Pangenome Graph Pipeline

Pipeline to integrate multiple assemblies into a graph representation. This pipeline wraps the functionality Minigraph for genome graph construction. We add the utility to labels nodes with the assemblies it derives, which crucial for many pangenome analyses. Analyses which are common in pangenome studies are also performed, including:

• Determination of core and flexible genome
• Analysis of non-reference sequences
• Extraction of the structural variations
• Novel genes predictions and corresponding expression level
• Variants (SNP and Indels) called from non-reference sequences

See Here for the scheme of the pipeline and Here for example of the generated report.

Developed for analysis of bovine genomes, but should be applicable to the other species as well.

Under active development

Input

• Minigraphs and Gfatools need to be installed and available in $PATH. Please downloaded Here to get the same version used in the paper. Required python packages, R libraries, and bioinformatic softwares are listed Here. Alternatively, one could use mamba / conda to create environment with all softwares installed (Minigraph not included). To generate pdf report one need to install weasyprint.

conda env create -f envs/environment.yml
conda activate pangenome 

• Set all parameters required in config/config.yaml. All paths will be interpreted relative to the workdir directory.
• Multiple assemblies in the workdir/assembly with naming scheme of {population}.fa. The prefix will be used as identifier for the assembly.
• A file config/graph_comp.tsv that mapping the name of graph and the order of inclusion. First in the order used as the graph backbone, which is usually the reference genome (e.g., UCD).
  Construction of multiple graphs can be specified in the different line e.g.,

graph1 UCD,OBV,Angus 
graph2 UCD,Angus 

• Job specification in the pipeline designed for LSF system. One need to adapt for the other computing clusters.

Usage

snakemake -s snake_graph.py

Output

• Integrated pangenome graphs in graph folder with prefix set in the config e.g., graph1.gfa

• Matrix that map node to the assembly it derives (i.e., node colour), e.g.,

  Node	UCD	OBV	Angus
  s1	1	0	0
  s2	0	1	1

  *0 and 1 indicate absence and presence respectively

• Structural variations derived from graphs.
  These are large variations (fragment length > 100 bp) from bubbles in the graph that are not part of the reference sequences. The SVs grouped by biallelic and multiallelic. SVs crossing coding sequences visualized using Graphviz.
  Script app.py can be run which will set up a local webserver (not part of the pipeline) to inspect SVs in a more detailed and in an interactive way (Under development).

• Prediction of novel /non-reference genes with corresponding expression levels from transcriptome.

• Variants (SNP and Indels) nested in non-reference sequences. One need to run separate pipeline for variant calling. Set config for the pipeline in Here.

• Reports in reports/{graph} folder. This contains summary of computational resources, statistics of core/flexible genome, structural variations, novel gene models derived from graphs. Will output a single pdf from each constructed graph. See the example Here.