R Observatory: Metrics for QTLEMM version 3.1.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

QTLEMM

3.1.0Package record

QTL EM Algorithm Mapping and Hotspots Detection

0packages depend

6.5Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Ping-Yuan ChungCRAN page ↗GitHub ↗Issues ↗

For QTL mapping, this package comprises several functions designed to execute diverse tasks, such as simulating or analyzing data, calculating significance thresholds, and visualizing QTL mapping results. The single-QTL or multiple-QTL method, which enables the fitting and comparison of various statistical models, is employed to analyze the data for estimating QTL parameters. The models encompass linear regression, permutation tests, normal mixture models, and truncated normal mixture models. The Gaussian stochastic process is utilized to compute significance thresholds for QTL detection on a genetic linkage map within experimental populations. Two types of data, complete genotyping, and selective genotyping data from various experimental populations, including backcross, F2, recombinant inbred (RI) populations, and advanced intercrossed (AI) populations, are considered in the QTL mapping analysis. For QTL hotspot detection, statistical methods can be developed based on either utilizing individual-level data or summarized data. We have proposed a statistical framework capable of handling both individual-level data and summarized QTL data for QTL hotspot detection. Our statistical framework can overcome the underestimation of thresholds resulting from ignoring the correlation structure among traits. Additionally, it can identify different types of hotspots with minimal computational cost during the detection process. Here, we endeavor to furnish the R codes for our QTL mapping and hotspot detection methods, intended for general use in genes, genomics, and genetics studies. The QTL mapping methods for the complete and selective genotyping designs are based on the multiple interval mapping (MIM) model proposed by Kao, C.-H. , Z.-B. Zeng and R. D. Teasdale (1999) <doi: 10.1534/genetics.103.021642> and H.-I Lee, H.-A. Ho and C.-H. Kao (2014) <doi: 10.1534/genetics.114.168385>, respectively. The QTL hotspot detection analysis is based on the method by Wu, P.-Y., M.-.H. Yang, and C.-H. Kao (2021) <doi: 10.1093/g3journal/jkab056>.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("QTLEMM", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("py-chung/QTLEMM")

Development version from py-chung/QTLEMM. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-qtlemm

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-QTLEMM

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-QTLEMM

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 2.2 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-09-08
ERROR12 OK, 1 ERROR2026-09-07
OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 3.1.0

READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 14
Examples that run: 100%14 run in a plain check
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 100%

How these are measured

Downloads

6.5K

CRAN downloads in the past year

Rank #6,996 · ~18/day · ~545/mo

Releases R versions

Daily download trend is not available in this view yet.

45630 days

1.3K90 days

6.5K1 year

Compare downloads with other packages →

Also on79 r2u8 autocran

How downloads are counted

Repository

py-chung/qtlemm ↗Account: py-chung

0Stars

0Forks

0Open issues

0Open PRs

1Releases

60Commits

1Commit identities

60 commits · Last activity 2025-09-16

Responsiveness

not measured

Releases over time

2024-03-18 · 12026-07-07 · 1

How these are measured

PracticesBeta

Checks run against github.com/py-chung/qtlemm on 2026-10-25.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

2 external dependencies (excludes base and recommended)

Installing QTLEMM adds 2 packages (2 with compiled code, 1.2 MB of source tarballs). Heaviest: mvtnorm 1.0 MB, gtools 236 KB.

Depends (0)

none

Imports (6)

mvtnormutilsstatsgraphicsgrDevicesgtools

LinkingTo (0)

none

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (8)

Ping-Yuan Chung

Maintainer since 0.1.0 (2021)

Y.-T. Guo

Author · added in 1.3.0

H.-N. Ho

Author · added in 1.3.0

Chen-Hung Kao

Author

H.-I. Lee

Author · added in 1.3.0

P.-Y. Wu

Author · added in 1.3.0

M.-H. Yang

Author · added in 1.3.0

M.-H. Zeng

Author · added in 1.3.0

Releases (20)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
3.1.0Latest
record
2025-09-12 · current release · diff ↗
R
R 4.5.0 released · 2025-04-11
3.0.1
record
2025-03-11 · diff ↗
3.0.0
record
2025-02-21 · diff ↗ ·
removed 4 exports
EM.MIM2, IM.search2, MIM.points2, MIM.search2
2.1.0
record
2024-06-25 · diff ↗
2.0.0
record
2024-06-21 · diff ↗ ·
added 1 export
Qhot.EQF
1.5.4
record
2024-05-17 · diff ↗
1.5.3
record
2024-04-26 · diff ↗
R
R 4.4.0 released · 2024-04-24
1.5.2
record
2024-03-13 · diff ↗
1.5.1
record
2024-02-29 · diff ↗
1.5.0
record
2024-01-23 · diff ↗ ·
added 1 export
EM.MIMv
1.4.1
record
2023-10-23 · diff ↗
1.4.0
record
2023-10-13 · diff ↗
1.3.1
record
2023-08-15 · diff ↗

Show 10 earlier eventsHide 10 earlier events

1.3.0
record
2023-08-08 · diff ↗
1.2.0
record
2023-06-05 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.1.3
record
2022-10-07 · diff ↗
1.1.2
record
2022-09-08 · diff ↗ ·
added 1 export
Qhot
R
R 4.2.0 released · 2022-04-22
1.1.0
record
2021-10-13 · diff ↗
1.0.0
record
2021-09-03 · diff ↗
0.1.0
record
2021-06-11
R
R 4.1.0 released · 2021-05-18

Package metadata

First published: 2021-06-11
Total releases: 20 / 5 yrs
License: GPL-2 OSI
Download size: 1.9 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("QTLEMM")

Format

Chung, P., Guo, Y. -., Ho, H. -., Kao, C., Lee, H. -., Wu, P. -., Yang, M. -., & Zeng, M. -. (2025). QTLEMM: QTL EM Algorithm Mapping and Hotspots Detection (Version 3.1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.QTLEMM

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for QTLEMM version 3.1.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →