Millefy is a tool for visualizing read coverage of scRNA-seq(single-cell RNA sequencing) datasets in genomic contexts. By dynamically and automatically reorder single cells based on locus-specific pseudo time, Millefy highlights cell-to-cell heterogeneity in read coverage of scRNA-seq data.
This package Copynumber KAryotyping of Tumors infers genomic copy number and subclonal structure of human tumors using integrative Bayesian approaches to identify genome-wide aneuploidy at 5MB resolution in single cells data. It separates tumor cells and tumor subclones from normal cells using high-throughput sc-RNAseq data.
This package provides syntax highlighting of R code, specifically designed for the needs of RMarkdown packages like pkgdown, hugodown, and bookdown. It includes linking of function calls to their documentation on the web, and automatic translation of ANSI escapes in output to the equivalent HTML.
This package 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).
This package provides an implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature.
This package provides a generic object traverser for Ruby. It takes the object and recursively yields:
the given object
instance variables, class variables, constants
Hash keys and values
Enumerable members
Struct members
Data members
Range begins and ends
dStruct identifies differentially reactive regions from RNA structurome profiling data. dStruct is compatible with a broad range of structurome profiling technologies, e.g., SHAPE-MaP, DMS-MaPseq, Structure-Seq, SHAPE-Seq, etc. See Choudhary et al., Genome Biology, 2019 for the underlying method.
EpiTxDb facilitates the storage of epitranscriptomic information. More specifically, it can keep track of modification identity, position, the enzyme for introducing it on the RNA, a specifier which determines the position on the RNA to be modified and the literature references each modification is associated with.
To classify Helicobacter pylori genomes according to genetic distance from nine reference populations. The nine reference populations are hpgpAfrica, hpgpAfrica-distant, hpgpAfroamerica, hpgpEuroamerica, hpgpMediterranea, hpgpEurope, hpgpEurasia, hpgpAsia, and hpgpAklavik86-like. The vertex populations are Africa, Europe and Asia.
This package implements the spatially aware library size normalisation algorithm, SpaNorm. SpaNorm normalises out library size effects while retaining biology through the modelling of smooth functions for each effect. Normalisation is performed in a gene- and cell-/spot- specific manner, yielding library size adjusted data.
The Aquo Standard is the Dutch Standard for the exchange of data in water management. With *aquodom* (short for aquo domaintables) it is easy to exploit the API (<https://www.aquo.nl/index.php/Hoofdpagina>) to download domaintables of the Aquo Standard and use them in R.
This package provides a Bayesian smoothing method for post-processing of remote sensing image classification which refines the labelling in a classified image in order to enhance its classification accuracy. Combines pixel-based classification methods with a spatial post-processing method to remove outliers and misclassified pixels.
This package provides a comprehensive toolkit for political linguistics featuring a museum of famous digital gaffes, phonetic transformation algorithms (Soundex, consonant shifts), QWERTY keyboard geometry for typo simulation, syllable parsing, word blending (portmanteau creation), and text corruption analysis. Originally inspired by the infamous "covfefe" tweet of 2017.
Price credit default swaps using C code from the International Swaps and Derivatives Association CDS Standard Model. See <https://www.cdsmodel.com/cdsmodel/documentation.html> for more information about the model and <https://www.cdsmodel.com/cdsmodel/cds-disclaimer.html> for license details for the C code.
This package provides a flexible, extendable representation of an ecological community and a range of functions for analysis and visualisation, focusing on food web, body mass and numerical abundance data. Allows inter-web comparisons such as examining changes in community structure over environmental, temporal or spatial gradients.
This package provides a set of functions to implement the Combined Compromise Solution (CoCoSo) Method created by Yazdani, Zarate, Zavadskas and Turskis (2019) <doi:10.1108/MD-05-2017-0458>. This method is based on an integrated simple additive weighting and compromise exponentially weighted product model.
Designed for network analysis, leveraging the personalized PageRank algorithm to calculate node scores in a given graph. This innovative approach allows users to uncover the importance of nodes based on a customized perspective, making it particularly useful in fields like bioinformatics, social network analysis, and more.
It provides the subset operator for dist objects and a function to compute medoid(s) that are fully parallelized leveraging the RcppParallel package. It also provides functions for package developers to easily implement their own parallelized dist() function using a custom C++'-based distance function.
Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm. For a manual on how to use FDboost', see Brockhaus, Ruegamer, Greven (2017) <doi:10.18637/jss.v094.i10>.
This package provides color palettes designed to be reminiscent of text on paper. The color schemes were taken from <https://stephango.com/flexoki>. Includes discrete, continuous, and binned scales that are not necessarily color-blind friendly. Simple scale and theme functions are available for use with ggplot2'.
Generalized Odds Rate Mixture Cure (GORMC) model is a flexible model of fitting survival data with a cure fraction, including the Proportional Hazards Mixture Cure (PHMC) model and the Proportional Odds Mixture Cure Model as special cases. This package fit the GORMC model with interval censored data.
Write SARIMA models in (finite) AR representation and simulate generalized multiplicative seasonal autoregressive moving average (time) series with Normal / Gaussian, Poisson or negative binomial distribution. The methodology of this method is described in Briet OJT, Amerasinghe PH, and Vounatsou P (2013) <doi:10.1371/journal.pone.0065761>.
Calibration and risk-set calibration methods for fitting Cox proportional hazard model when a binary covariate is measured intermittently. Methods include functions to fit calibration models from interval-censored data and modified partial likelihood for the proportional hazard model, Nevo et al. (2018+) <arXiv:1801.01529>.
Uses data and researcher's beliefs on measurement error and instrumental variable (IV) endogeneity to generate the space of consistent beliefs across measurement error, instrument endogeneity, and instrumental relevance for IV regressions. Package based on DiTraglia and Garcia-Jimeno (2020) <doi:10.1080/07350015.2020.1753528>.