HIFI-SE
Project description
HIFI-barcode-SE400
The BGISEQ-500 platform has launched a new test sequencing kits capable of single-end 400 bp sequencing (SE400), which offers a simple and reliable way to achieve DNA barcodes efficiently. In this study, we explored the potential of the BGISEQ-500 SE400 sequencing in DNA barcode reference construction, meanwhile provided an updated HIFI-Barcode software package that can generate COI barcode assemblies using HTS reads of length >= 400 bp.
Manual
Versions
version 1.0.4 Python
- v1.0.4 2019-04-02 Fix a bug of "polish", and update the bold_identification module
- v1.0.3 2018-12-14 Fix a bug of "trim"
- v1.0.2 2018-12-10 Add "-trim" function in filter; accept mismatches in tag or primer sequence, when demultiplexing; accept uneven reads to assembly; add "-ds" to drop short reads before assembly.
- v1.0.1 2018-12-2 Add "polish" function
- v1.0.0
HIFI-SE v1.0.0 2018/11/22. Changers form previous version:- Formatted python code writing style as PEP8.
- Fixed several small bugs.
- v0.0.3
HIFI-SE v0.03 2018/11/15. Changes from previous version:- Modify the description of some arguments for better understanding.
- v0.0.1
HIFI-SE v0.0.1 2018/11/03 beat version, establish the framework and archive almost complete functions.
original Perl version & Python, rough sources
0.expected_error.pl
1.split_extract.pl
2.hificonnect.pl
0.expected_error.py
1.split_extract.py
2.hificonnect.py
Installation
System requirement and dependencies
Operating system: HIFI-SE is designed to run on most platforms, including UNIX, Linux and MacOS/X. Microsoft Windows. We have tested on Linux and on MacOS/X, because these are the machines we develop on. HIFI-SE is written in python language, and a version 3.5 or higher is required.
Dependencies:
- biopython version 1.5 or higher (required). Please check https://biopython.org/ and https://pypi.org/project/biopython/#description for more details on installation of biopython.
- Another python package - bold_identification is also required for getting complete function of HIFI-SE. See https://pypi.org/project/bold-identification/
- HIFI-SE supposed you have installed the VSEARCH on your device, and its path in your $PATH. See https://github.com/torognes/vsearch
Install
-
I only deploy my latest version on github, so you can clone this repository to your local computer. However, it would not solve package dependencies, thus you need to install biopython and bold_identification before using HIFI-SE software.(NOTE: pip is a link from pip3)
git clone https://github.com/comery/HIFI-barcode-SE400.git pip install biopython pip install bold_identification
-
Installation by pip is recommended because it will solve package dependencies automatically, including biopython and bold_identification packages.
pip install HIFI-SE
Usage (latest)
python3 HIFI-SE.py
or
./HIFI-SE.py
usage: HIFI-SE [-h] [-v]
{all,filter,assign,assembly,polish,bold_identification} ...
Description
An automatic pipeline for HIFI-SE400 project, including filtering
raw reads, assigning reads to samples, assembly HIFI barcodes
(COI sequences), polished assemblies, and do tax identification.
See more: https://github.com/comery/HIFI-barcode-SE400
Versions
1.0.4 (20190402)
Authors
yangchentao at genomics.cn, BGI.
mengguanliang at genomics.cn, BGI.
positional arguments:
{all,filter,assign,assembly,polish,bold_identification}
all run filter, assign and assembly.
filter remove or trim reads with low quality.
assign assign reads to samples by tags.
assembly do assembly from assigned reads,
output raw HIFI barcodes.
polish polish COI barcode assemblies,
output confident barcodes.
