QTLBIM, a library for QTL Bayesian Interval Mapping, provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits.
QTLBIM has been released as an R package. This means it is available for free and can be downloaded and used from within the R statistical programming environment. For more information about the package, please read our documentation pages.
An important scientific question in understanding a trait / disease in any organism is to identify its genetic basis. This means identifying the portions of the genome that contain information affecting the particular trait or disease of interest. Most traits or diseases are affected by multiple locations on the genome in varying degrees and are called complex traits. Knowledge of the genetic dependencies of such complex traits can prove really useful in conducting targeted studies.
A region on the genome that has a statistically significant association with a disease/trait of interest is called a quantitative trait locus. QTL Mapping is the process of identifying all the interacting QTL on the genome that produce a significant effect on the trait. QTLBIM is one such QTL mapping package that relies on Bayesian inference.
Bayesian Inference refers to a class of methods that facilitate incorporating "prior" information (generally from previous studies). This prior information (or belief) is then updated using the data & analyses from the current study to give us a (hopefully) better estimate. More about Bayeisan methods can be found on wikipedia.
If all that sounded like greek, here's a shorter description of what this is all about: QTLBIM is a statistical software package that is used by people who are interested in statistical genetics or related areas. Its primary objective is to aid in the identification of genes that have a significant effect on a trait or disease that is being studied.