BatchMap is a fork of the OneMap software package for the construction of linkage maps. Specifically it aims to provide a framework that enables creating linkage maps from dense marker data (N>10,000).
Most of the non-core functionality of OneMap has been stripped and only a few functions are left at user-level. Further, this package is typically expected to be run on a headless server due to memory requirements, so all graphic functionality has also been removed.
BatchMap employs a divide and conquer algorithm that manages to speed up the calculation of high density datasets and - additionally - scales well with higher marker numbers. It further features a routine inspired by OneMap’s
ripple.seq function that can adaptively reorder windows of markers to improve the order of sequences.
BatchMap is created specifically for F1 outcrossing populations. If your data is not that (e.g. backcross, F2, RIL), use OneMap.
The twopoint table of recombination fractions and likelihoods will take
4 * 8 * N * N bytes in memory, where
N is your marker number. If you have anything less than that, you need to either reduce the number of input markers, or rent a cloud server (Amazon EC2 provides high memory machines).
This will install the current development version, which is newest, but might include unstable code. If you’re in doubt, install from CRAN.
install.packages("devtools") library(devtools) install_github("bschiffthaler/BatchMap")
This installs the latest stable version.
Windows is currently not able to parallelize R code using the
parallel package. It is therefore highly recommended to use the docker container here.
After installation, you can read the user tutorial (‘vignette’) here.
This software depends whole-heartedly on the work done by all original and current authors of OneMap. We therefore ask you to cite both OneMap and BatchMap if you find BatchMap useful in your research.