Map Interpolator of the Rutgers Map

The old website of our map interpolator will be offline soon.

This application allows interpolation of map positions on the Rutgers second- and third-generation combined linkage-physical maps (Rutgers Maps v.2 and v.3 for Builds 36 and 37.3, respectively). This resource allows you to determine cM-scale linkage-based map positions for any marker, given only its physical position.

Note #1: The interpolator function uses our smoothed v.2 (Build 36) and smoothed v.3 (Build 37.3) maps. This means that map positions from our interpolator are only in-scale with our smoothed maps, not with our backbone (raw) maps. If you are using the interpolator to look up some map positions (say for markers that are not on our maps), and you are using our map files to look up positions of markers that are on our maps, you must use our smoothed map files to obtain consistent map positions.

Note #2: The Rutgers Maps v.2 and v.3 use Build 36 coordinates and Build 37.3 coordinates, respectively. To convert physical positions from previous or into succeeding builds we recommend the UCSC liftOver tool.

Note #3: If your query is in a map format (chromosome, marker name, genetic location, physical position), the interpolator will keep the column of your current genetic location (even if it is a bunch of zeroes) and call it as the "Current (cM)." This allows you to keep track of your original map positions.

Our lab is happy to assist with your project. Please contact us if we can be of any help - converting from other linkage maps or from other genome builds, or performing large-scale conversion or interpolation. Please e-mail us with suggestions for additional features that would be useful to improve the utility of our maps.

Build:      Chromosome: 

Query Format:
Physical positions (bp) only
Marker names and physical positions (bp)
Chromosome, marker names, and physical positions (bp)
Map [Chromosome, marker names,
     genetic locations (cM), and physical positions (bp)]

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© 2014 Matise Laboratory of Computational Genetics