PEHaplo

PEHaplo is a de novo assembly tool for recovering virus haplotypes from virus quasispecies sequencing data. It utilizes overlap graph and paired-end information to recover virus haplotypes.

It requires paired-end reads file as input and outputs contigs that are part of or full haplotypes.

PEHaplo does not need any reference genomes and thus can be applied for identifying new haplotyps or haplotypes that are remotely related to characterized ones.

Quick Start

To quickly test the core assembly algorithm, we have prepared the procssed data set (after error correction, removing duplicates, reads orientation adjustment, etc.) in folder processed_test_data.

Required Dependencies

1. Install Python 2.7.x
2. Install Python module: networkx 1.11

cd networkx-1.11/  
sudo python setup.py install  

3. Apsp

cd Apsp/  
make  

Copy the compiled binary file Apsp to your path

Installation

PEHaplo was developed to run in Linux. To install:
git clone https://github.com/chjiao/PEHaplo.git

Running Example

cd PEHaplo  
mkdir assembly  
cd assembly  
python ../apsp_overlap_clique.py ../processed_test_data/Plus_strand_reads.fa ../processed_test_data/pair_end_connections.txt 180 250 600 210  

180: initial overlap threshold before merging cliques
250: read size
600: paired-end insert size
210: overlap threshold after merging cliques

Output:
Contigs.fa: the produced contigs
PEG_nodes_sequences.fa: the nodes sequences in the graph

The whole pipeline

Installing via conda

Noted that all the packages can be found on anaconda.cloud, which means you can easily install them by using conda. You can follow the Guaidance to install step by step.

Installing without using conda: required dependencies

1. Install Python 2.7.x
2. Install Python module: networkx 1.11
3. Install Karect, so that karect is in your path
4. Install Readjoiner, so that readjoiner is in your path
5. Install Apsp, so that Apsp is in your path
6. Install SGA, so that sga is in your path
7. Install Samtools, so that samtools is in your path

For contigs correction based on alignment:
Bowtie2 is required in your path

Usage

python pehaplo.py [-h] -f1 INPUT_F1 -f2 INPUT_F2 -l OVERLAP_LEN -r READ_LEN [-l1 OVERLAP_LEN1] [-F FRAGMENT_LEN] [-std FRAGMENT_STD] [-n DUP_N] [-correct CONTIG_CORRECT] [-t THREADS]

Arguments:

-f1 INPUT_F1 input .1 part of paired-end fasta file

-f2 INPUT_F2 input .2 part of paired-end fasta file

-l OVERLAP_LEN, --overlap_len OVERLAP_LEN overlap threshold between reads for overlap graph construction

-l1 OVERLAP_LEN1, --overlap_stage1 OVERLAP_LEN1 overlap cutoff to remove potentially error overlaps after merging linked cliques, default same as -l

-n DUP_N, --dup_n DUP_N keep the reads that are duplicated at least n times

-r READ_LEN, --read_len READ_LEN reads length

-F FRAGMENT_LEN, --fragment_len FRAGMENT_LEN paired-end reads insert size, default as 2.5*read_len

-std FRAGMENT_STD standard deviation of paired-end reads insert size, default as 100

-n DUP_N, --dup_n DUP_N the reads kept should be duplicated at least n times, default as keep all the duplicates removed reads

-correct CONTIG_CORRECT whether apply alignment based contigs correction(yes/no), default: no

-t THREADS, --threads THREADS threads for karect, sga, bowtie2

Test data and Running Examples

Use the test in folder raw_test_data/.
Example:

cd PEHaplo  
mkdir assembly  
python ../pehaplo.py -f1 ../raw_test_data/virus_1.fa -f2 ../raw_test_data/virus_2.fa -l 180 -l1 210 -r 250 -F 600 -std 150 -n 3 -correct yes

Output:
Contigs.fa: the raw output contigs
Contigs_clipped.fa: the contigs after error correction
PEG_nodes_sequences.fa: the nodes sequences in the graph