噬菌体序列分析工具PhaVa的使用和使用方法

github:?25280841/PhaVa: Adapting the phasefinder approach for identifying phase variation to long reads (github.com)

?挺简单的，这里就不翻译了，大家看着直接用吧。

PhaVa

PhaVa is an approach for finding potentially?Phase?Variable invertible regions, also referred to as invertons, in long-read seqeuncing data

Dependencies

Versions listed are the versions PhaVa has been tested on.

• EMBOSS?(v. 6.5.7)?einverted
• minimap2?(v. 2.17)
• pysam?(v. 0.17.0)
• Biopython?(v. 1.81)

PhaVa is developed and tested on Linux operating systems (CentOS Linux 7), however it should compatible with Mac OSX and Windows

Usage

The PhaVa workflow is divided into three steps: locate, create, and ratio.

phava locate -i genome.fasta -d out_dir
phava create -d out_dir
phava ratio -r long_reads.fastq -d out_dir

Alternatively, all three steps can be run in a single command via variation_wf

phava variation_wf -i genome.fasta -r long_reads.fastq -d out_dir

Output from each step is centered around a output directory (-d) and should be the same directory for the entire workflow The locate and create steps only need to be performed once for a given genome or metagenome, and ratio can then be run on long-read samples using the same output directory (-d)

Any invertons with at least 1 read aligning in the reverse orientation will be found in the output. However, it is strongly recommended to fruther filter based on a minimum reverse read count and minimum % reverse of all reads cutoff (3 and 3% are recommended, respectively)

Expected output:?

Installation

Beyond installing dependencies, PhaVa install is:

git clone https://github.com/patrickwest/PhaVa

Testing

PhaVa install can be tested on a small simulated dataset, typically in <1 minute, with pytest and a pytest module located in the 'tests' subdirectory:

pytest phava_test.py