Skip to content
/ ptgaul Public

chloroplast genome assembly using long reads data

Notifications You must be signed in to change notification settings

Bean061/ptgaul

Repository files navigation

PlasTid Genome Assembly Using Long reads data (ptGAUL)

===========================================================================
                       _____           _        _         _    _
    ___      _       /  ___  \       / _ \     | |       | |  | |
   / _ \    | |     / /     \ \     / / \ \    | |       | |  | |
  / / \ \ __| |__  | |       \_|    / / \ \    | |       | |  | |
  ||   |||__   __| | |             / / _ \ \   | |       | |  | |
  | \_/ /   | |    | |      ___    /  ___  \   | |       | |  | |
  |  __/    | |_   | |     |__ |  / /     \ \  \ \       / /  | |        _
  | |       |   |   \ \ ___ / /   / /     \ \   \ \ ___ / /   | | _____ | |
  |_|       |__/     \ _____ /   /_/       \_\   \ _____ /    | _________ |

===========================================================================

This pipeline is used for plastid (chloroplast) genome assembly based on long read data, including both Nanopore and PacBio. It can easily help assemble the complex plastomes with many long repeat regions which cannot be addressed by short read data only. Short reads assembly can sometimes generate many paths due to the long repeat regions (e.g. Juncus). This pipeline is very straitforward with two mendatory arguments (reference and raw long-read data). It usually takes about 10 minutes to assemble a plastome with 16Gb memory and less than 10Gbp sequence data. Our paper is in prep. [Zhou et al. (unpublished)]. We introduced this pipeline in BAGGs workshop at UNC-Chaple Hill.

Latest updates

ptGAUL 1.0.5 release (Feb 9, 2023)

  • New options for ptGAUL: -o output directory; -g genome size; -c coverage.
  • New argument for python script: -o output directory.
  • Fixed the combine_gfa.py, which can be run automatically.

ptGAUL 1.0.4 release (Oct 31, 2022)

  • First version.

Installation

Create a conda environment

conda create --name chloroplast python=3.7
source activate chloroplast

Use conda to install.

conda install -c bioconda ptgaul
ptGAUL.sh -h

Environment

Examples can be applied on Linux and Mac.

Quick run

The basic arguments in ptGAUL.sh are 1) -r: a plastome from a closely related species (it should work for the references either from the same genus or the same family) and 2) -l: your long read data (any seuquence file in fasta, fastq, and fq.gz format).

If you run 1.0.4 version, the command in the ptGAUL_version directory. Otherwise, combine_gfa.py will not be able to run automatically.

ptGAUL.sh -r [PATH]/[reference_genome]/ -l [PATH]/[long_read_data]

EXAMPLE

The command for the example data.
ptGAUL.sh -r /path/Beta.fasta -l /path/SRR1980665.1 -t 8 -f 3000 -o ./ptgaul/

To check all parameters in ptGAUL using:

ptGAUL.sh -h
Parameters in details
Usage: ptGAUL.sh -r (REFERENCE FILE) -l (LONG READ FILE)

                 [-t threads int] [-g genome size int]
                 [-c coverage int] [-f filter threshold int]
                 [-o output directory string]

this pipeline is used for plastome assembly using long read data.

optional arguments:
-h, --help            <show this help message and exit>
-r, --reference       <MANDATORY: reference contigs or scaffolds in fasta format>
-l, --longreads       <MANDATORY: raw long reads in fasta/fastq/fq.gz format>
-t, --threads         <number of threads, default:1>
-g, --genomesize      <expected genome size of plastome (bp), default:160000>
-c, --coverage        <a rough coverage of data used for plastome assembly, default:50>
-f, --filtered        <the raw long reads will be filtered if the lengths are less than this number (bp); default: 3000>
-o, --outputdir       <output directory of results, defult is current directory>

Check your results before using it

If the edge number does not equal 1 or 3 with abnormal plastid length, You should manually check the assembled data using BANDAGE. When you confirm the edges are three, you can manually run the python script again to get the assembly results including two paths.

combine_gfa.py -e ./PATH_OF_EDGES_FILE/edges.fa -d ./PATH_OF_SORTED_DEPTH_FILE/sorted_depth -o ./

(Optional) Final assembly polish using long reads data

This step will improve your assembly a little, but not too much. Using short reads is highly recommended (see as follows).

install racon using conda.

minimap2 -x ava-ont -t $n $asm $nanopore > ${racon_outdir}/map.paf
racon -t $n $nanopore_fq ${racon_outdir}/map.paf $asm > ${racon_outdir}/asm.racon.fasta

(Optional) Final assembly polish using short reads data

Software for polishing step (this needs a separate python2 environment)

  1. ropebwt2 or use conda to install.
check if ropebwt2 is installed successfully by typing "ropebwt2 -h" in terminal.
  1. msbwt or use conda to install.
check if msbwt is installed successfully by typing "msbwt -h" in terminal.
  1. fmlrc or use conda to install. Use the fmlrc instead of fmlrc2.
check if fmlrc is installed successfully by typing "fmlrc -h" in terminal.

Highly recommended steps: use fmlrc for polishing step. It outperforms other polishers.

files illumina_* are the fq.gz file of illumina reads. Change the output path directory "/PATH/msbwt".

gunzip -c $illumina_1r1 $illumina_1r2 $illumina_2r1 $illumina_2r2 | awk 'NR % 4 == 2' | sort | tr NT TN | ropebwt2 -LR | tr NT TN | msbwt convert /PATH/msbwt

Once you finished msbwt run. $N means thread number. $assembled_cp is assembled plastome from ptGAUL. Change the output path of "/PATH/fmlrc/corrected.fasta"

fmlrc -p $N /PATH/msbwt/comp_msbwt.npy $assembled_cp /PATH/fmlrc/corrected_cp.fasta

Citation

(in prep.) Zhou et al., Plastid Genome Assembly Using Long-read data (ptGAUL). DOI: 10.1101/2022.11.19.517194

If you are using fmlrc, please cite Wang, Jeremy R. and Holt, James and McMillan, Leonard and Jones, Corbin D. FMLRC: Hybrid long read error correction using an FM-index. BMC Bioinformatics, 2018. 19 (1) 50.

About

chloroplast genome assembly using long reads data

Resources

Stars

Watchers

Forks

Packages

No packages published