Back

Statistical analysis and simulation allowing simultaneously positive, negative, and no crossover interference in multilocus recombination data

Sapielkin, S.; Frenkel, Z.; Privman, E.; Korol, A. B.

2022-11-03 bioinformatics
10.1101/2022.11.02.514815 bioRxiv
Show abstract

Crossover interference (COI) is a widespread feature of homologous meiotic recombination. It can be quantified by the classical coefficient of coincidence (CoC) `but this characteristic is highly variable and specific to the pair of chromosomal intervals considered. Several models were proposed to characterize COI on a chromosome-wise level. In the gamma model, the strength of interference is characterized by a shape parameter{nu} , while the gamma-sprinkled two-pathway model (GS) accounts for both interference-dependent and independent crossover (CO) events by fitting a mixture of gamma distributions with v>1 and v=1, correspondingly, and mixture proportions 1-p and p. In reality, COI can vary along chromosomes resulting in low compliance of the fitted model to real data. Additional inconsistency can be caused by common neglecting of possible negative COI in the model, earlier reported for several organisms. In this work, we propose an extension of the GS-model to take possible negative COI into account. We propose a way for data simulation and parameter estimation for such situations.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.