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This document concerns a suite of packages complementary to R/qtl2 that extend capabilities in terms of plotting, fast data access, deeper probe of SNPs and structural variants, and a user-friendly interface for deep investigation of small intervals.

The QTL2 Shiny Interface can be invoked from the Shiny server http://www.statlab.wisc.edu/shiny/qtl2shiny. We demonstrate with a publicly available dataset from Recla (see https://github.com/rqtl/qtl2data). However, this Shiny server is set up with project-specific login and password protection for data that has not been published, using server side Apache htaccess. See in addition the qtl2shiny Developer Guide for more details on the package structure and flow.

Strategy to Study Small Interval

Here is a strategy to look at multiple traits in a small interval. These are rough and ready notes that will be smoothed out in time.

  • use analyses table (or other approach) to identify region of interest
    • say 1-5Mb window
  • identify set of traits in region
  • estimate allele effects at peak for each trait
    • useful plots?
  • find best SNP(s) and pattern(s)
    • identify SDP and pattern for each
    • useful plots?
  • do same for full effects
    • 36 diplotypes
    • 3-level SNPs

Some challenges

  • don’t have useful thresholds yet
  • would like to think about inference across related patterns
  • multiple peaks in small region
  • pleiotropy vs close linkage

How to incorporate this into shiny tool?

  • quick computation: limit size of region
  • do we have to run genome scan?
    • or just consider flanking markers for each peak?

QTL2 Shiny Interface

Information will appear here about how the Shiny Interface works.

R/qtl2 companion packages

The popular R/qtl package for gene mapping has been redeveloped for high volume, multi-parent systems genetics data as R/qtl2. This new package is still in a state of flux, so please work with us to improve.

This document describes companion packages that are used to build the Shiny server:

The four other packages can be employed on their own separate from the server. In particular, R/qtl2ggplot provides full capability for ggplot2 plot objects.

Additional packages used are

The intermediate package is used by qtl2mediate to manage analysis results and keep code clean and readable; it is a fork of R/intermediate The R/qtl2fst package transforms large, slow calc_genoprob objects central to R/qtl2 into a set of fst databases for quick access. See each package for its own documentation.