NAHRwhals (NAHR-directed Workflow for catcHing seriAL Structural Variations)

NAHRwhals is an R package providing tools for visualization and automatic detection of complex, NAHR-driven rearrangements (few kbp to multiple Mbp) using genome assemblies. Modules include:

• Liftover of coordinates between arbitrary human DNA assemblies
• Accurate sequence alignments of multi-MB DNA sequences
• Dotplot visualizations
• Segmented Dotplots
• A tree-based caller for complex, nested NAHR-mediated rearrangements.

Installation

(1) Clone the NAHRwhals repository

git clone https://github.com/WHops/NAHRwhals.git
cd NAHRwhals

(2) Install dependencies

We recommend using mamba to install dependencies.

For Mac Silicon (M1, M2, M3) Users (Untested!):

conda config --set channel_priority flexible
export CONDA_SUBDIR=osx-64
mamba env create --file env_nahrwhals_apple_silicon.yml
conda activate nahrwhals
unset CONDA_SUBDIR

# Install Julia manually:
# Step 1: download a julia .dmg file:
wget https://julialang-s3.julialang.org/bin/mac/aarch64/1.10/julia-1.10.5-macaarch64.dmg
# Step 2: install by double clicking and adding to your applications
# Step 3: update your $PATH in .zshrc or .profile to point to julia: 
export PATH=/Applications/Julia-1.10.app/Contents/Resources/julia/bin:$PATH
# Step 4: Install julia packages
julia -e 'using Pkg; Pkg.add("DelimitedFiles"); Pkg.add("ProgressMeter"); Pkg.add("ArgParse")'

For all other users:

conda config --set channel_priority flexible
mamba env create --file env_nahrwhals.yml
conda activate nahrwhals

julia -e 'using Pkg; Pkg.add("DelimitedFiles"); Pkg.add("ProgressMeter"); Pkg.add("ArgParse")'

(3) Install NAHRwhals

Install NAHRwhals using:

Rscript install_package.R

(4) Test your installation

Confirm the installation with a testrun (producing output files and plots in the ./res folder).

R
> library(nahrwhals)
> nahrwhals(testrun_std=T)

(The latter is equivalent to running the following command:)
> nahrwhals(ref_fa = 'inst/extdata/assemblies/hg38_partial.fa', 
            asm_fa = 'inst/extdata/assemblies/assembly_partial.fa', 
            anntrack='inst/extdata/assemblies/hg38_partial_genes.bed',
            region='chr1_partial:1700000-3300000')

Usage

1. Provide region=chr:start-end coordinates to genotype a single region

R
> library(nahrwhals)
> nahrwhals(ref_fa = 'ref.fa', 
            asm_fa = 'asm.fa,
            region = 'chr:start-end',
            outdir = 'res',
            threads = 8)

2. Provide a regions.bedfile to genotype multiple regions at once

R
> library(nahrwhals)
> nahrwhals(ref_fa = 'ref.fa', 
            asm_fa = 'asm.fa,
            regionfile = 'regions.bed',
            outdir = 'res',
            threads = 8)

3. Provide no region coordinates to invoke whole genome discovery mode. If ref.fa is human (or comparably complex), you must provide a blacklist bed file to skip centromeres and acrocentric chromsome arms. Tracks for hg38 and t2t are included in the package. Resources: ~1h using 16cpus, max-memory usage ~40Gb.

R
> library(nahrwhals)
> nahrwhals(ref_fa = 'ref.fa', 
            asm_fa = 'asm.fa,
            outdir = 'res',
            blacklist = system.file("extdata", "blacklists", "t2t_blacklist.bed", package = "nahrwhals"),
            threads = 8)

Postprocessing

Modes 2 and 3 automatically invoke post-processing of the nahrwhals_res.tsv file. This can be also done post-hoc on any res.tsv:

> nahrwhals::tsv_to_bed_regional_dominance('/your/nahrwhals.tsv', '/output/nahrwhals.bed')

Output

Key results in the outdir folder are:

1. res/res.tsv: The SV call output file.

seqname	start	end	sample	res_ref	res_max	mut_max
chr1_partial	1700000	3300000	Fasta_x_Fasta_y	71.378	99.595	4_12_inv+11_18_del

In the example provided, the input sequence x and its counterpart on y yielded a 71.3% correspondence in reference state and a 99.6% correspondence after applying the highest-scoring mutation, 'mut_max' (Inversion between blocks 4 and 12, followed by deletion of blocks 11 to 18). The file contains additional columns used mainly for QC. Those are explained at the end of the README.

2. res/chr1_partial-1700000-3300000/Fasta_x_Fasta_y_all.pdf:

This PDF contains seven plots that document the NAHRwhals run:

• 2.1. Self-dotplot of the selected region on sequence x
• 2.2. Self-dotplot of the corresponding homologous region on sequence y
• 2.3. Pairwise dotplot of the two regions
• 2.4. Visualization of the obtained segments on sequence x
• 2.5. Pariwise dotplot colored on x axis by obtained segments
• 2.6. Segmented pairwise alignment
• 2.7. Segmented pairwise alignment AFTER applying the top-scoring mutation

Figures and results from the NAHRwhals manuscript can be replicated by querying coordinates of interest (see supp. Tables and https://doi.org/10.5281/zenodo.7635935). Note the use of T2T as reference.

Run Modes and Required Parameters

The script supports three distinct run modes, each with its own set of required parameters. Below is an outline of what is needed for each mode:

Common required Parameters

These parameters are applicable across all run modes unless otherwise specified.

Variable name	Description	Default value
ref_fa	Path to the reference genome FASTA file.	-
asm_fa	Path to the assembly genome FASTA file for comparison.	-
outdir	Path to desired output directory	'./res'

Mode-dependent required Parameters

Single-region Mode

Variable name	Description	Default value
region	reference coordinates to genotype	-

Multi-region Mode

Variable name	Description	Default value
regionfile	path to a bedfile with reference coords to genotype	-

Whole-genome Mode

Variable name	Description	Default value
blacklist	path to a blacklist bedfile of centromeres and acrocentric chr arms to skip. Required to avoid explosion of runtimes in human genomes.	-

Optional Parameters

Optional Recommended Parameters

Variable name	Description	Default value
ref_name	Label for the reference genome used in outputs.	'Fasta_ref'
asm_name	Label for the assembly genome used in outputs.	'Fasta_asm'
anntrack	Include annotation tracks (e.g., genes) in dotplot. Specify as a 4-column bedfile (col 4: displayed name).	FALSE

Optional Advanced Parameters

Variable name	Description	Default value
depth	Depth of the BFS mutation search.	3
eval_th	Evaluation threshold as a percentage.	98
chunklen	Sequence chunk length for alignment.	'default'
minlen	Minimum length for considering alignments in segmentation.	'default'
compression	Minimum segment length.	'default'
max_size_col_plus_rows	Maximum size for the alignment matrix.	250
max_n_alns	Maximum number of alignments for a single query sequence.	150
self_plots	Generates self-comparison plots for the assembly and reference genomes.	TRUE
plot_only	Skip BFS/genotyping and only create dotplots.	FALSE
use_paf_library	Use an external PAF library for alignments.	FALSE
conversionpaf_link	If use_paf_library is TRUE, provide link to whole-genome PAF here.	FALSE
maxdup	BFS: max number of duplications per chain.	2
init_width	BFS: follow up only the best-scoring init_width nodes per depth.	1000
region_maxlen	Maximum length of a window that can be analyzed. Larger windows will be split into overlapping fragments.	5000000
threads	In whole genome / multi-region: regions analysed simultaneously. Single-region: cores for minimap2	1
asm_fa_mmi	Path to pre-indexed assembly genome with minimap2. Useful to avoid re-calculating.	'default'

Report Errors

Please help improve the code by reporting issues you encounter.

Citation

For more information about NAHRwhals, check out our publication

Correspondence

Please direct any correspondence to: Wolfram Höps ([email protected])