isoCNV

isoCNV optimizes DECoN parameters to improve copy number variant (CNV) detection from targeted sequencing (TS) and whole-exome sequencing (WES) data using only next-generation sequencing (NGS) information.

Key Features:

• DECoN parameter optimization: Adjusts DECoN algorithm parameters to increase CNV detection sensitivity in TS and WES datasets.
• NGS-only workflow: Performs optimization and validation using only NGS data without requiring MLPA or array comparative genomic hybridization (aCGH).
• In silico validated CNV dataset: Builds an in silico validation set from overlapping CNV calls produced by CNVkit, panelcn.MOPS, and DECoN.
• Sensitivity improvement: Demonstrates increased sensitivity compared with unoptimized DECoN on real TS and WES datasets.
• Analysis-ready outputs: Produces CNV calls calibrated for consistent experimental conditions to be used directly in downstream analyses.

Scientific Applications:

• CNV detection in TS and WES: Enhances detection of germline CNVs from targeted sequencing and whole-exome sequencing data.
• Algorithm calibration: Provides a method to calibrate DECoN parameters for specific experimental setups and sequencing platforms.
• In silico benchmarking: Generates in silico validated CNV sets for benchmarking and comparative evaluation of CNV-calling methods.

Methodology:

Optimizes DECoN parameters using NGS data and an in silico validated CNV dataset derived from overlapping calls of CNVkit, panelcn.MOPS, and DECoN, and evaluates performance on real TS and WES datasets by measuring sensitivity.