AlmostSignificant

AlmostSignificant aggregates quality metrics and sequencing-run metadata to support quality control of Illumina high-throughput sequencing data.

Key Features:

• Data Aggregation and Integration: Consolidates multiple quality metrics from diverse sources into a unified dataset, including run-specific and sample-associated metrics.
• Comprehensive Metadata Management: Stores additional run and sample metadata beyond standard QC metrics to enhance traceability and reproducibility.
• Run-level Monitoring and Management: Facilitates monitoring and management of sequencing runs by retaining and linking quality metrics with run and sample information.
• Scalability and Efficiency: Scales to large projects and has been used to track over 80 sequencing runs encompassing more than 2,500 samples over a three-year period.

Scientific Applications:

• Quality Monitoring: Enables continuous assessment of sequencing data quality across multiple Illumina runs to inform downstream analyses.
• Data Management: Centralizes QC metrics and associated metadata to support organization and long-term tracking of sequencing projects.
• Research Reproducibility: Retention of detailed run and sample metadata supports reproducibility and traceability of genomic analyses.

Methodology:

Collects quality metrics from various sources associated with sequencing runs and aggregates those metrics together with comprehensive run and sample metadata.