The aim is drive standard population genetic analyses using pangenomic data models. Typically represented in the Graphical Fragment Assembly (GFA) format, these models can represent whole genome alignments in a compact graphical structure.

I have focused on algorithms for bubble detection that allow us to generate Variant Call Format (VCF) files from graphs.

I use this projection to drive standard population genetic analyzes, and as a mechanism to validation results that I obtain from pangenome graph based population genetic analyzes which I am designing.

ODGI

• Building from GitHub odgi

• Download from Bioconda odgi

Clone the source locally:

git clone https://github.com/Flavia95/VGpop.git
cd VGpop

• gfatovcf

• bubblepop

Before run the script GfatoVcf.py and bubblepop.py, you need to:

1. Convert the GFA format to the ODGI format

By example:

odgi build -g samplePath3.gfa -o samplePath3.odgi

The odgi format as input to the script.

2. With -path specify the path of the odgi library and with -input specify the input file as odgi format

python GfatoVcf.py -path /../odgi/lib/ -input /../samplePath3.odgi

These functions are here:

    arg1: matrix

    arg1: matrix

    arg1: matrix
    arg2: collections

    arg1: matrix

    arg1: matrix

These functions are here:

    arg1: num_sequences
    arg2: num_segregating_sites
    arg3: avg_num_pairwise_differences 

Flavia Villani

MIT