Whole Genome Sequencing (WGS) Bioinformatics Analysis

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High-throughput next-generation sequencing (NGS) technologies have reshaped the scope of genomics research in many diseases, especially in cancers. Based on our high-throughput SuPrecision™ platform, Creative Biolabs has accumulated extensive experience in whole genome sequencing (WGS) (WGS) and we have explored a powerful pipeline for large-scale WGS data analysis. We are pleased to tailor the most appropriate strategies to meet every unique need of our global clients.

Whole Genome Sequencing (WGS) Bioinformatics Analysis

High-Accuracy Bioinformatics Tools is Needed for WGS Data Analysis

Patients with a family history of cancer are being evaluated with single-gene or gene panel tests. Recent explosive advances in NGS technology and computational approaches to massive data enable us to analyze a number of cancer genome profiles by WGS. The decreasing cost and potential to provide comprehensive genetic risk assessment make WGS an attractive tool for understanding the genetic risk for cancer. Technical improvements have decreased sequencing costs while the size and number of genomic datasets have increased rapidly. The growing clinical use of WGS will require large-scale efforts to consolidate WGS results with clinical data to improve the accuracy of interpretation of rare variants and to determine optimum management strategies. The expanding volume of data has enabled the rapid adoption of WGS to enhance drug research and development. This leads to a significant increase in the need for computational methods and bioinformatics tools.

Whole Genome Sequencing (WGS) Bioinformatics Analysis Fig.1 WGS by NGS can detect non-coding mutations, structural variants (SVs) including somatic copy number alterations (SCNAs) and translocations, and pathogen detection, as well as protein-coding mutations (Nakagawa et al. 2015).

WGS Bioinformatic Analysis at Creative Biolabs

Scientists from Creative Biolabs have developed a powerful pipeline for cancer WGS bioinformatic analysis with high accuracy. Our in-house pipeline has the capacity to process genomic data from large-scale subjects. Our strategy focuses on identifying genetic variations from WGS data. The genetic variants analysis pipeline consists of 1) quality control of raw data, 2) production of the clean data, 3) unspliced mapping of the clean data onto a reference genome, 4) post-alignment processing, 5) quality control of the mapped reads, 6) variant calling, annotation and prioritization.

Key Features and Advantages of WGS Bioinformatic Analysis Service Include but Are Not Limited to:

  • Large-scale WGS data analysis
  • Rich experience in cancer WGS data analysis
  • High accuracy and high-throughput
  • Highly professional Ph.D. level scientists
  • Fast turnover time
  • Competitive and affordable price

With years of research and development experience in the field of deep sequencing, Creative Biolabs has accomplished over hundreds of WGS projects. Our seasoned scientists can provide the best service of large-scale WGS data analysis at the most competitive cost.

Please contact us for more information and a detailed quote.

Q&As

Q: What are the main features of WGS Bioinformatics Analysis?
A: Key features include high-throughput sequencing, comprehensive variant detection, structural variant analysis, and functional annotation. These features enable detailed genetic profiling, facilitating the discovery of biomarkers and therapeutic targets.
Q: How does WGS improve the accuracy of disease models?
A: WGS provides a complete genetic profile, allowing for the identification of specific genetic mutations and variations that contribute to disease. This detailed information enhances the accuracy of disease models, leading to better understanding and treatment strategies.
Q: What bioinformatics tools are used in WGS analysis?
A: Bioinformatics tools used in WGS analysis include sequence alignment software, variant calling algorithms, and annotation tools. These tools process and interpret genomic data, enabling the identification of genetic variations and their potential impact on health and disease.
Q: How can WGS Bioinformatics Analysis be applied to cancer research?
A: WGS Bioinformatics Analysis can identify somatic mutations, structural variations, and copy number alterations in cancer genomes. This information helps researchers understand the genetic basis of cancer, discover new therapeutic targets, and develop personalized treatment strategies based on the tumor's genetic profile.
Q: What is the role of functional annotation in WGS Bioinformatics Analysis?
A: Functional annotation involves linking genetic variants to biological functions and pathways. In WGS Bioinformatics Analysis, this step is crucial for understanding the impact of identified genetic variants on disease processes, helping researchers prioritize variants for further study and therapeutic development.

Reference

  1. Nakagawa, H.; et al. Cancer whole-genome sequencing: present and future. Oncogene. 2015, 34(49):5943-50.

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Note: Our sequencing services are for Research Use Only. Not For Clinical Diagnosis.
Related Services:
  1. WES Bioinformatic Analysis
  2. Targeted Sequencing Bioinformatics Analysis
  3. WTS Bioinformatics Analysis
  4. SuPrecision™ Pipeline for Immune Repertoire Analysis
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