bold_identification
do taxa identification on BOLD system
optional arguments:
-h, --help show this help message and exit
-v, --version show program's version number and exit
run by steps [filter -> assign -> assembly]
python3 HIFI-SE.py filter
usage: HIFI-SE filter [-h] -outpre <STR> -raw <STR> [-phred <INT>] [-e <INT>]
[-q <INT> <INT>] [-trim] [-n <INT>]
optional arguments:
-h, --help show this help message and exit
common arguments:
-outpre <STR> prefix for output files
filter arguments:
-raw <STR> input raw Single-End fastq file, and only
adapters should be removed; supposed on
Phred33 score system (BGISEQ-500)
-phred <INT> Phred score system, 33 or 64, default=33
-e <INT> expected error threshod, default=10
see more: http://drive5.com/usearch/manual/exp_errs.html
-q <INT> <INT> filter by base quality; for example: '20 5' means
dropping read which contains more than 5 percent of
quality score < 20 bases.
-trim whether to trim 5' end of read, it adapts to -e mode
or -q mode
-n <INT> remove reads containing [INT] Ns, default=1
python3 HIFI-SE.py assign
usage: HIFI-SE assign [-h] -outpre <STR> -index INT -fq <STR> -primer <STR>
[-outdir <STR>] [-tmis <INT>] [-pmis <INT>]
optional arguments:
-h, --help show this help message and exit
common arguments:
-outpre <STR> prefix for output files
index arguments:
-index INT the length of tag sequence in the ends of primers
when only run assign arguments:
-fq <STR> cleaned fastq file
assign arguments:
-primer <STR> taged-primer list, on following format:
Rev001 AAGCTAAACTTCAGGGTGACCAAAAAATCA
For001 AAGCGGTCAACAAATCATAAAGATATTGG
...
this format is necessary!
-outdir <STR> output directory for assignment,default="assigned"
-tmis <INT> mismatch number in tag when demultiplexing, default=0
-pmis <INT> mismatch number in primer when demultiplexing, default=1
python3 HIFI-SE.py assembly
usage: HIFI-SE assembly [-h] -outpre <STR> -index INT -list FILE
[-vsearch <STR>] [-threads <INT>] [-cid FLOAT]
[-min INT] [-max INT] [-oid FLOAT] [-tp INT] [-ab INT]
[-seqs_lim INT] [-len INT] [-ds] [-mode INT] [-rc]
[-codon INT] [-frame INT]
optional arguments:
-h, --help show this help message and exit
common arguments:
-outpre <STR> prefix for output files
index arguments:
-index INT the length of tag sequence in the ends of primers
only run assembly arguments(not all):
-list FILE input file, fastq file list. [required]
software path:
-vsearch <STR> vsearch path(only needed if vsearch is not in $PATH)
-threads <INT> threads for vsearch, default=2
-cid FLOAT identity for clustering, default=0.98
assembly arguments:
-min INT minimun length of overlap, default=80
-max INT maximum length of overlap, default=90
-oid FLOAT minimun similarity of overlap region, default=0.95
-tp INT how many clusters will be used inassembly, recommend 2
-ab INT keep clusters to assembly if its abundance >=INT
-seqs_lim INT reads number limitation. by default,
no limitation for input reads
-len INT standard read length, default=400
-ds drop short reads away before assembly
-mode INT 1 or 2; modle 1 is to cluster and keep
most [-tp] abundance clusters, or clusters
abundance more than [-ab], and then make a
consensus sequence for each cluster.
modle 2 is directly to make only one consensus
sequence without clustering. default=1
-rc whether to check amino acid
translation for reads, default not
translation arguments(when set -rc or -cc):
-codon INT codon usage table used to checktranslation, default=5
-frame INT start codon shift for amino acidtranslation, default=1
quickstart
Files used in tutorial
All related files could be found from here. The important files for tutorial are:
- raw.fastq.gz, raw output fastq file generated from BGISEQ-500 SE400 module.
- indexed_primer.list, tagged primer list
Run in "all"
Example:
python3 HIFI-SE.py all -outpre hifi -trim -e 5 -raw test.raw.fastq -index 5 -primer index_primer.list -mode 1 -cid 0.98 -oid 0.95 -seqs_lim 50000 -threads 4 -tp 2
Citation
This work is not be published, but coming soon! I will update this part after publication.
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