Targeted analysis is hypothesis-driven.
Targeted Analysis is CellSeekr’s most granular analysis mode. It enables users to investigate the expression of selected genes across custom-defined immune cell signatures, offering precise control over both cell type selection and gene queries. Users can specify immune cell signatures, explore transcriptional profiles across these populations, and perform pairwise comparisons between two custom cell types in the context of patient response or treatment setting within a given study.
Interested in a guided case study? Read a Case Study tutorial or watch a Video tutorial.
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Basic Steps to Using CellSeekr Targeted Analysis
In order to use CellSeekr, access the analyzer page and select “Targeted.”
Step 1. Select tumor
CellSeekr has several pre-built studies that are ready to be analyzed. Select the tumor type/study that interest you using the dropdown menu.
Step 2. Select Analysis Mode
Select one of three analysis modes: Standard, Gene Expression and Correlation.
Standard Analysis enables quantification of custom immune cell signatures in tumor and patient datasets, with flexible assignment of cell gates based on user-selected genes.
Gene Expression Analysis calculates the average normalized expression of a user-selected gene within a desired cell type.
Correlation Analysis enables the calculation and visualization of the correlation between two immune cell types, or between a gene and a cell type, and reports the Pearson correlation coefficient.
Standard Mode: Immune Cell Expression
Step 1. Select Study and Comparison Groups
Select the comparison groups (pairwise comparison) which you want to analyze. A reference to the Gene Expression Omnibus study or studies from which the data were sourced will appear below your selection.
Step 2. Select Cell Type
The cell type you are interested in exploring gene expression for is referred to as Phenotype 1. You can select from several pre-populated immune cells by checking the box next to cell type of choice. If you wish to define your own gene signature, skip to the next step.
Select “Enable Second Phenotype” to add a second cell type. If selected, follow the same steps as for the first cell type. When a second phenotype is enabled, the final graph will display data for each cell type separately.
Step 3. Option A. Add custom genes to selected cell type
You can define additional genes to be added to the pre-selected cell type in Step 2. To do that, click on “Other/Custom” under “Select a Cell Type” in Step 2. In the dropdown menu, select the cell population to which you want to add additional genes.
To add additional genes, click “Add gene” for each additional gene you want to add. Use “negative” to select for cells lacking this gene, or “positive” to include this gene in the cell’s expression. If the gene is recognized, the border of the input box will turn green. If a gene is not recognized, the border will turn red, and the entry will need to be corrected, edited, or removed before proceeding.
Once you are done adding genes, click “Done Defining Gate (Phenotype 1).”
Step 3. Option B. Define genes independent of cell type
Use this option is you want to look at expression of genes that are not associated with any cell type. To do that, when selecting cell type, click “Other,” then under “Start from predefined cell type” click “None.” Then, select “Add Genes” to add your genes. This will yield expression of genes across all cells.
Step 4. Select viability gate
UBC (ubiquitin C) is a housekeeping gene expressed in all healthy, transcriptionally active cells. Select UBC as a filter for viable cells. This setting is selected by default.
If selected, every cell must have UBC > 0 to be counted. If not selected, only the upstream QC filters apply (nFeature > 200, MT% < 10, doublets removed).
Step 5. Define reference cell type and phenotype
CellSeekr calculates gene expression relative to a selected reference cell type and phenotype. The cells and genes selected in Steps 1–3 serve as the “numerator,” while the reference phenotype serves as the “denominator” for percentage calculations.
To define the reference phenotype, select the appropriate cell type under “Denominator for Percentage Calculation.” If desired, you may also add additional genes to the reference cell type by entering the gene name(s) in the input field. To do that, click “Add Gene to Denominator” and type the gene symbol(s) of choice. Repeat for each gene you wish to add.
When selected, this option prompts CellSeekr to treat both the genes associated with the chosen cell type and the additional gene(s) as a single combined signature.
Step 6. Run Analysis
After making all your desired selections, click “Apply Filter & Run Analysis” to run the analysis. Depending on the complexity of your request, the analysis may take several minutes to complete.
