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DADEC

DADEC is a hybrid error correction tool specifically designed for long-read sequencing data. It combines multiple correction strategies to effectively reduce errors while preserving biological variations.

Current version: 1.0.1

Installation

Install from source code

To compile DADEC from source, follow these steps:

Clone the repository

  • git clone https://github.com/ZYMavis/DADEC.git
  • cd DADEC

Initialize and update submodules

  • git submodule update --init --recursive

Create and activate the conda environment

  • conda env create -f environment.yaml
  • conda activate DADEC

Build the executable

  • make all

Note: The conda environment will install all required dependencies. If you prefer to manage dependencies manually, please ensure all libraries listed in environment.yaml are available.

Usage

Running

Quick start

Run DADEC with default parameters:

bash

DADEC -s short_reads.fa -l long_reads.fa -t 16

-s : short reads file (FASTA format)

-l : long reads file (FASTA format)

-t : number of threads (default: 1)

See Parameters, the option DADEC --help and the subsections below for more information and options

Demo

Test the basic functionality using the provided sample data:

  • cd dataDemo
  • sh demo.sh

The demo script will run DADEC on a small dataset and output the corrected reads.

Parameters

  • s input short reads Format .fa
  • l input long reads Format .fa

All parameters below are optional.

  • t number of threads. (default: 1)
  • o output file name. Format .fa (default: DADEC.fa)
  • S number of splits for long-read files (default: 5)
  • r Haplotype filtering threshold for the step two correction (default: 0.08)
  • k k-mer size for the step one correction (default: 39)
  • K k-mer size for the step three correction (default: 39)
  • a Abundance threshold for the step one correction (default: 2)
  • A Abundance threshold for the step three correction (default: 1)
  • --stages correction stages to run in ascending order; accepts 1, 2, 3, or a comma-separated subset (default: 1,2,3)

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