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ecc_finder

A robust and accurate detection tool to detect eccDNA using Illumina and ONT sequencing

Table of Contents

Introduction

ecc_finder is dedicated to

  1. identify eccDNA from Nanopore reads;
  2. identify eccDNA from from Illumina paried end short reads;
  3. provide bona fide locus boundary of eccDNA-producing loci to investigate the origins of eccDNAs.

ecc_finder works well on eccDNA-seq data (either mobilome-seq, Circle-Seq and CIDER-seq) from Arabidopsis, human, and wheat (with genome sizes ranging from 120 Mb to 17 Gb).

Validation

  1. To access ecc_finder accuracy for long read, the confidence score is assigned by tandem repeat pattern from read alignment. Except for satellites, when performing self-alignment, linear reads will not repeat itself while circular reads will be repeated two or more times because it goes through the rolling circle amplification experimentally. Therefore, the circular sequence will have a sub- read alignment in the same direction, and this sub-read alignment will be repeated two or more times on the same boundary.

  2. To access ecc_finder accuracy for short read, the confidence score for the eccDNA locus is assigned to the bona fide locus with an even distribution of split and discordant reads throughout their internal region.

ecc_finder_pipeline

Getting Started

Quick installation using conda

#Step 1. Download the latest ecc_finder:

git clone https://github.com/njaupan/ecc_finder.git

#Step 2. Go to ecc_finder folder

cd ecc_finder

#Step 3. Find the yaml file in the folder and run :

##For Linux64 system:

conda env create -f ecc_finder.yaml

##For MacOS system:

conda env create -f ecc_finder_MAC.yaml

conda activate ecc_finder

Video about how to install and run ecc_finder

You can watch this video: ecc_finder_install_Video about the installation and usuage of ecc_finder, which takes 2 minutes to install on a Mac.

Index

# before starting, create index file for the reference genome to reduce mapping time.

# Long reads: 
minimap2 -x map-ont -d reference.ont.idx reference.fa -I 4G 

# Short reads:
# You can choose minimap2 short read mapping mode to speed up given a large genome 
# build index accordingly

bwa index reference.fa 

minimap2 -x sr -d reference.sr.idx reference.fa -I 4G

Usage

ecc_finder: Tool for detecting eccDNA loci using Illumina and ONT sequencing.
Version: v1.0.0

usage: python ecc_finder.py <command> [options]
    
    Mapping mode:
      map-sr         Call candidate eccDNA loci from paired-end short reads
      map-ont        Call candidate eccDNA loci from Nanopore long reads
    
    Assembly mode:
      asm-sr         Assembly from paired-end short reads
      asm-ont        Assembly from Nanopore long reads
      
    options:
      -v, --version

Docs

Please see the Wiki for detailed documentation.

Long-read-mapping

Algorithm and usage in details, please see the Long-read-mapping

Run Example1: watch the video Long-read-mapping_Video_example using the Arabidopsis eccDNA sequencing subsample in the folder test_samples.

usage: python ecc_finder.py map-ont <reference.idx> <query.fq> -r reference.fasta (option)

Short-read-mapping

Algorithm and usage in details, please see the Short-read-mapping

Run Example2: watch the video Short-read-mapping_Video_example using the Arabidopsis eccDNA sequencing subsample in the folder test_samples.

Note that because the output from bwa index, it will create 5 files with appendix: reference.fa.bwt, reference.fa.amb, reference.fa.ann, reference.fa.pac and reference.fa.sa

So the <reference.fa> here represents the whole index output for bwa aligner, and "-r reference.fa" represents the reference fasta file

usage: 

python ecc_finder.py map-sr <reference.fa> <query.fq1> <query.fq2> -r reference.fa (option)

or to speed up:

python ecc_finder.py map-sr <reference.sr.idx> <query.fq1> <query.fq2> -r reference.fa --aligner minimap2 (option)

Long-read-assembly

Algorithm and usage in details, please see the Long-read-assembly

Run Example3: watch the video Long-read-assembly_Video_example using the Arabidopsis eccDNA sequencing subsample in the folder test_samples.

usage: python ecc_finder.py asm-ont <query.fq> (option)

Short-read-assembly

Algorithm and usage in details, please see the Short-read-assembly

Run Example4: watch the video Short-read-assembly_Video_example using the Arabidopsis eccDNA sequencing subsample in the folder test_samples.

usage: python ecc_finder.py asm-sr <query.fq1> <query.fq2> (option)

Output

All output is in eccFinder_output for mapping, eccFinder_asm_output for assembly, or whichever directory -o specifies.

Overview

Col Type Description
1 folder Folder containing alignment files (align_files)
2 folder Folder containing peak calling files (peak_files)
3 file CSV file of the eccDNA loci: ecc.{ont,sr}.csv
4 file FASTA file of the eccDNA sequence: ecc.{ont,sr}.fasta
5 file BED file of genomic enriched sites: ecc.{ont,sr}.site.bed
6 file Plot of the size distribution: ecc.{ont,sr}.distribution.png

**ecc.{ont,sr}.fasta **

The eccDNA sequence in FASTA format.

**ecc.{ont,sr}.csv **

The eccDNA locus in csv format.

Col Type Description
1 string Reference sequence name
2 int Reference start on original strand
3 int Reference end on original strand
4 int Circular read number at the locus
5 int Repeat units of all circular reads
6 int EccDNA sequence length

ecc.{ont,sr}.distribution.png

The Size distribution of detected eccDNA in png format.

Size_distribution

Example

#PRJEB46420 https://www.ebi.ac.uk/ena/browser/view/PRJEB46420?show=reads

  • Arabidopsis thaliana under heat stress
  • Triticum aestivum

Citation

Panpan Z, Haoran P, Christel L, Etienne B, Marie M. Ecc_finder: a robust and accurate tool for detecting extrachromosomal circular DNA (eccDNA) from sequencing data (https://www.frontiersin.org/articles/10.3389/fpls.2021.743742/abstract)