Package: QTLEMM
Type: Package
Title: QTL Mapping and Hotspots Detection
Version: 0.1.0
Authors@R: c(
person("Ping-Yuan", "Chung", email = "pychung@webmail.stat.sinica.edu.tw", role = "cre"),
person("Chen-Hung", "Kao", email = "chkao@webmail.stat.sinica.edu.tw", role = "aut"))
Description:
For QTL mapping, it consists of several functions to perform various tasks, including
simulating or analyzing data, computing the significance thresholds and visualizing the
QTL mapping results. The single-QTL or multiple-QTL method that allows a host of statistical
models to be fitted and compared is applied to analyze the data for the estimation of QTL
parameters. The models include the linear regression, permutation test, normal mixture model
and truncated normal mixture model. The Gaussian stochastic process is implemented to
compute the significance thresholds for QTL detection onto a genetic linkage map in the
experimental populations. Two types of data, the complete genotyping or selective genotyping
data, from various experimental populations, including backcross, F2, recombinant inbred (RI)
populations, advanced intercrossed (AI) populations, are considered in the QTL mapping
analysis. For QTL hotpot detection, the statistical methods can be developed based on either
using the individual-level data or using the summarized data. We have proposed a statistical
framework that can handle both the individual-level data and summarized QTL data for QTL
hotspots detection. Our statistical framework can overcome the underestimation of threshold
arising from ignoring the correlation structure among traits, and also identify the different
types of hotspots with very low computational cost during the detection process. Here, we
attempt to provide the R code for our statistical framework. The QTL mapping program is
carried out by EM process, which can be seen in Kao, C.-H. ,Z.-B. Zeng and R. D. Teasdale
(1999) <doi:10.1534/genetics.103.021642>. The analyze of selective genotyping can be seen in
H.-I LEE, H.-A. HO  and C.-H. Kao (2014) <doi:10.1534/genetics.114.168385>. The analyze of
QTL hotspot detection can be seen in Wu, P.-Y., M.-.H. Yang, and C.-H. Kao (2020)
<doi:10.1101/2020.08.13.249342>.
Imports: mvtnorm, utils, stats, graphics
License: GPL-2
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-06-10 10:14:25 UTC; pingyuan
Author: Ping-Yuan Chung [cre],
Chen-Hung Kao [aut]
Maintainer: Ping-Yuan Chung <pychung@webmail.stat.sinica.edu.tw>
Repository: CRAN
Date/Publication: 2021-06-11 08:10:02 UTC