IntSIM

IntSIM simulates next-generation sequencing (NGS) reads for DNA variant discovery and tumor studies, modeling simultaneous germline and somatic variants and tumor-purity-dependent heterogeneous genomes.

Key Features:

• Simultaneous Germline and Somatic Variants: Simulates both germline and somatic variants within the same sequence to enable study of their combined effects in a single dataset.
• Tumor Purity Consideration: Incorporates tumor purity levels to generate reads that reflect heterogeneous genomes and produce realistic tumor–normal matched samples.
• Correlation Simulation Among Variants: Simulates correlations among single nucleotide polymorphisms (SNPs) and copy number variations/aneuploidies (CNVs/CNAs) using Hidden Markov Models (HMMs) trained on real sequencing data to represent broad and focal CNV/CNA events.

Scientific Applications:

• Variant detection benchmarking: Generates realistic NGS datasets to evaluate the performance of bioinformatics tools for detecting germline and somatic variants.
• Somatic mutation calling assessment: Enables assessment of somatic mutation identification under varying tumor purity conditions in tumor samples.
• Cancer genomics method development: Provides simulated data for developing and testing computational methods for CNV/CNA and SNP analysis in cancer studies.

Methodology:

IntSIM uses models derived from actual sequencing genomes and Hidden Markov Models trained on real sequencing data to simulate correlated SNPs and CNV/CNA events and to generate reads reflecting specified tumor purity and matched tumor–normal samples.