Recomb Rate Tracks
Recombination rate: Genetic maps from deCODE and 1000 Genomes tracks   (All Mapping and Sequencing tracks)

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Recomb. deCODE Avg  Recombination rate: deCODE Genetics, average from paternal and maternal (mat for chrX)  
Recomb. deCODE Pat  Recombination rate: deCODE Genetics, paternal  
Recomb. deCODE Mat  Recombination rate: deCODE Genetics, maternal  
Recomb. deCODE Evts  Recombination events in deCODE Genetic Map (zoom to < 10kbp to see the events)  
Recomb. deCODE Dmn  Recombination rate: De-novo mutations found in deCODE samples  
Recomb. 1k Genomes  Recombination rate: 1000 Genomes, lifted from hg19 (PR Loh)  

new Note: Released Feb. 13, 2023


The recombination rate track represents calculated rates of recombination based on the genetic maps from deCODE (Halldorsson et al., 2019) and 1000 Genomes (2013 Phase 3 release, lifted from hg19). The deCODE map is more recent, has a higher resolution and was natively created on hg38 and therefore recommended. For the Recomb. deCODE average track, the recombination rates for chrX represent the female rate.

This track also includes a subtrack with all the individual deCODE recombination events and another subtrack with several thousand de-novo mutations found in the deCODE sequencing data. These two tracks are hidden by default and have to be switched on explicitly on the configuration page.

Display Conventions and Configuration

This is a super track that contains different subtracks, three with the deCODE recombination rates (paternal, maternal and average) and one with the 1000 Genomes recombination rate (average). These tracks are in signal graph (wiggle) format. By default, to show most recombination hotspots, their maximum value is set to 100 cM, even though many regions have values higher than 100. The maximum value can be changed on the configuration pages of the tracks.

There are two more tracks that show additional details provided by deCODE: one subtrack with the raw data of all cross-overs tagged with their proband ID and another one with around 8000 human de-novo mutation variants that are linked to cross-over changes.


The deCODE genetic map was created at deCODE Genetics. It is based on microarrays assaying 626,828 SNP markers that allowed to identify 1,476,140 crossovers in 56,321 paternal meioses and 3,055,395 crossovers in 70,086 maternal meioses. In total, the data is based on 4,531,535 crossovers in 126,427 meioses. By using WGS data with 9,305,070 SNPs, the boundaries for 761,981 crossovers were refined: 247,942 crossovers in 9423 paternal meioses and 514,039 crossovers in 11,750 maternal meioses. The average resolution of the genetic map is 682 base pairs (bp): 655 and 708 bp for the paternal and maternal maps, respectively.

The 1000 Genomes genetic map is based on the IMPUTE genetic map based on 1000 Genomes Phase 3, on hg19 coordinates. It was converted to hg38 by Po-Ru Loh at the Broad Institute. After a run of liftOver, he post-processed the data to deal with situations in which consecutive map locations became much closer/farther after lifting. The heuristic used is sufficient for statistical phasing but may not be optimal for other analyses. For this reason, and because of its higher resolution, the DeCODE map is therefore recommended for hg38.

As with all other tracks, the data conversion commands and pointers to the original data files are documented in the makeDoc file of this track.

Data Access

The raw data can be explored interactively with the Table Browser, or the Data Integrator. For automated access, this track, like all others, is available via our API. However, for bulk processing, it is recommended to download the dataset.

For automated download and analysis, the genome annotation is stored at UCSC in bigWig and bigBed files that can be downloaded from our download server. Individual regions or the whole genome annotation can be obtained using our tools bigWigToWig or bigBedToBed which can be compiled from the source code or downloaded as a precompiled binary for your system. Instructions for downloading source code and binaries can be found here. The tools can also be used to obtain features confined to a given range, e.g.,

bigWigToBedGraph -chrom=chr17 -start=45941345 -end=45942345 stdout

Please refer to our Data Access FAQ for more information.


This track was produced at UCSC using data that are freely available for the deCODE and 1000 Genomes genetic maps. Thanks to Po-Ru Loh at the Broad Institute for providing the code to lift the hg19 1000 Genomes map data to hg38.


1000 Genomes Project Consortium., Abecasis GR, Altshuler D, Auton A, Brooks LD, Durbin RM, Gibbs RA, Hurles ME, McVean GA. A map of human genome variation from population-scale sequencing. Nature. 2010 Oct 28;467(7319):1061-73. PMID: 20981092; PMC: PMC3042601

Halldorsson BV, Palsson G, Stefansson OA, Jonsson H, Hardarson MT, Eggertsson HP, Gunnarsson B, Oddsson A, Halldorsson GH, Zink F et al. Characterizing mutagenic effects of recombination through a sequence-level genetic map. Science. 2019 Jan 25;363(6425). PMID: 30679340