Mappability Track Settings
 
Single-read and multi-read mappability by Umap   (All Mapping and Sequencing tracks)

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 Umap S24  Single-read mappability with 24-mers   Data format 
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 Umap S36  Single-read mappability with 36-mers   Data format 
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 Umap S50  Single-read mappability with 50-mers   Data format 
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 Umap S100  Single-read mappability with 100-mers   Data format 
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 Umap S150  Single-read mappability with 150-mers   Data format 
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 Umap S250  Single-read mappability with 250-mers   Data format 
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 Configure 		 Umap M24  Multi-read mappability with 24-mers   Data format 
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 Configure 		 Umap M36  Multi-read mappability with 36-mers   Data format 
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 Configure 		 Umap M50  Multi-read mappability with 50-mers   Data format 
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 Configure 		 Umap M100  Multi-read mappability with 100-mers   Data format 
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 Configure 		 Umap M150  Multi-read mappability with 150-mers   Data format 
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 Configure 		 Umap M250  Multi-read mappability with 250-mers   Data format 
    
Data schema/format description and download
Assembly: Human Jan. 2022 (T2T CHM13v2.0/hs1)

Description

Umap single-read and multi-read mappability

Umap single-read mappability

These tracks mark any region of the genome that is uniquely mappable by at least one k-mer. To calculate the single-read mappability, you must find the overlap of a given region with this track.

Umap multi-read mappability

These tracks represent the probability that a randomly selected k-mer which overlaps with a given position is uniquely mappable.

For greater detail and explanatory diagrams, see the publication, the Umap and Bismap project website, or the Umap and Bismap software documentation.

You can use these tracks for many purposes, including filtering unreliable signal from sequencing assays.

Data Access

The raw data can be explored interactively with the Table Browser, or the Data Integrator. For automated analysis, genome annotation is stored in a bigBed or bigWig file that can be downloaded from the download server. Individual regions or the whole genome annotation can be obtained using our tool bigBedToBed or bigWigToWig, 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 tool can also be used to obtain only features within a given range, for example:

bigBedToBed -chrom=chr6 -start=0 -end=1000000 http://hgdownload.soe.ucsc.edu/gbdb/hs1/hoffmanMappability/k24.Unique.Mappability.bb stdout
bigWigToWig -chrom=chr6 -start=0 -end=1000000 http://hgdownload.soe.ucsc.edu/gbdb/hs1/hoffmanMappability/k24.Umap.MultiTrackMappability.bw stdout

Please refer to our mailing list archives for questions, or our Data Access FAQ for more information.

Credits

Anshul Kundaje (Stanford University) created the original Umap software in MATLAB. The original Umap repository is available here. Mehran Karimzadeh (Michael Hoffman lab, Princess Margaret Cancer Centre) implemented the Python version of Umap and added features, including Bismap.

References

Karimzadeh M, Ernst C, Kundaje A, Hoffman MM. Umap and Bismap: quantifying genome and methylome mappability. Nucleic Acids Res. 2018 Nov 16;46(20):e120. PMID: 30169659; PMC: PMC6237805