Single-Cell
The Single-Cell Omics Platform offers the single-cell services listed below covering both experimental and computational analysis. Computational support includes data processing, QC, annotation, and differential gene expression analysis.
Services
Universal 3' Gene Expression
Universal 3’ Gene Expression (10x Genomics) is a high through-put transcriptomic analysis (PolyA capture) with detection of up to several thousand transcripts per cell or nucleus. It can be combined with antibody-based surface detection (hashing) to enable sample multiplexing.
SCOP Product Sheet
Epi ATAC
EPI ATAC (10x Genomics) enables the analysis of chromatin accessibility at a single cell resolution. It can be combined with antibody-based surface detection to enable sample multiplexing (hashing).
PerturbSeq & DC-TAPSeq
Perturb-seq & DC-TAP-seq combines CRISPRi editing system for precise gene manipulations with single-cell RNA sequencing (10x Genomics) readout for whole transcriptome (Perturb-seq) or targeted (DC-TAP-seq) profiling of perturbation effects.
Flex Gene Expression
Flex Gene Expression (10x Genomics) is a sensitive probe-based method that enables whole transcriptomic analysis of fixed cells or nuclei. It can be especially useful for large-scale setups.
Epi Multiome
EPI Multiome (10x Genomics) allows RNA and ATAC sequencing from the same nucleus. It can be combined with antibody-based surface detection to enable sample multiplexing (hashing).
Guidelines
Please read through our guidelines below:
Good quality of cells/nuclei is essential to obtain good data; therefore, the cells/nuclei dissociation is one of the most critical steps in a single-cell experiment!
Dissociation: Have a validated protocol for single cell/nuclei dissociation for the target tissue/cell line before you initiate a single-cell project. We recommend testing and validating different dissociation protocols to find the best protocol for your sample type, with high quality nuclei/cells and without debris. If antibody-based detection (hashing) is used, mimic this condition to validate your sample quality after hashing.
Multiplexing: Consider multiplexing your samples. For most setups, multiplexing will be an advantage and reduce technical variability. The best way to multiplex will be sample and setup dependent. Talk to SCOP about how this can be done. Freezing: Freezing can affect both the quality and quantity of your samples. If you need to freeze down your samples (after cell harvest or similar), validate your freezing protocol before you initiate a project. Tests may include checking cell morphology, viability %,aggregate% and quantification.
Fluorescence-activated cell sorting (FACS): if FACS will be used, we strongly recommend performing a FACS test on your sample types prior to the actual start of the single-cell experiment. SCOP together with the user will establish and agree on an optimal FACS procedure.
- If using cells as input: > 90% cell viability (a cell viability between 70-80% can be accepted but data quality may be compromised).
- Intact nuclei or cell membranes
- No to minimal debris and cells/nuclei aggregates
- Optional quality measures: DV200 > 30% for nuclei and fixed samples
SCOP always recommends performing a pilot project to assess both sample and data quality.
Single cells or nuclei should be delivered at a specific concentration which depends on assay type and the desired number of cells. Please contact SCOP for more information.
- Single-cell/nuclei suspension quality assessment (optional)
- FACS (optional)
- GEM generation and barcoding using Chromium X
- Library construction and QC
- Pooling and Sequencing on NovaSeq X
- FASTQ files
- Data processing using SCOP’s RNAseq pipeline (LINK)
- Cell annotation
- Differential Gene Expression analysis
- Data report
Support is limited to simple experimental designs; complex or custom analyses and advanced statistics are not supported.
Applicable for GEX:
FASTQ generation, mapping and quantification are performed as described in our workflow COMUNEQAID (link).
Quality control is performed using either outlier detection or pre-agreed thresholds based on UMI counts, gene counts, mitochondrial content, and unspliced RNA percentage.
Cell type annotation can be performed using label transfer with a user-provided reference; be aware, this is dependent on the quality and resolution of the reference.
Differential gene expression (DGE) analysis is conducted using a pseudo-bulk approach. Marker genes are identified via one-vs-rest DGE analysis. Upon prior agreement, two-way ANOVA –like tests can be performed per cell type with selected covariates and contrasts.
The price for a single-cell project depends on the number of required cells/nuclei, recovery, and sequencing depth. We recommend running a pilot study to assess data quality, cell recovery, and estimate the required number of cells. Contact SCOP to receive a quote.
Please recognize and acknowledge SCOP’s contributions to the scientific improvements in your project. Being acknowledged in publications is very important as it serves as documentation for the SCOPS's value and performance.
Single-Cell Workflow
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