ECCFP - EccDNA Caller based on Consecutive Full Pass

A software package for identifying eccDNAs in the ONT sequencing data of RCA-amplified eccDNA

Introduction

ECCFP utilizes all consecutive full passes to determine accurate eccDNA positions and generate consensus sequences, based on rolling circle amplification and nanopore sequencing.

Reference

ECCFP is optimized from the Flec software.

• eccDNA_RCA_nanopore

Dependency (python packages)

• numpy
• pandas
• pyfaidx
• pyfastx
• Biopython

Installation

git clone https://github.com/WSG-Lab/ECCFP.git
cd ECCFP
pip install .

Usage

simple usage

eccfp --fastq input.fastq --paf mapping.paf --reference ref.fa -o output

Parameter

usage: eccfp.py [options]

options:
  -h, --help            show this help message and exit

  Generate candidate eccDNA from rolling circle reads:

  --fastq FASTQ         input reads in fastq format
  --paf PAF             input alignments in PAF format
  --reference REFERENCE
                        reference genome sequences in fasta format
  --output OUTPUT, -o OUTPUT
                        output folder, the default is the current folder
  --maxOffset MAXOFFSET
                        maximum offset of start/end positions between two sub-reads to be considered as mapping to the same location, default is 20
  --minMapQual MINMAPQUAL
                        minimum mapping quality of sub-reads, default is 30

  Get accurate eccDNA location from candidate eccDNA:

  --fluctuate FLUCTUATE
                        maximum offset between the candidate eccDNA and the candidate eccDNA in a group, default is 20bp
  --nf NF               minimum number of fullpass to support candidate eccDNA, default is 2
  --cov COV             minimum fullpass used for merging a set of candidate eccDNA, default is 1
  --nc NC               minimum number of candidate eccDNA required to merge overlapped candidate eccDNAs, default is 2

  Generate consensus sequences and variants:

  --minDP MINDP         minimum depth to call variants, default is 4
  --minAF MINAF         minimum alternative allele frequency to call variants, default is 0.75

Example

cd example
minimap2 -cx map-ont ref.fa example.fastq --secondary=no -t 8 -o mapping.paf
eccfp --fastq example.fastq --paf mapping.paf --reference ref.fa -o output

Output

Five files are generated following the completion of the pipeline: unit.txt and candidate_consolidated.txt(intermediate files), final_eccDNA.txt, consensus_sequence.fasta, and variant.txt (result files).

file	details
unit.txt	full pass alignment details for all candidate eccDNAs detected in reads
candidate_consolidated.txt	the consolidating steps used to derive accurate eccDNAs from the candidate eccDNAs
final_eccDNA.txt	accurate eccDNA information
consensus_sequence.fasta	the consensus sequences of accurate eccDNAs
variants.txt	variant profiles specific to these accurate eccDNAs

Example final_eccDNA.txt file

eccDNApos	Nfullpass	Nfragments	Nreads	refLength	seqLength
chr16:757924-758274(+)	4	1	1	351	350
chr1:21828265-21828439(+)|chr7:132167689-132167880(+)	24	2	2	367	367

	description
eccDNApos	eccDNA position
Nfullpass	Number of consecutive full pass for this eccDNA covered by all reads
Nfragments	Number of fragment that form this eccDNA
Nreads	Number of reads identified for the eccDNA
refLength	The length of reference genome that this eccDNA
seqLength	The length of consensus sequence that this eccDNA

variants.txt file

	description
col1	chromsome
col2	position in the reference genome
col3	reference base
col4	variant
col5	supportive coverage depth
col6	total coverage depth
col7	type
col8	eccDNApos

Citation

Zhang, T. et al. ECCFP: a consecutive full pass based bioinformatic analysis for eccDNA identification using Nanopore sequencing data. bioRxiv 2025.05.13.653627 (2025) doi:10.1101/2025.05.13.653627.