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r-mlphaser
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Phase haplotypes from genotypes based on a list of known haplotypes. Suited to highly diverse loci such as HLA.
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2023-06-16 |
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r-milc
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The MILC package is designed to predict individual trajectories using the continuous time microsimulation model MILC, that describes the natural history of lung cancer.
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2023-06-16 |
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r-meth27qc
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Meth27QC is a tool for analyzing Illumina Infinium HumanMethylation27 BeadChip Data and generating QC reports. This package allows users quickly assess data quality of the Assay. Users can evaluate the data quality in the way that Illumina GenomeStudio/BeadStudio recommended based on the control probes. The package reads files exported from GenomeStudio/BeadStudio software, generating intensity and standard deviation plots grouped by the types of the control probes. Meth27 carries 40 control probes for staining, hybridization, target removal, extension, bisulfite conversion, specificity, negative and non-polymorphic controls. Details of those control probes can be found in the Infinium Assay for Methylation Protocol Guide from Illumina.We also used the other non-control probes to plot intensity of detected genes, signal average for green and red. Outliers can be identified.
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2023-06-16 |
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r-mcc
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A number of biomedical problems involve performing many hypothesis tests, with an attendant need to apply stringent thresholds. Often the data take the form of a series of predictor vectors, each of which must be compared with a single response vector, perhaps with nuisance covariates. Parametric tests of association are often used, but can result in inaccurate type I error at the extreme thresholds, even for large sample sizes. Furthermore, standard two-sided testing can reduce power compared to the doubled p-value, due to asymmetry in the null distribution. Exact (permutation) testing approaches are attractive, but can be computationally intensive and cumbersome. MCC is an approximation to exact association testing of two vectors that is accurate and fast enough for standard use in high-throughput settings, and can easily provide standard two-sided or doubled p-values.
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2023-06-16 |
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r-mattools
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This package in includes functions for receiver operating characteristic (ROC) analyses as well as Monte Carlo simulation. It includes specific graphical functions for interpreting the output of these techniques.
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2023-06-16 |
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r-linlir
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This package implements the methodology of Likelihood-based Imprecise Regression (LIR) for the case of linear regression with interval data.
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2023-06-16 |
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r-laercio
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The package contains functions to compare and group means.
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2023-06-16 |
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r-netdata
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This package contains all data needed for Dan McFarland's SNA R labs.
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2023-06-16 |
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r-mvcwt
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Computes the continuous wavelet transform of irregularly sampled time series.
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2023-06-16 |
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r-mavtgsa
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This package is a gene set analysis function for one-sided test (OLS), two-sided test (multivariate analysis of variance). If the experimental conditions are equal to 2, the p-value for Hotelling's t^2 test is calculated. If the experimental conditions are great than 2, the p-value for Wilks' Lambda is determined and post-hoc test is reported too. Three multiple comparison procedures, Dunnett, Tukey, and sequential pairwise comparison, are implemented. The program computes the p-values and FDR (false discovery rate) q-values for all gene sets. The p-values for individual genes in a significant gene set are also listed. MAVTgsa generates two visualization output: a p-value plot of gene sets (GSA plot) and a GST-plot of the empirical distribution function of the ranked test statistics of a given gene set. A Random Forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes.
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2023-06-16 |
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r-lrth
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R code of a likelihood ratio test for genome-wide association under genetic heterogeneity.
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2023-06-16 |
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r-localcontrolstrategy
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Especially when cross-sectional data are observational, effects of treatment selection bias and confounding are revealed by using the Nonparametric and Unsupervised "preprocessing" methods central to Local Control (LC) Strategy. The LC objective is to estimate the "effect-size distribution" that best quantifies a potentially causal relationship between a numeric y-Outcome variable and a t-Treatment variable. This t-variable may be either binary {1 = "new" vs 0 = "control"} or a numeric measure of Exposure level. LC Strategy starts by CLUSTERING experimental units (patients) on their pre-exposure X-Covariates, forming mutually exclusive and exhaustive BLOCKS of relatively well-matched units. The implicit statistical model for LC is thus simple one-way ANOVA. The Within-Block measures of effect-size are Local Rank Correlations (LRCs) when Exposure is numeric with more than two levels. Otherwise, Treatment choice is Nested within BLOCKS, and effect-sizes are LOCAL Treatment Differences (LTDs) between within-cluster y-Outcome Means ["new" minus "control"]. An Instrumental Variable (IV) method is also provided so that Local Average y-Outcomes (LAOs) within BLOCKS may also contribute information for effect-size inferences ...assuming that X-Covariates influence only Treatment choice or Exposure level and otherwise have no direct effects on y-Outcome. Finally, a "Most-Like-Me" function provides histograms of effect-size distributions to aid Doctor-Patient communications about Personalized Medicine.
