An analysis toolkit focused on genes. It mainly includes five
    features (search, convert, analysis, plot, and export).
    The user just needs to input feature id ('entrez', 'symbol', 'ensembl' or
    'uniprot') to retrieve feature information and 'PubMed'<https://pubmed.ncbi.nlm.nih.gov/> records, 
    to convert id types, to easily handle gene enrichment analysis and publication-level figures, 
    to plot group interaction and export results as sheets in one 'excel'
    file to easily share and communicate with others.

Using simple input, this package creates plots of gene models. Users can create plots of alternatively spliced gene variants and the positions of mutations and other gene features.

Analyzes gene expression
  (time series) data with focus on the inference of gene networks.
  In particular, GeneNet implements the methods of Schaefer and 
  Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007)
  for learning large-scale gene association networks (including
  assignment of putative directions).

A collection of methods to extract gene programs from single-cell gene expression data using non-negative matrix factorization (NMF). 'GeneNMF' contains functions to directly interact with the 'Seurat' toolkit and derive interpretable gene program signatures.

Package for Genetic Epidemiologic Methods Developed at MSKCC. It contains functions to calculate haplotype specific odds ratio and the power of two stage design for GWAS studies.

Makes the Genepop software available in R. This software implements a mixture of traditional population genetic methods and some more focused developments: it computes exact tests for Hardy-Weinberg equilibrium, for population differentiation and for genotypic disequilibrium among pairs of loci; it computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc.; and it performs analyses of isolation by distance from pairwise comparisons of individuals or population samples.