This pipeline is designed to complete circular bacterial genomes using a sampling strategy from a single MinION with barcoding.
To run with Docker
Since CCBGpipe implements many analytical tools, we strongly recommend you to run it with Docker. Alternatively, you can install all dependencies as listed in the Installation section.
git clone https://github.com/espirado/CCBGpipe.git
cd CCBGpipe
docker build -t "ccbgpipe:v1" ./
docker run -h ccbgpipe --name ccbgpipe -t -i -v /:/MyData ccbgpipe:v1 /bin/bash
Inside the Docker: root@ccbgpipe:/#
To install java:
apt-get update
apt-get install -y software-properties-common
add-apt-repository ppa:webupd8team/java
apt-get update && apt-get install oracle-java8-installer
Please note: the Oracle JDK license has changed starting April 16, 2019.
You can download zulu to include Java (https://www.azul.com/downloads/zulu/).
apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 0xB1998361219BD9C9
apt-add-repository 'deb http://repos.azulsystems.com/ubuntu stable main'
echo 'deb http://repos.azulsystems.com/debian stable main' > /etc/apt/sources.list.d/zulu.list
apt-get update
apt-get install zulu-8
Installation from source
cd /opt
git clone https://github.com/jade-nhri/CCBGpipe.git
cd CCBGpipe/CCBGpipe
chmod +x *.py
export PATH="$PATH:/opt/CCBGpipe/CCBGpipe/"
- [Albacore 2.1.7]
- Canu v1.6
- samtools 1.7
- BWA-0.7.17
- racon v1.1.1 -
- minimap 2.10 and miniasm v0.2
- nanopolish v0.9.0
- Graphmap v0.3.0
Before installing these dependencies it may be required to install some prerequisite libraries, best installed by a package manager. On Ubuntu theses are:
- cmake
- liblzma-dev
- libbz2-dev
- libz-dev
- libncurses-dev
- libcurl4-gnutls-dev
- libssl-dev
- make
- wget
- python3-all-dev
- parallel
- networkx
- pandas
- pyfastaq
- To extract fastq (joinedreads.fastq) and fast5 files using extract.py. Joinedreads.fastq and fast5 files are both produced in the directory (outpath/fast5/barcodeXX/).
extract.py path-to-raw_reads outpath (e.g., extract.py raw-reads albacore)
- To create a Run folder and enter it
mkdir Run && cd Run
- To get high-quality and long-length reads from joinedreads.fastq using runGetFastq.py
runGetFastq.py path-to-fast5 (e.g., runGetFastq.py ../albacore/fast5)
- To get miniasm assemblies using runmini.py
runmini.py
- To run canu with the sampling strategy by using runAssembly.py
runAssembly.py
- To run racon and nanopolish for consensus sequence generation using runConsensus.py with fast5 files
runConsensus.py path-to-fast5 (e.g., runConsensus.py ../albacore/fast5/)
- To get circular genomes by using finalize.py
finalize.py outpath (e.g., finalize.py ../results)
./opt/ont-guppy-cpu/bin/guppy_basecaller -i path to raw reads -s outputpath
- or
cd /opt/ont-guppy-cpu/bin
./guppy_bascaller
- To extract fastq files using guppy_bascaller
guppy_basecaller -i path-to-raw_reads -s outpath (e.g., guppy_basecaller -i Fast5 -s guppy_out)
- To de-multiplex
guppy_barcoder -i inpath -s outpath (e.g., guppy_barcoder -i guppy_out -s barcoding)
- To produce read_id list and joinedreads.fastq for each barcode
preprocess.py -b path-to-barcoding_summary.txt -s path-to-sequencing_summary.txt -o outpath (e.g., preprocess.py -b barcoding/barcoding_summay.txt -s guppy_out/sequencing_summary.txt -o outdir)
- To bin fast5 files into each barcode using filter_reads (a command from https://github.com/nanoporetech/fast5_research)
e.g., filter_reads --recursive --multi --workers 32 Fast5/ fast5/barcode01 outdir/barcode01/barcode01_readid.tsv
- With the data produced by the above process, you can perform CCBGpipe by beginning with creating a Run folder
mkdir Run && cd Run
runGetFastq.py path-to-fast5 (e.g., runGetFastq.py ../outdir/)
runmini.py
runAssembly.py
runConsensus.py path-to-fast5 (e.g., runConsensus.py ../fast5/)
finalize.py outpath (e.g., finalize.py ../results)