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2023-06-16 |
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r-mbi
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Over 20 multiple-site diversity indices can be calculated. Later versions will include phylogenetic diversity
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2023-06-16 |
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r-mbcluster.seq
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Cluster genes based on Poisson or Negative-Binomial model for RNA-Seq or other digital gene expression (DGE) data
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2023-06-16 |
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r-lllcrc
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Applies local log-linear capture-recapture models (LLLMs) for closed populations, as described in the doctoral thesis of Zachary Kurtz. The method is relevant when there are 3-5 capture occasions, with auxiliary covariates available for all capture occasions. As part of estimating the number of missing population units, the method estimates the "rate of missingness" as it varies over the covariate space. In addition, user-friendly functions are provided to recreate (approximately) the method of Zwane and van der Heijden (2004), which applied the VGAM package in a way that is closely related to LLLMs.
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2023-06-16 |
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r-leafletr
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Display your spatial data on interactive web-maps using the open-source JavaScript library Leaflet. 'leafletR' provides basic web-mapping functionality to combine vector data and online map tiles from different sources. See <http://leafletjs.com> for more information on Leaflet.
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2023-06-16 |
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r-multinbmod
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This is a likelihood approach for the regression analysis of overdispersed correlated count data with cluster varying covariates. The approach fits a multivariate negative binomial model by maximum likelihood and provides robust estimates of the regression coefficients.
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2023-06-16 |
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r-msap
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public |
Statistical Analyses of Methylation-sensitive Amplification Polymorphism (MSAP) assays.
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2023-06-16 |
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r-motilitylab
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Statistics to quantify tracks of moving things (x-y-z-t data), such as cells, bacteria or animals. Available measures include mean square displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension.
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2023-06-16 |
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r-modcmfitr
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Fits a modified version of the Connor-Mosimann distribution (Connor & Mosimann (1969)<doi:10.2307/2283728>), a Connor-Mosimann distribution or Dirichlet distribution (e.g. Gelman, Carlin, Stern & Rubin Chapter 3.5 (2004, <ISBN:1-58488-388-X>) to elicited quantiles of a multinomial distribution. Code is also provided to sample from the distributions, generating inputs suitable for a probabilistic sensitivity analysis / Monte Carlo simulation in a decision model.
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2023-06-16 |
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r-mixmap
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A collection of functions to implement the MixMAP algorithm, which performs gene level tests of association using data from a previous GWAS or data from a meta-analysis of several GWAS. Conceptually, genes are detected as significant if the collection of p-values within a gene are determined to be collectively smaller than would be observed by chance.
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2023-06-16 |
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r-metapca
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MetaPCA implements simultaneous dimension reduction using PCA when multiple studies are combined. We propose two basic ideas to find a common PC subspace by eigenvalue maximization approach and angle minimization approach, and we extend the concept to incorporate Robust PCA and Sparse PCA in the meta-analysis realm.
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2023-06-16 |
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r-lshorth
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Calculates the (localised) length of the shorth and supplies corresponding diagnostic plots.
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2023-06-16 |
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r-lazyrmd
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An R Markdown html document format that provides the ability to lazily load plot outputs as the user scrolls over them. This is useful for large R Markdown documents with many plots, as it allows for a fast initial page load and defers loading of individual graphics to the time that the user navigates near them.
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2023-06-16 |
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r-nhds
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The National Hospital Discharge Survey (2010) summarizes the state of patients at the end of their hospital admissions. The US CDC publishes the data in the public domain, and describes it as follows: The National Hospital Discharge Survey (NHDS) is a continuing nationwide sample survey of short-stay hospitals in the United States. The scope of NHDS encompasses patients discharged from noninstitutional hospitals, exclusive of military and Department of Veterans Affairs hospitals, located in the 50 States and the District of Columbia. Only hospitals having six or more beds for in-patient use are included in the survey. See <https://www.cdc.gov/nchs/nhds> for more information.
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2023-06-16 |
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r-ncg
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Computes the noncentral gamma function: pdf, cdf, quantile function and inverse for the noncentrality parameter.
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2023-06-16 |
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r-mwridge
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A two stage moving-window Ridge method for coefficients estimation and model prediction. In the first stage, moving-window penalty and L1 penalty are applied. In the second stage, ridge regression is applied.
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2023-06-16 |
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r-mpe
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Functions for calculating sample size and power for clinical trials with multiple (co-)primary endpoints.
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2023-06-16 |
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r-mpcmp
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A collection of functions for estimation, testing and diagnostic checking for the mean-parametrized Conway-Maxwell Poisson (COM-Poisson) regression model of Huang (2017) <doi:10.1177/1471082X17697749>.
