Windows QTL Cartographer 2.5 - FTP Directory Listing

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Windows QTL Cartographer 2.5
To do the pleiotropy vs. close linkage test according to above parameter setting.
8. Genome wide test of QTL effects
To do the QTL effect(s) equality test according to above parameter setting.
9. Trait pairwise co-relation in current population
To calculate QTL co-relation between pairs of traits according to a control file (TPControl.txt).
Example of TPControl file:
#begin
1 gene_563 gene_2694 3 3 54.6 15 52.5 13 288.1
2 gene_563 gene_4898 2 3 54.6 15 52.5
3 gene_563 gene_5323 2 3 54.6 15 52.5
#end
The control file start with line of #begin and end with line of #end. For each line between is the
information for a pair of traits. The first number is the numbering, and second and third are the marker
labels for the first and second trait. After that is the total QTL number follow by chromosome number and
position for each QTL.
Bayesian Interval Mapping
WinQTLCart's Bayesian interval mapping (BIM) module is an implementation of the command-line BIM
library, provided courtesy of the R Project for Statistical Computing.
What it is
Bayesian interval mapping library R/bim provides Bayesian analysis of multiple quantitative trait loci
models. This includes posterior estimates of the number and location of QTL and of their effects.
Bayesian interval mapping for controlled experiment provides a nice complement to the classical
analysis for mapping QTLs. It is recommended that the standard IM, CIM, MIM, etc. analyses be run
first. The Bmapqtl implements Bayesian analysis for either a fixed or random number of QTLs.
(WinQTLCart's default is random.)
The program generates a random sample from the joint posterior of QTL and effects. Note that the BIM
estimates should generally agree with those of MIM, and should be similar to those from CIM.
BIM allows one to look deeper at the properties of those estimates, such as how effects estimates are
related to loci estimates. It also provides handy tools to explore research questions, such as the
posterior chance of multiple QTL in an interval.
How to use
The defaults are quite robust, and it is recommended you use them during your first BIM runs.
For more information on the BIM parameters
Please refer to the R implementation, particularly the function bmapqtl.options(). The best way to get
library(bim) is to already have R 1.9.0 installed on your PC.
1. If you don't have R 1.9.0 installed on your computer, go to http://cran.r-project.org/
2. Download the precompiled binary distribution of R (Linux or Windows is preferred.) Follow
© 2010 N.C. State University, Bioinformatics Research Center