This package provides an SCSS compiler, powered by the libsass library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the Sass CSS extension language, which is stable, powerful, and CSS compatible.
This package provides fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the Eigen C++ library for numerical linear algebra and RcppEigen glue.
Recoll finds documents based on their contents as well as their file names. It can search most document formats, but you may need external applications for text extraction. It can reach any storage place: files, archive members, email attachments, transparently handling decompression.
OGRE calculates overlap between user defined genomic region datasets. Any regions can be supplied i.e. genes, SNPs, or reads from sequencing experiments. Key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.
The spqn package implements spatial quantile normalization (SpQN). This method was developed to remove a mean-correlation relationship in correlation matrices built from gene expression data. It can serve as pre-processing step prior to a co-expression analysis.
SAFE is a resampling-based method for testing functional categories in gene expression experiments. SAFE can be applied to 2-sample and multi-class comparisons, or simple linear regressions. Other experimental designs can also be accommodated through user-defined functions.
This package provides a classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.
This package provides several methods for performing permutation tests. It has three main functions, to perform linear permutation tests. These tests are tests where the test statistic is the sum of the product of a covariate (usually group indicator) and the scores.
This package lets you calculate power for generalized linear mixed models, using simulation. It was designed to work with models fit using the lme4 package. The package is described in Green and MacLeod (2016).
This package provides functions for reading array comparative genomic hybridization (aCGH) data from image analysis output files and clone information files, creation of aCGH objects for storing these data. Basic methods are accessing/replacing, subsetting, printing and plotting aCGH objects.
R-scape discovers RNA secondary structure consensus elements. These elements include riboswitches and ribozymes. It utilizes probabilistic modeling of sequence alignments, explicitly considering folding dependencies. The tool enables the de novo search for new structural elements and facilitates comparative analysis of known RNA families.
This package provides tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). The area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.
This package provides S3 classes and methods to create and work with year-quarter, year-month and year-isoweek vectors. Basic arithmetic operations (such as adding and subtracting) are supported, as well as formatting and converting to and from standard R date types.
This package generates well-known integer sequences. The gmp package is adopted for computing with arbitrarily large numbers. Every function has a hyperlink to its corresponding item in the On-Line Encyclopedia of Integer Sequences (OEIS) in the function help page.
Package to integrate methylation and expression data. It can also perform methylation or expression analysis alone. Several plotting functionalities are included as well as a new region analysis based on redundancy analysis. Effect of SNPs on a region can also be estimated.
This package automates analysis workflow for Thermal Shift Analysis (TSA) data. Processing, analyzing, and visualizing data through both shiny applications and command lines. Package aims to simplify data analysis and offer front to end workflow, from raw data to multiple trial analysis.
The Rcpp package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about Rcpp is provided by several vignettes included in this package, via the Rcpp Gallery site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer); see citation("Rcpp") for details on these last two.
R-wrs2 offers a range of strong stats methods from Wilcox WRS functions. It implements robust t-tests, both independent and dependent, robust ANOVA, including designs with between-within subjects, quantile ANOVA, robust correlation, robust mediation, and nonparametric ANCOVA models using robust location measures.
ROCR is a flexible tool for creating cutoff-parameterized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parameterization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism.
The pscl is an R package providing classes and methods for:
Bayesian analysis of roll call data (item-response models);
elementary Bayesian statistics;
maximum likelihood estimation of zero-inflated and hurdle models for count data;
utility functions.
This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study.
This package provides tools for accessing the Botanical Information and Ecology Network (BIEN) database. The BIEN database contains cleaned and standardized botanical data including occurrence, trait, plot and taxonomic data. This package provides functions that query the BIEN database by constructing and executing optimized SQL queries.
The aim of httr is to provide a wrapper for RCurl customised to the demands of modern web APIs. It provides useful tools for working with HTTP organised by HTTP verbs (GET(), POST(), etc). Configuration functions make it easy to control additional request components.
R-coop offers implementations of covariance, correlation and cosine similarity. The implementations are fast and memory-efficient and their use is resolved automatically based on the input data, handled by R's S3 methods. Full descriptions of the algorithms and benchmarks are available in the package vignettes.