In this project, I developed a versatile VCF (Variant Call Format) data processor tailored for genomic analysis. The processor efficiently reads and filters large-scale genomic datasets, extracting relevant variant information. Leveraging Node.js and various libraries, the processor filters variants based on position, read depth, and specific sample attributes. It also enriches data by querying a genomics API to gather gene-related insights for each variant. The processed data is organized into individual output files for each sample, ensuring data integrity.
- Developed a versatile VCF data processing tool using Node.js, readline interface, and axios for API requests.
- Implemented dynamic filtering based on variant position and read depth, catering to specific sample requirements.
- Utilized efficient caching techniques to optimize retrieval of gene information from the genomics API.
- Designed a CSV conversion function for streamlined organization and storage of processed data for subsequent analysis.