PHG version 2

The Practical Haplotype Graph (PHG) is a powerful tool for representing pangenomes. The PHG is optimized for plant breeding and genetics, where genomic diversity can be high, phased haplotypes are common (e.g. inbred lines), and imputation with low density markers is essential for breeding efficiency. This complements other imputation tools (e.g. BEAGLE) designed explicitly for handling samples from unphased species characterized by low genetic diversity and high-density genotyping.

The PHG is a trellis graph based representation of consecutive genic and intergenic regions (called reference ranges) which represent diversity across and between samples. It can be used to:

Create custom genomes for alignment
Call rare alleles
Impute genotypes
Efficiently store genomic data from many samples (i.e. reference, assemblies, and other lines)

The PHG also works well with community standards including the Breeding API (BrAPI) and efficient tools for R such as rPHG for pangenome extraction and rTASSEL for connecting genotype to phenotype.

Quick start

Installation

Using a Linux distribution, download the latest release here or use the command line:

curl -s https://api.github.com/repos/maize-genetics/phg_v2/releases/latest \
| awk -F': ' '/browser_download_url/ && /\.tar/ {gsub(/"/, "", $(NF)); system("curl -LO " $(NF))}'

Untar and add the wrapper script to your PATH variable. Detailed information about these steps can be found here.

Build and load data

Long-form documentation for this section can be found here

## Setup conda environment
./phg setup-environment

## Initialize TileDB DataSets
./phg initdb --db-path /path/to/dbs

## Preprocessing data
./phg annotate-fastas --keyfile /path/to/keyfile --output-dir /path/to/annotated/fastas --threads numberThreadstoRun

## Build VCF data
./phg create-ranges --reference-file Ref.fa --gff my.gff --boundary gene --pad 500 --range-min-size 500 -o /path/to/bed/file.bed
./phg align-assemblies --gff anchors.gff --reference-file Ref.fa -a assembliesList.txt --total-threads 20 --in-parallel 4 -o /path/for/generatedFiles
./phg agc-compress --db-path /path/to/dbs --reference-file /my/ref.fasta --fasta-list /my/assemblyFastaList.txt 
./phg create-ref-vcf --bed /my/bed/file.bed --reference-file /my/ref.fasta --reference-url https://url-for-ref --reference-name B73 --db-path /path/to/tiled/dataset folder
./phg create-maf-vcf --db-path /path/to/dbs --bed /my/bed/file.bed --reference-file /my/ref.fasta --maf-dir /my/maf/files -o /path/to/vcfs
## Convert GVCF to HVCF: use this if you have GVCF files created by PHG, but do not have MAF or h.vcf files
./phg gvcf2hvcf --bed /my/bin/file.bed --gvcf-dir /my/gvcf/dir --reference-file /my/ref.fasta --reference-name B73 
## Load data into DBs
./phg load-vcf --vcf /my/vcf/dir --dbpath /path/to/dbs

Imputation

Note

This section is currently in progress and command input may be subject to change. The following pseudocode is a possible representation of the imputation workflow:

## Index
./phg index-kmers --ancestor founder.h.vcf -o kmer_index.map // we need this

## Map
./phg map-kmers \
    --kmer-index kmer_index.map \
    --reads my_reads.fastq \ // possibly thousands of samples being inputted
    --output read_count_out.map \ // could we pipe this into impute method? // thousands of outputs
    // consider batch interface here ^^

## Impute
./phg impute \
    --hap-counts read_count_out.map \ // will users understand the di
    --diploid false \
    --ancestor founder.h.vcf \
    --max-anc-hap-num 20 \
    --max-anc-hap-prop 0.95 \
    --output-parent best_parents.txt \
    -o my_impute.h.vcf

## Load
./phg load-vcf --vcf my_impute.vcf --dbpath /my/db/uri

Data retrieval

Note

This section is currently in progress and command input may be subject to change. The following pseudocode is a possible representation of the retrieval workflow:

## Export from Tiledb
./phg export-vcf --db-path /my/db/uri --dataset-type hvcf --sample-Names LineA,LineB --output-dir /my/output/dir

Design and history

PHGv1 was published in 2022. It addressed many challenges related to aligning diverse genomes, efficient storage, and imputation across a pangenome. However, it depended on a custom relational database that necessitated unique formats, and database queries did not scale effectively with a large number of taxa and rare alleles. Moreover, after developing PHGs for six species, we identified significant opportunities to refine and streamline the platform for curation.

The redesign leverages the performant TileDB-VCF database, which is widely used in human genetics for extensive medical applications and is highly proficient for rapid querying and storage of rare variants. The PHG is now backed by two TileDB-VCF databases: one for tracking haplotypes across all samples (.h.vcf), and another for tracking variants relative to either the reference genomes or the closest haplotype (.g.vcf). Our implementation of haplotype encoding in VCF heavily relies on the VCF ALT haplotype specification defined in v4.2.

Other important things to note:

High-quality phased genome assemblies (or similar) are available to initialize the PHG.
Ancestral haplotypes are aligned to the reference genome for the identification of haplotypes.
All PHG tools rely on public file standards - FASTA, VCF, BCF, BED, and MAF.
We rely on public tools like TileDB, Minimap2, GATK, AnchorWave, BioKotlin, and HTSJDK.
Genotyping with low-density markers is now done using a memory- and speed-efficient k-mer approach, followed by pathfinding (imputation) with hidden Markov model methods.
Rare allele discovery with short reads is based on the above path, involving short read alignment to the inferred haplotype path genome and the GATK haplotype caller.

Terminology

When describing components used in the PHG, certain terms are used to efficiently communicate more complicated ideas. Some common terms you may find are:

Term	Definition
haplotype	The sequence of part of an individual chromosome.
path	The phased set of haplotypes that represent a chromosome.
reference genome	A genome used for initial alignment and base coordinates.
reference range	A segment of the reference genome.

eead-csic-compbio/phg_v2