Computational protocol: qtl.outbred: Interfacing outbred line cross data with the R/qtl mapping software

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Protocol publication

[…] The functions in qtl.outbred are summarized in Table . The main task of qtl.outbred is to import genotype probabilities, calculated for outbred cross data, into the R-environment and converting them into an object of the class cross in R/qtl. This data object can then directly be used in the R/qtl package [] for further QTL mapping analyses. R/qtl is well established and provides a comprehensive set of tools for QTL analysis which are applicable to all type of line cross data (once the genotype probabilities are calculated and imported), but today this software is limited to inbred line cross data. Importing outbred line cross data through qtl.outbred provides access to these tools to users with outbred line cross data.Calculation of genotype probabilities from outbred line cross data is not trivial and qtl.outbred provides support for obtaining these values. We recommend using the build-in function in qtl.outbred, which is much faster and more accurate than the current methods []. This method uses a new algorithm (triM) that calculates genotype probabilities from marker and pedigree data from F2 and back-cross populations, using a hidden Markov model [].Other features in qtl.outbred include the option to directly import genotype probabilities generated from the widely used GridQTL software []. However, the simple input format used in qtl.outbred, should allow the user to create input files from any other files with genotype probability data. […]

Pipeline specifications

Software tools R/qtl, GridQTL
Application WGS analysis