Service workflow


ROKIT Single-cell RNA-seq Service workflow

Sample Preparation
Single-cell mRNA Capture
& cDNA Amplification
Transcriptome
Amplification Library
Preparation
Next-Generation
Sequencing
Bioinformatics
Analysis

Features

• Single-cell RNA Sequencing

Analysis Type
Whole Transcriptome Analysis
Targeted mRNA Sequencing
Description
To study all cells in samples by identifying more than 20,000 total genes.
To study all cells in samples by identifying 397 immune-related genes.
- Can be added custom target genes
- Only for human and mouse samples
Available Samples
Cell line or cells from various biological resources, such as blood, tissue, organoid, etc.
Optional Cell Labeling :Different barcode sequences can be combined with antibodies targeting cell surface antigens to distinguish up to 12 samples.

• Bioinformatics Analysis

Analysis Type
Standard Analysis
Premium Analysis
Description
Analysis to obtain the primary results of the single-cell RNA-seq data
- Quality control, Dimensional Reduction (tSNE/UMAP), clustering, etc.
Analysis to study deeply and submit the results of the single-cell RNA-seq data to scientific journals
- Cell type classification, sequential sub-clustering, trajectory analysis, Differentially expressed gene analysis, etc.

Single-cell RNA-seq Technology


BD Rhapsody™ Single-Cell Analysis System

• Single-cell mRNA Capture & cDNA Amplification
• Transcriptome Amplification Library Preparation
• Next-generation sequencing (NGS, NextSeq 550dx)
Flow Cell Configuration
High-output Flow Cell
Mid-output Flow Cell
Read Length
2 x 75 bp
2 x 75 bp
Output
≥ 45 Gb
≥ 15 Gb
Data Quality
> 75% ≥ Q30
> 75% ≥ Q30

Bioinformatics Analysis


ROKIT Bioinformatics Analysis

• Heatmap
• Feature plot
• Dot plot
• Ridge plot
• Dimensional reduction
• Cell type classification
• Trajectory Analysis
• Differentially Expressed Genes (DEGs)