This repository contains code for quantifying crossover (CO) inteference in meiosis based on the interference length Lint, which is defined in the pre-print Interference Length reveals regularity of crossover placement across species by M. Ernst, R. Mercier, and D. Zwicker.
The JavaScript version should run in any decently modern browser by simply opening the
file measure_CO_interference.html.
There is the option to load example data using the button "Load example data", but you can also paste your own CO
positions (as explained in the file).
The button "Calculate quantities" then calculates all quantities (and the respective standard deviations of the mean)
and displays the result below.
The calculation of the coefficient of coincidence curve is based on the implementation given in https://github.com/mwhite4/MADpatterns/blob/master/interval_analysis.m
The positions need to be specified in fractions of the total chromosome length, so they are numbers between 0 and 1. The chromosome length can be specified in units of micrometer (µm) for cytological data, units of megabases (Mb) for genetic data, or left set to 1 to obtain results normalized to the chromosome length.
The python version of the code requires the numpy and scipy packages, which can be installed using the requirements
files.
pip install -r requirements.txtExemplary data from A. thalania (genetic data) from [1, 2] for various genotypes (wild-type, HEI10oe, zyp1 and zyp1
HEI10oe), both male/female and all five chromosomes (index 1..5) is contained in the folder data/.
The associated genetic chromosome lengths are stored in data/chromosome_lengths.csv, whereas the CO positions for the
samples are stored in files following the scheme data/A_thalania_[genotype]_[sex]_[chromosome_index].csv.
Running the python script displays summary statistics for various genotypes and sexes:
python example.pyThe functions are implemented in the python script measure_CO_interference.py.
The summary statistics (mean number of COs, interference length, normalized interference
length, gamma shape parameter and interference distance) can be used by calling the
python function get_interference_measures(positions, my_params), and the coefficient
of coincidence can be computed using coefficient_of_coincidence(positions, my_params).
The positions need to be specified in fractions of the total chromosome length, so they are numbers between 0 and 1. The chromosome length can be specified in units of micrometer (µm) for cytological data, units of megabases (Mb) for genetic data, or left set to 1 to obtain results normalized to the chromosome length.
The parameter dictionary my_params has the following relevant parameters
length which gives the length of the chromosome (or SC) in the respective unit. NUM_BOOTSTRAP_SAMPLES gives the
number of bootstrap samples to compute the standard deviation of the mean.
NUM_INTERVALS gives the number of bins of the coefficient of coincidence curve and
COC_IMPLEMENTATION can be set to either mwhite to compute the curve according to
the implementation given in
https://github.com/mwhite4/MADpatterns/blob/master/interval_analysis.m
while setting it to mernst uses an implementation that does not require pre-binning
and is described in the publication in SI-1B.
[1] Durand, S., Lian, Q., Jing, J. et al. Joint control of meiotic crossover patterning by the synaptonemal complex and HEI10 dosage. Nat Commun 13, 5999 (2022). https://doi.org/10.1038/s41467-022-33472-w
[2] Singh, D. K., Lian, L., Durand, S. et al. Heip1 is required for efficient meiotic crossover implementation and is conserved from plants to humans, Proceedings of the National Academy of Sciences 120, e2221746120 (2023). https://doi.org/10.1073/pnas.2221746120