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.
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
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.
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Standard analysis
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Sequencing data statistics
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Remove adapter sequence and low-quality sequence
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Map to reference genome
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MRNA identification
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Quantitative analysis of mRNA
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MRNA differential expression analysis （more than two samples or groups）
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MRNA expression
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Differential gene clustering
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GO annotation and enrichment of differentially expressed genes
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KEGG pathway analysis of differentially expressed genes
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GO annotation and enrichment of differentially expressed genes
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mRNA structure analysis
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Advanced analysis
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Annotate to the database
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Interaction network analysis
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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 high-tech company specializing in multiomic data analysis. We provide services such as project design, data analysis, and database construction. With a focus on developing breakthrough products and services, we are a pioneer in the biotechnology industry, serving researchers and partners worldwide.
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
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Itay T, et al. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science, 2016, 352(6282):189-196.
