Metallaxis

Metallaxis is a Python graphical interface for viewing and annotating VCF files. On loading a VCF file or compressed variant (vcf.gz,vcf.xz) it will generate statistics, graphs, and open a table view where the variants can be sorted, filtered, and their position visualised compared to the location of genes, based on data retrieved from API requests to ENSEMBL.

Additionally, there is the option to annotate the VCF, whereby the dbSNP and clinVar databases are downloaded and SnpEff is used to annotate the VCF, to view the impact of the variant.

On the interface basic statistics and graphs are displayed in the statistics pane, and a Table pane is also avaliable on which variants can be filtered by data from VCF, from annotation, or parsed form the INFO column.

Features

INFO column splitting into columns that can be sorted
Filtering of all VCF columns
Automatic annotation from dbSNP, ClinVar, and ENSEMBL (provided VCF is human)
Automatically generated statistics and graphs
Savable analysis as a portable sqlite database

Authors

Sean Laidlaw, with supervision from Anna-Sophie Fiston-Lavier, and with contributions from Qiqi He.

Requirements:

Python:

Python 3.6

Libraries

python-magic : 0.4.15
pandas : 0.23.4
numpy : 1.15.4
PyQt5 : 5.11.2
requests : 2.20.1
matplotlib : 3.0.2
wget : 3.2

Installation

Pip

Use the package manager pip to install Metallaxis.

pip install Metallaxis

From Source

Metallaxis can also be installed from source, by running a git clone and then running the make file which will install dependancies and install as a python module.

git clone https://github.com/SL-LAIDLAW/Metallaxis
cd Metallaxis && make

Usage

To open the GUI and get started, run Metallaxis as a module:

python3 -m metallaxis

It can also be run directly on a VCF file:

python3 -m metallaxis ../samples/1000_genomes_extract.vcf.gz

Or to load a previously saved Metallaxis session, by using the saved database file as argument:

python3 -m metallaxis ../saves/big_saved_analysis.sqlite

Screenshots

Example variant data displaying statistics of variants by chromosome, as well as number of variants by position for each chromosome.

Example variant data with annotation listing consequence terms, biotype, gene id, impact, etc. for some of our variants.

Example data showing off filtering ability of Metallaxis, not just limited to normal VCF columns but works equally well on recently obtained annotation columns: