GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics

Area of Science:

• Forensic Science
• Bioinformatics
• Genetics

Background:

• High-throughput sequencing (HTS) of single nucleotide polymorphisms (SNPs) offers advanced DNA forensics beyond traditional STR analysis.
• Large SNP panels for complex analyses like mixture deconvolution and ancestry prediction present computational challenges.

Purpose of the Study:

• To develop a tool, GrigoraSNP, that addresses the allele-calling bottleneck in HTS SNP analysis.
• To optimize the SNP calling module for large SNP panels used in forensic applications.

Main Methods:

• GrigoraSNP employs MapReduce parallel processing across multiple computational threads.
• A novel locus-identification hashing strategy using target sequence tags is utilized.
• The tool's performance is benchmarked against established pipelines like SAMtools and GATK.

Main Results:

• GrigoraSNP significantly reduces computational time for analyzing large SNP panels (>5000 loci).
• The tool's runtime scales linearly with the number of HTS reads, ensuring efficiency.
• It effectively removes a major computational bottleneck in forensic DNA analysis pipelines.

Conclusions:

• GrigoraSNP provides an optimized solution for rapid SNP calling in forensic HTS.
• The tool enhances the feasibility of using large SNP panels for diverse forensic applications.
• It represents a significant advancement in computational efficiency for forensic genomics.