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UserGuide.Rmd
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---
title: "qtl2shiny UserGuide"
author: "Brian S. Yandell"
date: "`r format(Sys.Date(), '%d %b %Y')`"
output: rmarkdown::html_vignette
vignette: >
%\VignetteIndexEntry{qtl2shiny UserGuide}
%\VignetteEngine{knitr::rmarkdown}
%\VignetteEncoding{UTF-8}
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
This document concerns a suite of packages complementary to [R/qtl2](http://www.rqtl.org/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](https://httpd.apache.org/docs/current/howto/ssi.html).
## 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](http://www.rqtl.org) package for gene mapping has been redeveloped for high volume, multi-parent systems genetics data as [R/qtl2](http://www.rqtl.org/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:
- [R/qtl2ggplot](https://github.com/byandell/qtl2ggplot)
- [R/qtl2feather](https://github.com/byandell/qtl2feather)
- [R/qtl2pattern](https://github.com/byandell/qtl2pattern)
- [R/qtl2shiny](https://github.com/byandell/qtl2shiny)
The three other packages can be employed on their own separate from the server. In particular, [R/qtl2ggplot](https://github.com/byandell/qtl2ggplot) provides full capability for `ggplot2` plot objects. The [R/qtl2feather](https://github.com/byandell/qtl2feather) package transforms large, slow `calc_genoprob` objects central to [R/qtl2](http://www.rqtl.org/qtl2) into a set of `feather` databases for quick access. See each package for its own documentation.
There is another package that is more specialized and still need documentation:
[R/CausalMST](https://github.com/byandell/CausalMST) concerns Causal Model Selection Tests, which are used in conjunction with mediation to formally infer causal relationship between a phenotype and other phenotypes that co-map. Plan is to try to combine this with [R/intermediate](https://github.com/churchill-lab/intermediate).