All assays include partitioning and barcoding using the Chromium Controller and manual library preparation.
Chromium Single Cell Gene Expression
- Gene expression profiling for characterization of tens of thousands of single cells
- Identify rare cell types
- Atlas and characterize complex cell populations
- Understand cellular heterogeneity
- Discover new biomarkers
- Input:
- 500 - 10,000 cells or nuclei
- Suitable for:
- Cells or nuclei
- Flow-sorted cells
- Cells labeled with cell surface protein antibodies
- Cells expressing compatible CRISPR guides
- Molecular barcoding and capture:
- Capture and amplify 3' mRNA
- Capture and identify cell surface proteins and CRISPR perturbations
Chromium Single Cell Immune Profiling
- Paired, full-length receptor sequencing and gene expression profiling for tens of thousands of T and B cells
- Profile immune cell repertoires
- Determine antigen specificity of B cells and T cells
- Characterize tissue microenvironments
- Go beyond traditional cytometry
- Input:
- 500 - 10,000 cells
- Suitable for:
- Cells
- Flow-sorted cells
- Cells labeled with cell surface protein antibodies
- Cells labeled for antigen specificity analysis
- Molecular barcoding and capture:
- Capture and amplify 5' mRNA
- Capture and sequence paired, full-length BCR/TCR genes
- Capture and identify cell surface proteins and antigen-specific immune receptors
Chromium Single Cell Multiome ATAC + Gene Expression
- Simultaneous gene expression and open chromatin profiling from the same cell for tens of thousands of cells
- Link regulatory elements and target genes
- Characterize cell heterogeneity
- Discover new gene regulatory interactions
- Identify rare cell types
- Input:
- 500 - 10,000 nuclei
- Suitable for:
- Nuclei treated with transposase
- Molecular barcoding and capture:
- Capture and amplify transposase-accessible DNA fragments
- Capture and amplify 3' mRNA
Chromium Single Cell ATAC
- Assay for transposase-accessible chromatin (ATAC) for epigenomic analysis of tens of thousands of individual nuclei
- Define cell types and states
- Catalog cell type–specific regulatory elements
- Identify important transcription factors
- Characterize gene regulatory networks
- Input:
- 500 - 10,000 nuclei
- Suitable for:
- Nuclei treated with transposase
- Molecular barcoding and capture:
- Capture and amplify transposase-accessible DNA fragments
Other Options
- Requests for projects requiring significant modifications to existing protocols or library preparation options not already listed here will be discussed with the customer on a per-project basis.
Sample Submission
- We cannot accept any samples that would be classified as Biosafety Level 2 (BSL2) or higher!
- We work closely with the customer to coordinate sample submission and workflow timelines to optimize cell viability and recovery.
- The maximum cell size 10x Genomics tested in-house is 30 μm. 10x Genomics did not observe differential recovery for small vs. large cells when running a sample composed of cells of different sizes (for cells that are equal to or smaller than 30 μm).
- The recommended starting point for a new sample type is to load ~1,700 cells into each reaction, recovering approximately 1,000 cells, to achieve an expected multiplet rate of approximately 0.8%. For comparison, loading ~17,400 cells and recovering approximately 10,000 cells yields a multiplet rate of approximately 7.6%.
Notes & Resources
- Single Cell Protocols - Cell Preparation Guide
- Guidelines for Optimal Sample Preparation Flowchart
- Cell Thawing Protocols for Single Cell Assays
- Best Practices to Minimize Chromium Next GEM Chip Clogs and Wetting Failures
- Q&A: What buffers can be used for washing and cell resuspension?
- Q&A: What is the highest BSA concentration that can be used in the cell buffer?
- Q&A: What is the difference between Single Cell 3' and 5’ Gene Expression libraries?
- Interpreting Intronic and Antisense Reads in 10x Genomics Single Cell Gene Expression Data
- Confronting False Discoveries in Single-Cell Differential Expression
- MULTI-seq: sample multiplexing for single-cell RNA sequencing using lipid-tagged indices