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r-geode
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Given expression data this package calculate a multivariate geometrical characterization of the differential expression and can also perform gene-set enrichment.
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2025-04-22 |
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r-geoboxplot
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Make geographic box plot as detailed in Willmott et al. (2007).
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2025-04-22 |
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r-genwin
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Defines window or bin boundaries for the analysis of genomic data. Boundaries are based on the inflection points of a cubic smoothing spline fitted to the raw data. Along with defining boundaries, a technique to evaluate results obtained from unequally-sized windows is provided. Applications are particularly pertinent for, though not limited to, genome scans for selection based on variability between populations (e.g. using Wright's fixations index, Fst, which measures variability in subpopulations relative to the total population).
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2025-04-22 |
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r-gentag
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Implement a coherent and flexible protocol for animal color tagging. 'GenTag' provides a simple computational routine with low CPU usage to create color sequences for animal tag. First, a single-color tag sequence is created from an algorithm selected by the user, followed by verification of the combination uniqueness. Three methods to produce color tag sequences are provided. Users can modify the main function core to allow a wide range of applications.
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2025-04-22 |
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r-gensemble
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Generalized ensemble methods allowing arbitrary underlying models to be used. Currently only bagging is supported.
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2025-04-22 |
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r-genord
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A gaussian copula based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.
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2025-04-22 |
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r-genoplotr
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Draws gene or genome maps and comparisons between these, in a publication-grade manner. Starting from simple, common files, it will draw postscript or PDF files that can be sent as such to journals.
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2025-04-22 |
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r-genomicper
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Circular genomic permutation approach uses GWAS results to establish the significance of pathway/gene-set associations whilst accounting for genomic structure. All SNPs in the GWAS are placed in a 'circular genome' according to their location. Then the complete set of SNP association p-values are permuted by rotation with respect to the SNPs' genomic locations. Two testing frameworks are available: permutations at the gene level, and permutations at the SNP level. The permutation at the gene level uses fisher's combination test to calculate a single gene p-value, followed by the hypergeometric test. The SNP count methodology maps each SNP to pathways/gene-sets and calculates the proportion of SNPs for the real and the permutated datasets above a pre-defined threshold. Genomicper requires a matrix of GWAS association p-values. The SNPs annotation and pathways annotations can be performed within the package or provided by the user.
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2025-04-22 |
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r-genomic.autocorr
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Local structure in genomic data often induces dependence between observations taken at different genomic locations. Ignoring this dependence leads to underestimation of the standard error of parameter estimates. This package uses block bootstrapping to estimate asymptotically correct standard errors of parameters from any standard generalised linear model that may be fit by the glm() function.
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2025-04-22 |
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r-genmeta
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Generalized meta-analysis is a technique for estimating parameters associated with a multiple regression model through meta-analysis of studies which may have information only on partial sets of the regressors. It estimates the effects of each variable while fully adjusting for all other variables that are measured in at least one of the studies. Using algebraic relationships between regression parameters in different dimensions, a set of moment equations is specified for estimating the parameters of a maximal model through information available on sets of parameter estimates from a series of reduced models available from the different studies. The specification of the equations requires a reference dataset to estimate the joint distribution of the covariates. These equations are solved using the generalized method of moments approach, with the optimal weighting of the equations taking into account uncertainty associated with estimates of the parameters of the reduced models. The proposed framework is implemented using iterated reweighted least squares algorithm for fitting generalized linear regression models. For more details about the method, please see pre-print version of the manuscript on generalized meta-analysis by Prosenjit Kundu, Runlong Tang and Nilanjan Chatterjee (2018) <arXiv:1708.03818>.
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2025-04-22 |
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r-geneticsubsetter
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Finds subsets of sets of genotypes with a high Heterozygosity, and Mean of Transformed Kinships (MTK), measures that can indicate a subset would be beneficial for rare-trait discovery and genome-wide association scanning, respectively.
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2025-04-22 |
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r-genetics
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Classes and methods for handling genetic data. Includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ...
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2025-04-22 |
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r-genesysr
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Access data on plant genetic resources from genebanks around the world published on Genesys (<https://www.genesys-pgr.org>). Your use of data is subject to terms and conditions available at <https://www.genesys-pgr.org/content/legal/terms>.
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2025-04-22 |
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r-genesignaturefinder
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A tool for finding an ensemble gene-signature by a steepest ascending algorithm partially supervised by survival time data.
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2025-04-22 |
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r-generator
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Allows users to quickly and easily generate fake data containing Personally Identifiable Information (PII) through convenience functions.
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2025-04-22 |
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r-generaloaxaca
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Perform the Blinder-Oaxaca decomposition for generalized linear model with bootstrapped standard errors. The twofold and threefold decomposition are given, even the generalized linear model output in each group.
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2025-04-22 |
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r-generalizedhyperbolic
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Functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, normal inverse Gaussian distribution and generalized inverse Gaussian distribution, including fitting of these distributions to data. Linear models with hyperbolic errors may be fitted using hyperblmFit.
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2025-04-22 |
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r-generalhoslem
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Functions to assess the goodness of fit of binary, multinomial and ordinal logistic models. Included are the Hosmer-Lemeshow tests (binary, multinomial and ordinal) and the Lipsitz and Pulkstenis-Robinson tests (ordinal).
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2025-04-22 |
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r-genemodel
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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.
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2025-04-22 |
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r-genelistpie
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"geneListPie" package is for mapping a gene list to function categories defined in GOSlim or Kegg. The results can be plotted as a pie chart to provide a quick view of the genes distribution of the gene list among the function categories. The gene list must contain a list of gene symbols. The package contains a set of pre-processed gene sets obtained from Gene Ontology and MSigDB including human, mouse, rat and yeast. To provide a high level concise view, only GO slim and kegg are provided. The gene sets are regulared updated. User can also use customized gene sets. User can use the R Pie() or Pie3D() function for plotting the pie chart. Users can also choose to output the gene function mapping results and use external software such as Excel(R) for ploting.
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2025-04-22 |
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r-genef
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This package implements several generalized F-statistics. The current version includes a generalized F-statistic based on the flexible isotonic/monotonic regression or order restricted hypothesis testing.
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2025-04-22 |
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r-gendist
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Computes the probability density function (pdf), cumulative distribution function (cdf), quantile function (qf) and generates random values (rg) for the following general models : mixture models, composite models, folded models, skewed symmetric models and arc tan models.
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2025-04-22 |
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r-genderizer
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Utilizes the 'genderize.io' Application Programming Interface to predict gender from first names extracted from a text vector. The accuracy of prediction could be controlled by two parameters: counts of a first name in the database and probability of prediction.
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2025-04-22 |
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r-gendata
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Set of functions to create datasets using a correlation matrix.
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2025-04-22 |
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r-genbinomapps
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Density, distribution function, quantile function and random generation for the Generalized Binomial Distribution. Functions to compute the Clopper-Pearson Confidence Interval and the required sample size. Enhanced model for burn-in studies, where failures are tackled by countermeasures.
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2025-04-22 |
