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Single Cell RNA-Seq Analysis

Single Cell RNA-Seq Analysis Online Inquiry

CD Genomics provides single-cell RNA-Seq data analysis service. We can help you explore the secrets of biological individuals through cells by virtue of the excellent bioinformatic analysis techniques. Our unique skills in data analysis can meet customers' personalized data analysis needs and provide you the most comprehensive data analysis results.

Introduction of Single Cell RNA-Seq Analysis

A cell is the smallest functional unit of an organism. The unique gene expression characteristics of each cell are closely related to the function of the cell and tissue. Traditional genetic sequencing is performed on tissue samples or cell populations, and differences between cells may be masked by averaging. Understanding of biological systems requires the knowledge of their individual components. Single-cell RNA sequencing (scRNA-seq) can be used to dissect transcriptomic heterogeneity that is masked in population averaged measurements.

Single-cell RNA sequencing data bioinformatic analysis can reflect the difference of gene expression, which is helpful to study the heterogeneity and randomness of gene regulation network and gene expression. Combined with the method of system biology, it can be applied to the field of tumor research. Network analysis of gene expression regulation at the single-cell level can monitor disease progression, continuously track the dynamic expression of tumor-related genes and can also study tissue and organ maps at different stages of embryonic development.

Dissection of melanoma with single-cell RNA-seq. Fig 1. Dissection of melanoma with single-cell RNA-seq. (Itay T, et al. 2016)

Application Field

Single cell RNA-Seq data analysis can be used for but is not limited to the following research:

Immunology

Oncology

Neurobiology

Developmental biology

Our Advantages

An experienced analytical team.

Standardized analysis process.

Strict data quality control.

Reliable analysis results.

Fast analysis cycle.

CD Genomics Data Analysis Pipeline

CD Genomics single cell RNA-Seq data analysis pipeline - CD Genomics.

Bioinformatics Analysis Content

CD Genomics can perform biological information analysis on single-cell transcriptome sequencing data with different read lengths. For example, based on the sequence read length of paired-end100 bp or single-end 50 bp, the following analysis can be performed.

Standard analysis

Sequencing data statistics

Remove adapter sequence and low-quality sequence

Map to reference genome

MRNA identification

Quantitative analysis of mRNA

MRNA differential expression analysis (more than two samples or groups)

MRNA expression

Differential gene clustering

GO annotation and enrichment of differentially expressed genes

KEGG pathway analysis of differentially expressed genes

GO annotation and enrichment of differentially expressed genes

mRNA structure analysis

Advanced analysis

Annotate to the database

Interaction network analysis


For single cell RNA-seq bioinformatics analysis, if the read length of the original sequencing data is PE100, alternative splicing analysis can be performed. In addition, if you have other needs, such as upload raw data to the database, network analysis of key driver genes, and time series analysis, we will provide appropriate biological information analysis content according to your needs. For analysis content, price, cycle, if you have any questions, please click online inquiry.

How It Works

CD Genomics is a professional bioinformatics service provider with years of experience in NGS and long read sequencing (PacBio SMRT and Oxford Nanopore platforms) data analysis, integrated analysis services, database construction and other bioinformatics solutions.

How It Works

CD Genomics has successfully conducted single cell RNA-seq bioinformatics analysis on a variety of samples. If you are interested in our services, please contact us for more detailed information, and a CD Genomics representative is ready to answer your questions and get a complete understanding of your needs.

Reference

  1. Itay T, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science, 2016, 352(6282):189-196.
* For Research Use Only. Not for use in diagnostic procedures.
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