TIARA

TIARA integrates short-read next-generation sequencing (NGS) and ultra-high-resolution comparative genomic hybridization (CGH) array data to archive personal genomic datasets for detection and characterization of single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), and structural variants (SVs).

Key Features:

• Comprehensive data integration: Archives individual genomes from next-generation sequencing (NGS) and ultra-high-resolution comparative genomic hybridization (CGH) arrays to combine complementary data types.
• Variant detection capabilities: Detects and characterizes single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), and structural variants (SVs) using integrated NGS and CGH signals.
• Quantitative signal storage: Stores NGS read-depths and CGH log2 ratios as feature-level data for quantitative analysis.
• Data content: Contains archived genomes from 36 individuals, including raw short reads and feature-level CGH data.
• Scalability: Designed to accommodate incorporation of additional personal genomes as more samples are analyzed by NGS or CGH arrays.

Scientific Applications:

• Personalized genomics: Supports interpretation of individual genetic profiles through integrated variant calls and quantitative signals.
• Cross-platform comparison: Enables comparison of genomic datasets across NGS and CGH array techniques to improve variant identification.
• Variant discovery and characterization: Facilitates identification and characterization of genomic variations that may underlie phenotypic differences or disease susceptibility.

Methodology:

Integrates next-generation sequencing (NGS) short-read data with ultra-high-resolution comparative genomic hybridization (CGH) array feature-level signals (including read-depths and log2 ratios) to enable precise detection and characterization of SNPs, indels, and structural variants.