As one of the full-length transcriptome sequencing data analysis providers, CD Genomics uses bioinformatics to help you accurately reconstruct the whole picture of the transcriptome. Our unique data analysis skills will exceed customers' expectation on personalized data analysis. We provide a high-quality data analysis platform, a fast analysis cycle, and a high-quality result report.
Introduction of Full-length Transcriptome
Full-length transcriptome research is an important way to understand the functions of biological organisms. Traditional next-generation transcriptome sequencing cannot directly obtain the entire sequence of a single RNA molecule from 5' to 3'. The transcriptome research based on the PacBio three-generation sequencing platform, without interruption, directly read the full-length reverse transcribed cDNA, can effectively obtain the entire sequence of high-quality single RNA molecules. Because no assembly is required, outcome obtained from the transcriptome sequencing is more precise.
Using biological information analysis to analyze the full-length transcriptome sequencing data can more accurately distinguish the isoforms, homologous genes, superfamily genes or alleles that cannot be recognized by second-generation sequencing. In addition, for non-reference genome species, the problems of short transcript splicing and incomplete information can be overcome. Then accurately construct the whole picture of the species transcriptome and provide the data basis for the follow-up scientific research.
Fig 1. Maize PacBio Iso-Seq barcoding library and comparison of isoforms between RefGen_v3 and PacBio data. (Wang B , et al. 2016)
Application Field
Construct high-quality gene sets for species without reference sequences, and lay the foundation for subsequent functional studies of species.
Complete reference gene sets for species with reference sequences and identify structural variations such as alternative splicing and gene fusion.
Auxiliary gene annotation.
Advantages of CD Genomics
An experienced data 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 provide different analysis strategies for sequencing data with and without reference genomes. The following table shows the full-length transcriptome analysis items with reference genomes and without reference genomes.
| Sequencing data with reference genomes |
Data quality control |
| Transcript classification |
| Transcript clustering and correction |
| Compare with reference genome |
| Perform variable shear analysis |
| New gene prediction |
| Fusion gene analysis |
| Quantitative analysis |
| Protein coding box prediction |
| SSR analysis |
| lncRNA prediction |
| Functional Analysis |
| Sequencing data without reference genomes |
Data quality control |
| Transcript classification |
| Transcript clustering and correction |
| Transcript database notes |
| Quantitative analysis |
| lncRNA prediction |
| CDS prediction |
| SSR analysis |
We will provide personalized custom analysis for full-length transcriptome sequencing data analysis. For analysis content, price, cycle, or any other 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 provides general analysis and customized analysis of full-length transcriptome sequencing data analysis. Experienced teams of scientists, researchers, and technicians, we provide fast turnaround, high-quality data reports at competitive prices for worldwide customers. Customers can contact our scientists directly and we will provide prompt response. If you are interested in our services, please contact us for more detailed information.
Reference
- Wang B , et al. Unveiling the complexity of the maize transcriptome by single-molecule long-read sequencing[J]. Nature Communications, 2016, 7:11708.
