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Fast Assembler Workflow for MitoGenome

Project description

Fast Assembler Workflow for MitoGenome

FastMitoAssembler is a software for fast, accurate assembly of mitochondrial genomes and generation of annotation documents.

Installation

1. create environment

# method 1: use conda [slowly and need large resources]
conda env create -f environment.yml

# method 2: use mamba [*recommended*]
conda install mamba -c conda-forge -y
mamba env create -f environment.yml

# method 3: install manually
conda config --add channels yccscucib
conda config --add channels bioconda
conda config --add channels conda-forge

mamba create -n FastMitoAssembler -y python==3.9.*
mamba install -n FastMitoAssembler -y snakemake
mamba install -n FastMitoAssembler -y NOVOPlasty
mamba install -n FastMitoAssembler -y GetOrganelle
mamba install -n FastMitoAssembler -y spades
mamba install -n FastMitoAssembler -y blast
mamba install -n FastMitoAssembler -y mitoz
mamba install -n FastMitoAssembler -y seqkit
mamba install -n FastMitoAssembler -y meangs

mamba install -n FastMitoAssembler -y click
mamba install -n FastMitoAssembler -y jinja2 
mamba install -n FastMitoAssembler -y pyyaml

source $(dirname `which conda`)/activate FastMitoAssembler
python -m pip insatll genbank

2. activate environment

source $(dirname `which conda`)/activate FastMitoAssembler

3. install FastMitoAssembler

python -m pip install -U FastMitoAssembler
# or
python -m pip install -U dist/FastMitoAssembler*whl

Prepare Database

FastMitoAssembler prepare

# 1. prepare ete3.NCBITaxa
FastMitoAssembler prepare ncbitaxa # download taxdump.tar.gz automaticlly
FastMitoAssembler prepare ncbitaxa --taxdump_file taxdump.tar.gz 

# 2. prepare database for GetOrganelle
FastMitoAssembler prepare organelle --list  # list configured databases
FastMitoAssembler prepare organelle -a animal_mt  # config a single database
FastMitoAssembler prepare organelle -a animal_mt -a embplant_mt # config multiple databases
FastMitoAssembler prepare organelle -a all  # config all databases

Run Workflow

config.yaml example:

reads_dir: '../data/'
samples: ['2222-4']
fq_path_pattern: '{sample}/{sample}_1.clean.fq.gz' # the reads 1 path pattern relative to `reads_dir`

see the main Snakefile and Template configfile with: FastMitoAssembler --help

Use with Client

FastMitoAssembler --help

FastMitoAssembler run --help

# run with configfile [recommended]
FastMitoAssembler run --configfile config.yaml

# run with parameters
FastMitoAssembler run --reads_dir ../data --samples S1 --samples S2

# set cores
FastMitoAssembler run --configfile config.yaml --cores 8

# dryrun the workflow
FastMitoAssembler run --configfile config.yaml --dryrun

Use with Snakemake

# the `main.smk` and `config.yaml` template can be found with command: `FastMitoAssembler`
snakemake -s /path/to/FastMitoAssembler/smk/main.smk -c config.yaml --cores 4

snakemake -s /path/to/FastMitoAssembler/smk/main.smk -c config.yaml --cores 4 --printshellcmds

snakemake -s /path/to/FastMitoAssembler/smk/main.smk -c config.yaml --printshellcmds --dryrun

Use with Docker

docker-readme

Example Results Directory

  • [*] represents the main result
result/
└── 2222-4
    ├── 1.MEANGS
    │   ├── 2222-4
    │   ├── 2222-4_deep_detected_mito.fas  [*]
    │   └── scaffold_seeds.fas
    ├── 2.NOVOPlasty
    │   ├── config.txt
    │   ├── Contigs_1_2222-4.fasta
    │   ├── 2222-4.novoplasty.fasta  [*]
    │   ├── contigs_tmp_2222-4.txt
    │   └── log_2222-4.txt
    ├── 3.GetOrganelle
    │   ├── 2222-4_1.5G.fq.gz
    │   ├── 2222-4_2.5G.fq.gz
    │   ├── 2222-4.fq1.stats.txt
    │   ├── animal_mt.get_organelle.fasta  [*]
    │   └── organelle
    └── 4.MitozAnnotate
        ├── 2222-4.animal_mt.get_organelle.fasta.result  [*]
        └── tmp_2222-4_animal_mt.get_organelle.fasta_mitoscaf.fa

Softwares Used

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