At Ayugenixz, our NGS Variant Calling Services provide accurate and high-throughput identification of genetic variations from next-generation sequencing (NGS) data. We utilize advanced bioinformatics pipelines to detect SNPs (Single Nucleotide Polymorphisms), insertions/deletions (indels), and structural variants, enabling deep insights into genetic makeup, disease mechanisms, and therapeutic targets.

Our services are essential for clinical research, cancer genomics, rare disease diagnostics, pharmacogenomics, and population genetics.

Key Features of Our NGS Variant Calling Services:

•  Raw Data Preprocessing

High-quality filtering, adapter trimming, and quality control checks using tools like Fast QC and Trimmomatic.

•  Sequence Alignment

Accurate mapping of reads to reference genomes (e.g., GRCh38, mm10) using trusted aligners like BWA-MEM, Bowtie2, or STAR.

•  Variant Calling

Detection of variants using industry-standard tools such as GATK, Free Bayes, or Sam tools, with support for both germ line and somatic mutation calling.

•  Variant Annotation

Functional interpretation of variants using tools like ANNOVAR, SnpEff, or VEP, providing information on gene impact, clinical relevance, and population frequency.

•  Filtering and Prioritization

Application of customizable filters to prioritize high-confidence variants based on read depth, quality scores, allele frequency, and known pathogenicity.

•  Visualization and Reporting

Generation of user-friendly reports with variant summaries, genome browser visualizations (e.g., IGV), and interactive tables.

•  Custom Panel or Whole Genome/ Support

Compatible with targeted panels, or whole genome sequencing (WGS) data.

•  Optional Downstream Analysis

Including pathway enrichment, variant effect prediction, and disease association studies. With our robust bioinformatics expertise, Ayugenixz ensures high sensitivity and specificity in variant detection, supporting researchers and clinicians in understanding genetic variations and advancing precision medicine.