Cell Ranger5.0, printed on 11/05/2024
To reduce sequencing and library preparation costs, Feature Barcode Only mode can be used. In more recent versions of Cell Ranger, starting with 3.1, cellranger count can run using only an Antibody Capture library, without any gene expression data.
To use cellranger in Feature Barcode Only mode, follow instructions for Feature Barcode Analysis, and omit Gene Expression entries from the Libraries CSV file. Results from Feature Barcode Only analysis can be used with cellranger aggr, with the requirement that all aggregated runs must share a common feature reference.
Cell Ranger performs the normal Feature Barcode quantification analysis in Feature Barcode Only mode, but uses a simplified version of the cell calling algorithm. The EmptyDrops step that refines cell calls in not performed. See the Cell Calling algorithm documentation for details.
| We do not support analyzing libraries with peptide-MHC multimers only. We recommend using libraries with peptide-MHC mulitimers along with cell surface proteins targeting T-cell surface markers. |
| We also do not support analyzing a dataset with only a CRISPR Screening library. |
| If less than 10 antibodies are used in the Feature Barcode only mode, Cell Ranger will skip secondary analysis and will not output a cloupe file. This restriction does not affect runs where Gene Expression libraries are present. |
A web_summary.html file summarizing the run is produced as usual. Metrics for Antibody libraries appear under the Antibody Sequencing and Antibody Application sections. The Sequencing and Mapping sections, which display metrics from Gene Expression libraries, do not appear.
| Metrics results displayed in the web summary in Feature Barcode Only mode do not precisely match results for Gene Expression + Feature Barcode analysis, since there are differences in the set of cells that are called in each mode. |
Shown below are results for a single sample with Gene Expression and antibody Feature Barcode libraries. On the left, both libraries are processed together, and the barcode-rank plot displays Gene Expression counts. On the right, only the Feature Barcode library is supplied to cellranger count, and the barcode rank plot displays the antibody counts.
Observe that a similar number of cells were called in each cellranger run, but the shape of barcode-rank plot differs due to differences in the background levels of the Gene Expression and Antibody libraries.
Gene Expression + Feature Barcode |
Feature Barcode Only |
| The choice of antibodies in the panel plays a significant role in the effectiveness of cell calling in Feature Barcode only mode. |
Feature Barcode Only analysis only detects cells that are labelled by the Feature Barcode reagents in use. Cell types not well-stained by the panel have low total UMI counts and may not be called by the cell-calling algorithm. The table below illustrates this effect by comparing the number of cell detected in the gene expression library and antibody capture library derived from the same cells. As the number of antibodies in the panel increases, the number of cells detected in the Feature Barcode Only analysis approaches the number detected in the gene expression analysis. Below are results for a series of TotalSeq-B antibody panels applied to human PBMCs.
| Description | Loaded Cells | GEX Called Cells | Ab Called Cells | Called In Both |
|---|---|---|---|---|
| TotalSeq-B 4 Antibodies | 1000 | 705 | 562 | 533 (75.6%) |
| TotalSeq-B 5 Antibodies | 1000 | 749 | 653 | 626 (83.6%) |
| TotalSeq-B 14 Antibodies | 5000 | 4233 | 4389 | 3977 (93.9%) |
| TotalSeq-B 31 Antibodies | 5000 | 4616 | 4488 | 4540 (97.2%) |