CellSeekr generates a bar graph displaying cell type-specific gene expression for selected pairwise groups (See examples below).
How to select custom gene and immune signatures
CellSeekr pre-defines several immune populations:
T cells, NK cells, Myeloid cells, Tregs, M1 Macrophages, M2 Macrophages, Granulocytic MDSCs, Monocytic MDSCs, All immune cells, CD45– cells
You can choose any of these to perform your desired analysis. The signatures for each of these pre-defined cell types are listed in the documentation.
To add additional genes to the presets, follow “Step 3 Option A” above, where you can add additional genes to the pre-selected cell population.
Cell type-specific gene expression for Selected Pairwise Groups
The cell type-specific gene expression shows a bar graph comparing the expression of the select gene + cell type combination for each of the two comparison groups selected at the beginning of the analysis. p-values are shown for statistical significance determination.
The graph on the left shows expression of IL2RA on T cells in healthy bone marrow aspirate vs acute myeloid leukemia (AML) patient bone marrow aspirate.
Gene Expression Mode: Gene Quantiation
Step 1. Select Study and Comparison Groups
Select the comparison groups (pairwise comparison) which you want to analyze. A reference to the Gene Expression Omnibus study or studies from which the data were sourced is listed above each comparison group option.
Step 2. Select Cell Type
The cell type you are interested in exploring gene expression for is referred to as Phenotype 1. You can select from several pre-populated immune cells by checking the box next to cell type of choice. If you wish to define your own gene signature, skip to the next step.
The cell type you are interested in exploring gene expression for is referred to as Phenotype 1. You can select from several pre-populated immune cells by checking the box next to cell type of choice. If you wish to define your own gene signature, skip to the next step.
Step 3. Option A. Add custom genes to selected cell type
You can define additional genes to be added to the pre-selected cell type in Step 2. To do that, click on “Other/Custom” under “Select a Cell Type” in Step 2. In the dropdown menu, select the cell population to which you want to add additional genes.
To add additional genes, click “Add gene” for each additional gene you want to add. Use “negative” to select for cells lacking this gene, or “positive” to include this gene in the cell’s expression. If the gene is recognized, the border of the input box will turn green. If a gene is not recognized, the border will turn red, and the entry will need to be corrected, edited, or removed before proceeding.
Once you are done adding genes, click “Done Defining Gate (Phenotype 1).”
Step 3. Option B. Define genes independent of cell type.
Use this option is you want to look at expression of genes that are not associated with any cell type. To do that, when selecting cell type, click “Other,” then under “Start from predefined cell type” click “None.” Then, select “Add Genes” to add your genes. This will yield expression of genes across all cells.
Step 4. Select viability gate
UBC (ubiquitin C) is a housekeeping gene expressed in all healthy, transcriptionally active cells. Select UBC as a filter for viable cells. This setting is selected by default.
If selected, every cell must have UBC > 0 to be counted. If not selected, only the upstream QC filters apply (nFeature > 200, MT% < 10, doublets removed).
Step 5. Select second cell type (Optional)
If enabled, a second cell type can be selected for direct comparison of gene expression against the first. Check the second phenotype option and repeat steps 2 and 3 to define the second cell type.
Step 6. Select target gene
Type the name of the gene whose expression you wish to measure in the input box. If the gene is recognized, the border will turn green. If the gene is not recognized, the border will turn red, and the entry must be corrected or removed before proceeding.
Step 7. Run Analysis
After making all your desired selections, click “Apply Filter & Run Analysis” to run the analysis. Depending on the complexity of your request, the analysis may take several minutes to complete.
CellSeekr generates a violin plot displaying cell-specific gene expression for selected pairwise groups (See example below).
Gene Expression Violin Plot
Violin plot displaying the expression of a user-selected gene within a custom-defined cell type across two comparison groups. In the example shown, the plot displays expression of HAVCR2 on T cells in AML patient bone marrow aspirate compared its expression on T cells in healthy bone marrow aspirate.
Correlation Mode: Cell vs. Gene Analysis
Step 1. Select Study and Groups for Correlation Analysis
Select up to three study groups for correlative analysis.
