names provided in the ADAT files. Each file can contain multiple samples. For example, the Sample ID in the ADAT file (left image) corresponds to the sample name in a row of the ICM table (right image). A new sample will be created in ICM for each Sample ID listed in the ADAT file.

Single Cell RNA Data

Sample IDs for scRNA data are obtained by removing the file extension from the file name. As a result, scRNA samples will be paired with their corresponding files based on the sample name. For example, the name of the scRNA files (left image) matches the sample name in a row of the ICM table (right image). Refer to the File Extensions table for information on the required files that make up a single scRNA sample.

Spatial Data

Sample IDs for spatial data are derived by removing the file extension from the file name. Thus, spatial samples are linked to their corresponding files through the sample name. For instance, the name of the spatial data files (left image) corresponds to the sample name in a row of the ICM table (right image). Refer to the File Extensions table for details on the required files that make up a single spatial sample.

Metadata Mapping

Metadata columns are populated based on the information in your metadata TSV file. Upon importing a metadata file, the samples will automatically be updated to reflect the metadata attributes. The sample names in the metadata file must match those in the data files. For example, in the figure below, you can see that the Sample ID in the ADAT file matches the SampleID in the metadata file. As a result, the attribute columns in the metadata file will correspond with the metadata columns available for selection in the ICM table.

You can add multiple metadata files. In this case, any samples that do not overlap with existing ones will be added as new entries in the ICM table.

Sample Statuses

The following table describes the different sample statuses.

Note that protein samples only display the "Ready" status.

Status	Description
Ingested	The sample has been ingested to the ICM Study but may not have been uploaded to ICM Analysis yet.
Uploading	The sample is in the process of uploading to ICM Analysis. Samples cannot be used for analyses while they are uploading.
Ready	The sample is ready to be used in analysis.
Failed	The sample ingestion failed.

Sample Groups

A sample group refers to a collection or subset of samples that are grouped together based on shared characteristics or attributes.

Create Sample Group

To create a sample group, use the Filters tab in the right-hand side of the "Samples" section. Filter your samples down into only those you want to be part of your sample group.

For example, to create a sample group of women older than 30 years in age, filter the Sex and Age At Collection fields.

Note how the sample number at the top will change to reflect the number of samples that meet these conditions.

Now, click to create a sample group off of the filtered attributes. Give the sample group a name and click .

You can view all your sample groups by clicking the "Sample Groups" tab in the top. From here, you can search for sample groups, and customize or filter the columns in your view.

You can also click on the action icons to view more details and update your sample groups.

Icon	Action
	Opens a pop-up with details of your sample group.
	Allows you to edit the sample group's name.
	Allows you to delete the sample group.

Analyses

In the "Analyses" tab, you'll see all the analyses in your study. The analyses will be displayed in card view by default. Each card will display the following information.

Information	Description
Analysis Name	Name of analysis.
Status	Status of analysis. See Analysis Statuses for a table of statuses and descriptions.
Analysis Type	Type of omic data used in analysis.
Modified By	Last user who modified the analysis.
Date Modified	Date and time when the last update was made.

You can switch to list view by clicking the list icon in the top right. In the list view, you can customize the columns and filter your analyses.

Note that default analyses will be created automatically. This functionality will be applied to single cell RNA and spatial analyses.

Create Analysis

To create a new analysis, click .

Give your analysis a name and choose an analysis type from the dropdown menu.

Analysis Options

Analysis Option	Description
Default: Proteomic	General analysis pipeline for Illumina protein prep samples, with PCA and hierarchical clustering heatmap results
Default: Single Cell Transcriptomic	General analysis pipeline for Illumina single cell prep samples, including the processing steps to output PCA and UMAP visualizations
Default: Spatial Transcriptomics	General analysis pipeline for Illumina spatial prep samples, including a Spatial map with transcripts overlayed on the tissue image where each point is a grid. Graph-based clusters are also plotted on a UMAP and pie chart
Custom: Proteomic	Starts with the quantified samples which have undergone prior normalization and offers flexible analysis options
Custom: RNA	Starts with salmon format sample counts that have not been normalized and offers flexible analyses options. The assembly and annotation model used in secondary analysis is required to annotate the features
Custom: Single Cell Transcriptomics	Starts with single cell counts and offers flexibility with the analyses pipeline step
Custom: Spatial Transcriptomics	Two starting nodes as cell-binned or grid-binned data, including the spatial image outputs, and offers flexibility with the analyses parameters

Next, select the sample, sample group, or all samples for the analysis.

If all samples are chosen for the analysis, a sample group will be automatically added to the Sample Groups menu containing all of the samples in the analysis.

Run Analysis

Click to run the analysis. You will receive a notification that the analysis was successfully created.\

Wait for the analysis status to change from "Pending" to "Complete".

Analysis Statuses

The following table describes the different analysis statuses.

Status	Description
Pending	The analysis has been initiated but has not yet started. It is waiting in the queue to be processed.
In Progress	The analysis is currently being executed. The system is processing the data and generating results.
Complete	The analysis has finished, and the results are ready to be viewed. Click into the analysis to view it.

Once the analysis is complete, you can click into it to view the results. Refer to the "Enter Analysis" section for more information on how to view your analysis.

Data Management

In the "Data Management" tab, you'll see a list of all the data and metadata files within your study. From here, you can delete files if needed.

Note that deleting data or metadata files will not remove any samples that were added to ICM from those files. The samples will remain in ICM, even if the original files are deleted, ensuring that your sample data stays intact.