Hobbes

Hobbes maps next-generation sequencing (NGS) DNA reads and identifies all possible mapping locations to improve accuracy in applications such as ChIP-seq and RNA-seq.


Key Features:

  • Comprehensive Mapping: Unlike Bowtie and BWA that prioritize top candidate mappings, returns all potential mapping positions for each read to enable detection in repeat regions.
  • Efficiency and Speed: Leverages additional prefix q-grams for enhanced filtering during read mapping, achieving up to an order of magnitude speedup over state-of-the-art mappers while maintaining similar accuracy.
  • Resource Optimization: Memory-efficient implementation that consumes less space compared to competing tools, suitable for large-scale genomic studies.
  • Versatile Read Handling: Supports short and long reads, single-end and paired-end configurations, and multithreading across multiple CPU cores.
  • Algorithmic Precision: Handles sequence variation using Hamming distance for substitutions and edit distance for substitutions, insertions, and deletions.
  • Open Source Availability: Implemented in C++ with source code freely available.

Scientific Applications:

  • ChIP-seq binding-site discovery: Enables identification of binding sites within repeat regions by reporting all possible read mappings.
  • RNA-seq transcript abundance estimation: Improves transcript abundance estimates by providing comprehensive mapping of reads across transcripts.
  • Large-scale NGS projects: Suited for high-throughput studies that require memory-efficient, multithreaded mapping of short and long reads.

Methodology:

Uses additional prefix q-grams for read-filtering, supports Hamming and edit distance alignment models, returns all candidate mappings, and is implemented in C++ with multithreading support.

Topics

Details

Tool Type:
command-line tool
Operating Systems:
Linux
Programming Languages:
C++
Added:
8/3/2017
Last Updated:
11/25/2024

Operations

Publications

Kim J, Li C, Xie X. Improving read mapping using additional prefix grams. BMC Bioinformatics. 2014;15(1). doi:10.1186/1471-2105-15-42. PMID:24499321. PMCID:PMC3927682.

Documentation

Links