As a provider of 10x genomics single cell RNA-Seq data analysis, CD Genomics uses bioinformatics to help you explore the secrets of individuals biologically through cells. Our unique data analysis techniques will meet our customers' personalized data analysis needs. We provide a high-quality data analysis platform, a time-efficient analysis, and a high-quality study report.
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 as a whole, 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.
10x genomics single cell RNA sequencing data bioinformatics analysis can reveal the unique gene information and gene expression characteristics of each cell at the single cell level, so that different cell types can be well distinguished, and the relationship between different types of cells can be studied and understood more deeply and systematically .This tool has greatly helped people understand life phenomena, study pathogenesis, discover diagnostic biomarkers and therapeutic targets, and provide researchers and clinical experts with new latitudes and perspectives.
Fig 1. GemCode single-cell technology enables 3‘ profiling of RNAs from thousands of single cells simultaneously.(Grace X.Y. Z, et al. 2017)
Application Field
10x genomics single cell RNA-Seq data analysis can be used, but is not limited to the following research.
Construction of cell maps of various tissues.
Research on pathogenic mechanism of disease.
Cancer and microenvironment research.
Immunology research.
Plant single cell research.
Neurobiology research.
Advantages of CD Genomics
Complete hardware.
Rich experience.
Strict quality control.
Professional bioinformatics analysis team.
High-quality project service.
CD Genomics Data Analysis Pipeline
Bioinformatics Analysis Content
10x genomics single cell RNA-seq bioinformatics analysis may discover novel cell types and provide insights into regulatory networks during development.CD Genomics will split the Barcode, UMI and Insert parts of reads according to the unique library structure of single-cell RNA-Seq, and then the insert parts will be compared to the reference genome for subsequent analysis.
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Standard analysis
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Sequencing data statistics
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Data quality control statistics
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Map to reference genome
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Comparison result statistics
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Gene expression analysis
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Marker gene identification
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Cell type annotation
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Cell type clustering analysis
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Difference analysis of specific marker gene
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Analysis of the same cluster gene between different samples
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GO annotation and enrichment of differentially expressed genes
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KEGG pathway analysis of cluster differentially expressed genes
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Cluster differentially expressed genes TF coding ability prediction
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Proteins interaction analysis of cluster differentially expressed genes
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cluster gene correlation network analysis
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Advanced analysis
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Cell trajectory analysis
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For other analyses, such as multi-sample integration analysis, correlation genotype and phenotype analysis, transcription rate analysis, cell type annotation, and cell communication network, please contact us by online inquiry and we will respond soon.
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 10x genomics single cell RNA-seq bioinformatics analysis on a variety of samples. Combined with rich project experience, strict data quality control, and professional analysis process, we will carry out your project accurately and quickly. Please contact us for more information and a detailed quote.
Reference
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Grace X.Y. Z, et al. Massively parallel digital transcriptional profiling of single cells. Nature Communications, 2017, 8:14049.
