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Published on: March 22, 2018
lobSTR: A short tandem repeat profiler for personal genomes
Melissa Gymrek1, David Golan, Saharon Rosset
1Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Genome Research
|April 24, 2012
Summary
We developed lobSTR, a new bioinformatics tool for analyzing short tandem repeats (STRs) in genomes. lobSTR offers faster and more accurate STR profiling from high-throughput sequencing data than existing methods.
Area of Science:
- Genomics
- Bioinformatics
- Computational Biology
Background:
- Short tandem repeats (STRs) are crucial in genetics, forensics, and genealogy.
- High-throughput sequencing (HTS) enables large-scale STR profiling, but current bioinformatics tools are inefficient.
- Existing methods use gapped alignment, leading to slow processing and biased allele sampling.
Purpose of the Study:
- To introduce lobSTR, a novel computational method for accurate and efficient STR profiling in personal genomes.
- To overcome the limitations of current bioinformatics pipelines for STR analysis using HTS data.
Main Methods:
- Developed lobSTR, a method leveraging signal processing and statistical learning to avoid gapped alignment.
- Implemented an end-to-end solution accepting raw sequencing reads and outputting genotyping results.
- Utilized C/C++ with multi-threading and BAM format compatibility for efficient processing.
Main Results:
- lobSTR demonstrates superior speed and reliability compared to mainstream STR profiling algorithms.
- Validation through biological replicates, Mendelian inheritance tracing, and comparison with traditional methods confirmed lobSTR's accuracy.
- A comprehensive survey of a personal genome revealed over 50,000 STR variations across approximately 100,000 loci.
Conclusions:
- lobSTR provides a significant advancement in STR profiling from HTS data.
- The tool's speed and accuracy enable large-scale analysis of STR variations and mutation dynamics.
- lobSTR is a robust, end-to-end solution for researchers in medical genetics, forensics, and genetic genealogy.
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