NGS-QC Generator

NGS-QC Generator assesses quality and technical similarity of next-generation sequencing (NGS) datasets by inferring quality descriptors from read distribution patterns across ChIP-seq and other enrichment-based technologies to support comparative and systems biology analyses.

Key Features:

• Quality descriptor inference: Infers quality indicators by analyzing the distribution of sequenced reads within NGS profiles to evaluate dataset quality.
• Enrichment-technology compatibility: Applicable to ChIP-seq and enrichment-related NGS technologies including RNA-seq, GRO-seq, DNase-seq, FAIRE-seq, MNase-seq, Hi-C, and ChIA-PET.
• Technical similarity assessment: Assesses technical similarity across NGS profiles to enable accurate comparative analyses in systems biology.
• Database integration: Integrates with the NGS-QC database (www.ngs-qc.org) containing quality control indicators for over 21,000 publicly available datasets for benchmarking and comparison.

Scientific Applications:

• Systems biology integration: Enables integration of multiple NGS readouts to support reconstitution of genome-regulatory functions.
• Protein–genome interaction analysis: Supports robust conclusions about functional protein–genome interactions from comparative ChIP-seq and related datasets.
• Chromatin and transcriptional studies: Applicable to analyses of transcriptional activity, chromatin accessibility, and three-dimensional chromatin organization (Hi-C, ChIA-PET).

Methodology:

The methodology comprises an assessment protocol to generate quality descriptors, procedures for report interpretation, and database exploration to compare datasets with publicly available data.