REPdenovo

REPdenovo: Reference-free repeat sequence assembly from raw shotgun reads

REPdenovo assembles repetitive DNA sequences directly from raw shotgun sequencing data without reliance on reference genomes, enabling reconstruction of highly repetitive, low-divergence, and long repeat regions from short-read data.


Key Features:

  • Direct Assembly from Raw Data: Operates on raw shotgun sequencing reads without using pre-existing reference genomes.
  • Handling Highly Repetitive and Divergent Sequences: Constructs diverse repeat types, including highly repetitive and low-divergence sequences in complex genomes.
  • Reconstruction of Long Repeats: Reconstructs long repeat sequences from short reads, capturing extensive repetitive regions.
  • Improved Completeness and Quantity: Recovers repeat sequences with higher completeness and yield than existing assembly methods.

Scientific Applications:

  • Genome Annotation: Improves genome annotation by enabling identification and integration of previously unrecognized repetitive elements.
  • Evolutionary Studies: Supports discovery and comparative analysis of repeat sequence incorporation across genomes, including parasites.
  • Host-Derived Repeat Sequences in Parasite Genomes: Detects repeat sequences in human sequencing data that are also present in parasite genomes, indicating persistence linked to host DNA filtering during sequencing.

Methodology:

Applies a novel algorithmic strategy to assemble repeat sequences directly from raw shotgun reads, addressing challenges associated with repetitive regions and sequence divergence in conventional genome assembly pipelines.

Topics

Details

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

Operations

Publications

Chu C, Nielsen R, Wu Y. REPdenovo: Inferring De Novo Repeat Motifs from Short Sequence Reads. PLOS ONE. 2016;11(3):e0150719. doi:10.1371/journal.pone.0150719. PMID:26977803. PMCID:PMC4792456.

Documentation

Links