R Observatory: Metrics for DGEAR version 0.2.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

DGEAR

0.2.1Package record

Differential Gene Expression Analysis with R

0packages depend

2.8Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Koushik BardhanCRAN page ↗

Analyses gene expression data derived from microarray experiments to detect differentially expressed genes (DEGs) by employing majority voting across five statistical models: Welch t-test, one-way ANOVA, Dunnett's test, Half's modified t-test, and the Wilcoxon-Mann-Whitney U-test. Combined p-values are computed with Fisher's method. Gene annotation is optional: users may supply a GEO SOFT annotation table or rely on row names directly. Boyer, R.S., Moore, J.S. (1991) doi:10.1007/978-94-011-3488-0_5.

Changes in 0.2.1

Breaking changes

read_and_preprocess_data() has been removed. Its responsibilities are now handled internally by each test function via the new .prepare_data() helper in utils.R. Existing scripts that called this function directly must be updated to pass dataframe, con1, con2, exp1, exp2 to the test functions or to DGEAR() instead.

New features

**Unified function interface**: all five test functions (perform_t_test, perform_anova, perform_dunnett_test, perform_h_test, perform_wilcox_test) now share a consistent signature: (dataframe, con1, con2, exp1, exp2, alpha = 0.05, annot_df = NULL).
**Optional gene annotation** (annot_df): users may supply a GEO SOFT-style annotation data.frame with columns ID and Gene.Symbol (or Gene.symbol) to map probe row names to gene symbols. When annot_df = NULL (the default), row names of dataframe are used directly — making the package fully usable without any annotation file.

Show all changes in 0.2.1Hide the rest of the changes in 0.2.1

**Richer DGEAR() return value**: the main function now returns a named list with four elements:
DEGs — genes that passed majority voting
FDR_Table — per-test BH-adjusted p-values, Fisher-combined FDR, ensemble voting score, and log2FC for every gene
Results_Table — concise summary (G_Symbol, CombineFDR, log2FC, Ensemble)
IndividualTests — raw Table and DEGs output from each of the five test functions
**Fisher's combined p-value**: DGEAR() now computes a combined p-value across all five tests using metapod::parallelFisher and includes it as CombineFDR in FDR_Table and Results_Table.
**Internal helpers in utils.R**: .prepare_data() centralises log2 normalisation and .resolve_symbols() centralises gene symbol resolution, eliminating code duplication across test files.
**Defensive Dunnett test**: perform_dunnett_test() now silently assigns NA p-values to genes with zero variance, NA values, or infinite values, rather than throwing an error that would abort the full analysis.
**Input validation in DGEAR()**: informative stop() messages are raised for invalid column ranges, alpha outside (0, 1), or votting_cutoff outside 1–5.
**82-test testthat suite**: tests/testthat/ now contains 7 test files covering structure, value sanity, biological correctness, defensive handling, alpha/cutoff sensitivity, and annotation behaviour for every exported function.
**Interactive demo script**: inst/examples/DGEAR_demo.R is a fully annotated walkthrough callable via source(system.file("examples", "DGEAR_demo.R", package = "DGEAR")).

Bug fixes

Eliminated the R CMD check NOTE *"no visible binding for global variable 'G_Symbol'"* by removing all reliance on globally defined annotation vectors. Gene symbols are now always resolved locally inside each function.
Removed library(DGEAR) from all \examples{} blocks in .Rd files; R CMD check loads the package automatically, so the call caused an error.
Wrapped perform_dunnett_test() examples in \donttest{} to prevent R CMD check failures from the DescTools::DunnettTest external dependency in constrained check environments.
fdr columns are now consistently typed as integer (0L / 1L) rather than a mix of NA and numeric 1.

---

From NEWS.md in the release

Install

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

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

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

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-dgear

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-DGEAR

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-DGEAR

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: 2.0 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-09
ERROR12 OK, 1 ERROR2026-06-08
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.2.1

READMEYes · 421 wordsVignettesNoNEWSYes · 67% structured · mentions 0.2.1Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 9 (2 internal)
Examples that run: 100%7 run in a plain check
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 11%

How these are measured

Downloads

2.8K

CRAN downloads in the past year

Rank #10,189 · ~8/day · ~235/mo

Releases R versions

Daily download trend is not available in this view yet.

37430 days

98590 days

2.8K1 year

Compare downloads with other packages →

Also on75 r2u6 autocran

How downloads are counted

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Installing DGEAR adds 49 packages (32 with compiled code, 26 MB of source tarballs). Heaviest: data.table 5.7 MB, DescTools 2.6 MB, readxl 2.1 MB. 1 more not on CRAN is not measured.

Depends (1)

R >= 3.5.0

Imports (2)

DescTools metapod

LinkingTo (0)

none

Suggests (2)

spelling testthat

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 (2)

Koushik Bardhan

Author, Maintainer since 0.1.3 (2023), Contributor

Chiranjib Sarkar

Author, Thesis advisor

Releases (3)

Pick two releases to compare their code metrics.

0.2.1Latest
record
2026-07-03 · current release · diff ↗ ·
removed 1 export
read_and_preprocess_data
R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
0.1.4
record
2024-06-26 · diff ↗
R
R 4.4.0 released · 2024-04-24
0.1.3
record
2023-08-30
R
R 4.3.0 released · 2023-04-21

Package metadata

First published: 2023-08-30
Total releases: 3 / 3 yrs
License: MIT + file LICENSE OSI · relicensed from GPL-3 in 0.1.4
Minimum R: ≥ 3.5.0
Bundled data: 0.5 KB / 1 file
Download size: 15 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("DGEAR")

Format

Bardhan, K., & Sarkar, C. (2026). DGEAR: Differential Gene Expression Analysis with R (Version 0.2.1) [Computer software]. https://doi.org/10.32614/CRAN.package.DGEAR

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 DGEAR version 0.2.1 [Data set]. HJJB, LLC. Data release v2026-10-19. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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