Elixir BioHackathon November 3-7, 2025

Elixir-BH-2025

How to use this repo

git clone https://github.com/jedrzejkubica/Elixir-BH-2025.git
cd Elixir-BH-2025

Data

We assume all data listed below is downloaded into data/:

1. deCODE recombination map from Palsson et al., 2024 including both crossover (CO) and non-crsossover (NCO) recombination: https://doi.org/10.5281/zenodo.14025564

2. high-resolution recombination map from Halldorsson et al., 2019 with empirically defined recombination rates:

wget https://www.science.org/doi/suppl/10.1126/science.aau1043/suppl_file/aau1043_datas3.gz
gzip -d aau1043_datas3.gz

File aau1043_datas3 contains averaged maternal and paternal recombination rates.

Exploring recombination maps

All code for exploring recombination maps is in haploblock_breakpoints.ipynb.

Recombination map from Palsson et al., 2024

How the data looks:

Chr	Position	map (cM)	cMperMb	DSBs/Mb per meiosis	deltaDSB	oNCO
chr1	500000	0.0465734638273716	0.051548998802900314	0.18732483685016632	0.9579851031303406	0.00024600245524197817
chr1	1500000	0.05668618530035019	0.36985400319099426	0.23414182662963867	0.7754221558570862	0.0006765067810192704
chr1	2500000	0.08809421956539154	1.2260290384292603	0.3768974542617798	0.5750330686569214	0.0022755227982997894
chr1	3500000	0.07209863513708115	1.9589810371398926	0.3275741636753082	0.3099609315395355	0.0027675277087837458
chr1	4500000	0.06319160014390945	2.5238749980926514	0.3032439053058624	0.1271921992301941	0.002952029462903738

Are map (cM), cMperMb, DSBs/Mb per meiosis, deltaDSB and oNCO correlated?

We used DSB rate (DSBs/Mb per meiosis) to find haploblock boundaries.

1. We found 12 positions with high recombination rates defined as rate > 2*average:

Position	Recombination rate (DSBs/Mb per meiosis)
chr6:4500000	0.2726089060306549
chr6:5500000	0.2507183849811554
chr6:6500000	0.34163784980773926
chr6:7500000	0.2730921804904938
chr6:11500000	0.24522000551223755
chr6:15500000	0.27179062366485596
chr6:16500000	0.24810494482517242
chr6:43500000	0.24928732216358185
chr6:57500000	0.27551886439323425
chr6:58500000	0.37233930826187134
chr6:59500000	0.7373786568641663
chr6:166500000	0.25078296661376953

2. We found 7 positions with high recombination rates defined as rate > 1.5*IQR:

Position	Recombination rate (DSBs/Mb per meiosis)
chr6:4500000	0.2726089060306549
chr6:6500000	0.34163784980773926
chr6:7500000	0.2730921804904938
chr6:15500000	0.27179062366485596
chr6:57500000	0.27551886439323425
chr6:58500000	0.37233930826187134
chr6:59500000	0.7373786568641663

3. We found 6 positions with high recombination rates defined as peaks after Gaussian smooting:

Position	Recombination rate (DSBs/Mb per meiosis)
chr6:7500000	0.2730921804904938
chr6:38500000	0.08716981112957001
chr6:58500000	0.37233930826187134
chr6:90500000	0.12601755559444427
chr6:106500000	0.13935035467147827
chr6:165500000	0.2063562124967575

For more information about Gaussian smoothing see: https://en.wikipedia.org/wiki/Gaussian_filter

We compared different sigma for Gaussian smoothing:

Recombination map from Halldersson et al., 2019

We used cMperMb to generate haploblock boundaries.

1. We found 1398 positions with high recombination rates defined as rate > 10*average:

2. We found 11855 positions with high recombination rates defined as rate > 1.5*IQR.

3. We found 2287 positions with high recombination rates defined as peaks after Gaussian smooting (sigma=5). Zoom in on the first peak:

We compared different sigma for Gaussian smoothing:

The number of peaks found with different sigma:

Sigma	Number of peaks
1	8245
3	3579
5	2287
10	1210

Python environment

Create via Python venv with the following commands:

python -m venv --system-site-packages ~/pyEnv_ElixirBH2025
source ~/pyEnv_ElixirBH2025/bin/activate
pip install --upgrade pip
pip install numpy pandas scipy matplotlib

References

1. Palsson, G., Hardarson, M.T., Jonsson, H. et al. Complete human recombination maps. Nature 639, 700–707 (2025). https://doi.org/10.1038/s41586-024-08450-5

2. Bjarni V. Halldorsson et al., Characterizing mutagenic effects of recombination through a sequence-level genetic map. Science363,eaau1043 (2019). DOI:10.1126/science.aau1043