Step 2. Select Cell Type
The cell type you are interested in exploring gene expression for is referred to as Phenotype 1. You can select from several pre-populated immune cells by checking the box next to cell type of choice. If you wish to define your own gene signature, skip to the next step.
The cell type you are interested in exploring gene expression for is referred to as Phenotype 1. You can select from several pre-populated immune cells by checking the box next to cell type of choice. If you wish to define your own gene signature, skip to the next step.
Step 3. Option A. Add custom genes to selected cell type
You can define additional genes to be added to the pre-selected cell type in Step 2. To do that, click on “Other/Custom” under “Select a Cell Type” in Step 2. In the dropdown menu, select the cell population to which you want to add additional genes.
To add additional genes, click “Add gene” for each additional gene you want to add. Use “negative” to select for cells lacking this gene, or “positive” to include this gene in the cell’s expression. If the gene is recognized, the border of the input box will turn green. If a gene is not recognized, the border will turn red, and the entry will need to be corrected, edited, or removed before proceeding.
Once you are done adding genes, click “Done Defining Gate (Phenotype 1).”
Step 3. Option B. Define genes independent of cell type.
Use this option is you want to look at expression of genes that are not associated with any cell type. To do that, when selecting cell type, click “Other,” then under “Start from predefined cell type” click “None.” Then, select “Add Genes” to add your genes. This will yield expression of genes across all cells.
Step 4. Select viability gate
UBC (ubiquitin C) is a housekeeping gene expressed in all healthy, transcriptionally active cells. Select UBC as a filter for viable cells. This setting is selected by default.
If selected, every cell must have UBC > 0 to be counted. If not selected, only the upstream QC filters apply (nFeature > 200, MT% < 10, doublets removed).
Step 5. Select second cell type (Optional)
If enabled, a second cell type can be selected for direct comparison of gene expression against the first. Check the second phenotype option and repeat steps 2 and 3 to define the second cell type.
Step 6. Define reference cell type and phenotype
CellSeekr calculates gene expression relative to a selected reference cell type and phenotype. The cells and genes selected in Steps 1–3 serve as the “numerator,” while the reference phenotype serves as the “denominator” for percentage calculations.
To define the reference phenotype, select the appropriate cell type under “Denominator for Percentage Calculation.” If desired, you may also add additional genes to the reference cell type by entering the gene name(s) in the input field. To do that, click “Add Gene to Denominator” and type the gene symbol(s) of choice. Repeat for each gene you wish to add.
When selected, this option prompts CellSeekr to treat both the genes associated with the chosen cell type and the additional gene(s) as a single combined signature.
Step 7. Select type of correlation: Cell or Gene
Correlate with a gene: When selected, CellSeekr will calculate the Pearson correlation between the cell type defined in steps 2 and 3 and a gene of interest. Type the gene name in the input box to select it. If the gene is recognized, the border of the input box will turn green. If a gene is not recognized, the border will turn red, and the entry will need to be corrected, edited, or removed before proceeding.
Correlate with a 2nd phenotype: When selected, CellSeekr will calculate the Pearson correlation between the cell type defined in steps 2 and 3 and a second custom cell type. Repeat steps 2 and 3 to define the second cell type.
Step 8. Run Analysis
After making all your desired selections, click “Apply Filter & Run Analysis” to run the analysis. Depending on the complexity of your request, the analysis may take several minutes to complete.
CellSeekr generates a Pearson correlation graph displaying the correlation between the selected cell types and/or genes across the chosen pairwise comparison groups. (See example below).
Pearson Correlation Graph
The Pearson correlation graph displays the relationship between a selected immune cell type, expressed as a percentage of total cells, and either another cell type or a user-selected gene. The Pearson correlation coefficient (r) and corresponding p-value (p) are reported alongside the plot. In the example shown, the correlation between myeloid cells as a percentage of immune cells with ITGAM expression in AML bone marrow aspirate is plotted via the “Correlation” tool.
How to request studies to be added to CellSeekr
To request custom scRNAseq studies to be added to the analyzer, submit a study request.