Platform & pipeline — how it actually works.

ℹ️ Note: ATGC Flow is designed to support research and clinical workflows. Variant interpretations generated by automated tools should always be reviewed by a qualified geneticist or genetic counselor before being used to guide clinical decisions.

Platform Overview

ATGC Flow is a whole exome sequencing analysis platform that integrates industry-standard bioinformatics methodology within an automated pipeline to process paired-end FASTQ files through alignment, variant calling, and comprehensive annotation. The platform is designed for research use, with automated ACMG/AMP 2015 variant classification to support — not replace — expert review.

New to WES analysis? Our Genomics Knowledge Base covers the concepts behind every stage of this pipeline, and the Publications & References page lists the peer-reviewed methodology each stage is built on.

Technical Approach

Automated Pipeline

Scalable workflow management for reproducible bioinformatics analysis with automatic parallelization and resource optimization.

Multi-Step Processing

Quality control → alignment → base quality recalibration → variant calling → multi-source annotation.

Comprehensive Annotation

Variant effect prediction, functional annotation, population frequency data, and functional pathogenicity prediction scores.

ACMG Classification

Automated variant classification following ACMG/AMP 2015 guidelines with evidence-based scoring and clinical interpretation support.

Reference Genome & Databases

Reference Genome: GRCh38/hg38 (Genome Reference Consortium Human Build 38)

Known Variants: Curated known-indel reference sets used for base quality recalibration

Annotation Databases: Population frequency, functional prediction, and clinical significance knowledge bases

Gene Panels: Curated disease gene panel sources, ACMG SF v3.2 secondary findings genes

Pipeline Specifications

Input Requirements

  • • Paired-end FASTQ files (.fastq.gz)
  • • Whole exome sequencing data
  • • Minimum 50x mean coverage recommended
  • • Illumina platform supported

Output Files

  • • BAM file with BQSR (indexed)
  • • Raw VCF (gzipped & indexed)
  • • Fully annotated VCF
  • • Filtered TSV with functional annotations

Limitations & Considerations

Current Limitations

  • • Automated ACMG classifications require expert review before clinical reporting
  • • Optimized for Illumina paired-end WES data; WGS and targeted panels require configuration adjustments
  • • Structural variant detection is under active development
  • • Requires bioinformatics expertise for advanced result interpretation
  • • Processing time varies with compute resources and sample coverage depth

Future Enhancements

  • • Clinical validation studies
  • • Enhanced variant filtering options
  • • Structural variant detection
  • • Pharmacogenomics annotations
  • • Export to standard formats (HGVS, VCF 4.3)
  • • Batch processing for cohort analysis

Pipeline Performance

2-4 hours
Total processing time
~80,000
Variants per exome
20+
Annotation sources