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2023-06-16 |
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r-morgenstemning
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This package is a port of the MATLAB colourmap functions accompanying the paper M. Geissbuehler and T. Lasser, "How to display data by color schemes compatible with red-green color perception deficiencies," Opt. Express 21, 9862-9874 (2013) to R.
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2023-06-16 |
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r-mixtureinf
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Functions for computing the penalized maximum likelihood estimate (PMLE) or maximum likelihood estimate (MLE), testing the order of a finite mixture model using EM-test, drawing histogram of observations and the fitted density or probability mass function of the mixture model.
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2023-06-16 |
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r-mixtnb
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Differential expression analysis of RNA-Seq data when replicates under two conditions are available is performed. First, mixtures of Negative Binomial distributions are fitted on the data in order to estimate the dispersions, then the Wald test is computed.
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2023-06-16 |
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r-metstat
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A diverse collection of metabolomics related statistical tools.
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2023-06-16 |
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r-mcheatmaps
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mcheatmaps serves to visualize multiple different symmetric matrices and matrix clusters in a single figure using a dendogram, two half matrices and various color labels.
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2023-06-16 |
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r-lga
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Tools for linear grouping analysis. Three user-level functions: gap, rlga and lga.
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2023-06-16 |
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r-nlmeode
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This package combines the odesolve and nlme packages for mixed-effects modelling using differential equations.
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2023-06-16 |
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r-multisv
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MultiSV is an R package for identification of structural variations in multiple populations based on whole genome resequencing. It fits linear mixed model and identifies structural variations in multiple populations using whole genome sequencing data. It could also be manipulated to use on RNA-seq data for differential gene expression (implementation in future releases). Main steps for analysis include generating read depth in bins using ComputeBinCounts. conversion of bins to MultiSV format using Bin2MultiSV. Finally, identification of structural variations using CallMultiSV.
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2023-06-16 |
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r-morder
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MOrder provide functions to check time homogeneity and order of markov chain by using chi-squared test, AIC value and BIC value.
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2023-06-16 |
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r-mixrasch
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Estimates Rasch models and mixture Rasch models, including the dichotomous Rasch model, the rating scale model, and the partial credit model.
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2023-06-16 |
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r-metnorm
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Metabolomics data are inevitably subject to a component of unwanted variation, due to factors such as batch effects, matrix effects, and confounding biological variation. This package contains a collection of R functions which can be used to remove unwanted variation and obtain normalized metabolomics data.
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2023-06-16 |
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r-linkim
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A linkage information based method for imputing missing diploid genotypes
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2023-06-16 |
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r-myrrixjars
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External jars required for package 'Myrrix'. 'Myrrix' is a recommendation engine.
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2023-06-16 |
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r-mustat
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Performs Wilcox rank sum test, Kruskal rank sum test, Friedman rank sum test and McNemar test.
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2023-06-16 |
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r-mssqlr
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Can be used to query data from data from Microsoft SQL Server (MSSQL, see <http://www.microsoft.com/sqlserver/> for more information). Based on the concepts of Entity Framework, the package allows querying data from MSSQL Database.
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2023-06-16 |
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r-nfca
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Numerical Formal Concept Analysis (nFCA) is a modern unsupervised learning tool for analyzing general numerical data. Given input data, this R package nFCA outputs two nFCA graphs: a H-graph and an I-graph that reveal systematic, hierarchical clustering and inherent structure of the data.
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2023-06-16 |
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r-modygliani
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RMSD and Internal Energy analysis of NAMD and YASARA Molecular Dynamics output files. Allows to comparison of different dynamics per different complexes. Input files have to be ASCII files tab separated.
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2023-06-16 |
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r-nearender
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Performs network enrichment analysis against functional gene sets. Benchmarks networks. Renders raw gene profile matrices of dimensionality "N genes x N samples" into the space of gene set (typically pathway) enrichment scores of dimensionality "N pathways x N samples".
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2023-06-16 |
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r-myepisodes
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Useful functions for accessing MyEpisodes feeds and episode information as well as other tv episode related actions through www.myepisodes.com
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2023-06-16 |
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r-mixemm
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Contains functions for estimating a mixed-effects model for clustered data (or batch-processed data) with cluster-level (or batch- level) missing values in the outcome, i.e., the outcomes of some clusters are either all observed or missing altogether. The model is developed for analyzing incomplete data from labeling-based quantitative proteomics experiments but is not limited to this type of data. We used an expectation conditional maximization (ECM) algorithm for model estimation. The cluster-level missingness may depend on the average value of the outcome in the cluster (missing not at random).
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2023-06-16 |
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r-muficokriging
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This package builds multi-fidelity cokriging models from responses with different levels of fidelity. Important functions : MuFicokm, predict.MuFicokm, summary.MuFicokm.
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2023-06-16 |
