CODA (CrossOver Distribution Analyzer): Quantitative characterization of crossover position patterns along chromosomes
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Project leader Matthieu Falque
Recent evidence from several distantly related organisms shows that crossovers form in two pathways. One, the interfering pathway (pathway 1), lowers the probability that two COs occur close to each other in the same meiosis. The other, the non-interfering pathway (pathway 2) leads to randomly distributed COs. The main purpose of CODA is to provide easy access to powerful and appropriate statistical and computational tools to characterize CO pathways, namely by estimating two parameters: interference strength in pathway 1, and the proportion of COs formed through pathway 2 (Falque et al. 2009). The detailed algorithm is given in that paper.
CODA provides a graphical user interface which gives the possibility to customize settings before launching the job. Analyses are based on two possible interference models, and incorporate computation of confidence intervals for the estimated parameters.
In addition, severals real-time updated graphs are displayed while the job is running:
- Distribution of the number of COs per chromosome.
- Distribution of the positions of COs along the chromosome.
- Distribution of distances between successive COs.
These different graphs make it possible to visualize the fit between simulated data generated by the model and experimental data on the same plot.
CODA can work with CO positions observed at the level of the bivalents or at the level of gametes.
Bivalent data may come from cytological immunolocalizations (e.g. MLH1 foci) or EM observations of nodules on the synaptonemal complex, or tetrad-derived genetic data. Gamete data may come from linkage mapping experiments (segregation data), or sperm typing.
“CODA” is available for Windows (XP or superior), MacOSX (10.4 or superior) and Gnu/Linux-based platforms. Binary files are available for Windows and MacOS, and sources may also be freely downloaded to complile for any platforms (including linux). In this case you will need to have Qt4, Qwt and Qwtplot3d installed on your system.
Reference
Gauthier, F., Martin, O.C., and M. Falque (2011). CODA (CrossOver Distribution Analyzer): quantitative characterization of crossover position patterns along chromosomes. BMC Bioinformatics 12 27
Downloads
CODA user manual.
CODA software.
Legal notice
The program CODA is distributed under the GPL v3 public license.