'RAMAS Metapop' <https://www.ramas.com/ramas.htm#metapop> is a
popular software package for performing spatially-explicit population
viability analysis. It is primarily GUI-driven, but can benefit from
integration into an R workflow, wherein model results can be subjected to
further analysis. 'RAMAS Metapop' stores metapopulation model parameter
settings and population dynamics simulation results in plain text files
(.mp files). This package facilitates access, summary and visualisation of
'RAMAS Metapop 5' outputs in order to better integrate 'RAMAS' analyses into
an R workflow.
person('John', 'Baumgartner', email='johnbaums@gmail.com',
role = c("aut", "cre"))
methods, utils, grDevices, graphics, stats, raster, sp,
animation, lattice, zoo, rasterVis, latticeExtra, viridis

Standardized Comparison of Workflows in Mass Spectrometry-Based
Bottom-Up Proteomics
Useful functions to analyze proteomic workflows including
number of identifications, data completeness, missed cleavages,
quantitative and retention time precision etc. Various software
outputs are supported such as 'ProteomeDiscoverer', 'Spectronaut', 'DIA-NN'
and 'MaxQuant'.
comprehenr, data.table, dplyr, flowTraceR, forcats, ggplot2,
magrittr, plotly, purrr, stats, stringr, tibble, tidyr, UpSetR
flextable, knitr, rmarkdown, testthat (>= 3.0.0), utils

Marginal regresson models for dependent data
likelihood inference in a class of marginal regression
models for non-normal responses with a flexible specification
of the dependence structure.

Penalized Inverse-Variance Weighted Estimator for Mendelian
Randomization
The penalized inverse-variance weighted (pIVW) estimator is a Mendelian randomization method for estimating the causal effect of an exposure variable on an outcome of interest based on summary-level GWAS data. The pIVW estimator accounts for weak instruments and balanced horizontal pleiotropy simultaneously. See Xu S., Wang P., Fung W.K. and Liu Z. (2022) <doi:10.1111/biom.13732>.

Two Sample Mendelian Randomization using Robust Adjusted Profile
Score
c(person("Qingyuan", "Zhao", email = "qingyzhao@gmail.com", role = c("aut", "cre")))
Mendelian randomization is a method of identifying and estimating a confounded causal effect using genetic instrumental variables. This packages implements methods for two-sample Mendelian randomization with summary statistics by using Robust Adjusted Profile Score (RAPS). References: Qingyuan Zhao, Jingshu Wang, Jack Bowden, Dylan S. Small. Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score. <arXiv:1801.09652>.