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r-ampir
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public |
A toolkit to predict antimicrobial peptides from protein sequences on a genome-wide scale. It incorporates two support vector machine models ("precursor" and "mature") trained on publicly available antimicrobial peptide data using calculated physico-chemical and compositional sequence properties described in Meher et al. (2017) <doi:10.1038/srep42362>. In order to support genome-wide analyses, these models are designed to accept any type of protein as input and calculation of compositional properties has been optimised for high-throughput use. For best results it is important to select the model that accurately represents your sequence type: for full length proteins, it is recommended to use the default "precursor" model. The alternative, "mature", model is best suited for mature peptide sequences that represent the final antimicrobial peptide sequence after post-translational processing. For details see Fingerhut et al. (2020) <doi:10.1093/bioinformatics/btaa653>. The 'ampir' package is also available via a Shiny based GUI at <https://ampir.marine-omics.net/>.
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2025-09-24 |
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r-osmdata
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public |
Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server and processed with very fast 'C++' routines for return to 'R'.
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2025-09-24 |
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r-fme
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public |
Provides functions to help in fitting models to data, to perform Monte Carlo, sensitivity and identifiability analysis. It is intended to work with models be written as a set of differential equations that are solved either by an integration routine from package 'deSolve', or a steady-state solver from package 'rootSolve'. However, the methods can also be used with other types of functions.
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2025-09-24 |
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r-gluedown
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public |
Ease the transition between R vectors and markdown text. With 'gluedown' and 'rmarkdown', users can create traditional vectors in R, glue those strings together with the markdown syntax, and print those formatted vectors directly to the document. This package primarily uses GitHub Flavored Markdown (GFM), an offshoot of the unambiguous CommonMark specification by John MacFarlane (2019) <https://spec.commonmark.org/>.
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2025-09-24 |
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r-comparegroups
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public |
Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
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2025-09-24 |
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r-ggfx
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public |
Provides a range of filters that can be applied to layers from the 'ggplot2' package and its extensions, along with other graphic elements such as guides and theme elements. The filters are applied at render time and thus uses the exact pixel dimensions needed.
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2025-09-24 |
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r-bvar
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public |
Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.
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2025-09-24 |
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r-ggpackets
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public |
Create groups of 'ggplot2' layers that can be easily migrated from one plot to another, reducing redundant code and improving the ability to format many plots that draw from the same source 'ggpacket' layers.
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2025-09-24 |
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r-dotwhisker
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public |
Quick and easy dot-and-whisker plots of regression results.
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2025-09-24 |
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r-onesamplemr
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public |
Useful functions for one-sample (individual level data) Mendelian randomization and instrumental variable analyses. The package includes implementations of; the Sanderson and Windmeijer (2016) <doi:10.1016/j.jeconom.2015.06.004> conditional F-statistic, the multiplicative structural mean model Hernán and Robins (2006) <doi:10.1097/01.ede.0000222409.00878.37>, and two-stage predictor substitution and two-stage residual inclusion estimators explained by Terza et al. (2008) <doi:10.1016/j.jhealeco.2007.09.009>.
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2025-09-24 |
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r-smoother
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public |
A collection of methods for smoothing numerical data, commencing with a port of the Matlab gaussian window smoothing function. In addition, several functions typically used in smoothing of financial data are included.
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2025-09-24 |
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pz-rail-base
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public |
Base classes and core code for Redshift Assessment Infrastructure Layers
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2025-09-24 |
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r-tibbletime
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public |
Built on top of the 'tibble' package, 'tibbletime' is an extension that allows for the creation of time aware tibbles. Some immediate advantages of this include: the ability to perform time-based subsetting on tibbles, quickly summarising and aggregating results by time periods, and creating columns that can be used as 'dplyr' time-based groups.
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2025-09-24 |
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edalize
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public |
Edalize is a library for interfacing EDA tools, primarily for FPGA development
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2025-09-24 |
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r-sirius-ms
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public |
RSirius: R library for SIRIUS MS/MS analyses software.
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2025-09-24 |
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r-whirl
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public |
Logging of scripts suitable for clinical trials using 'Quarto' to create nice human readable logs. 'whirl' enables execution of scripts in batch, while simultaneously creating logs for the execution of each script, and providing an overview summary log of the entire batch execution.
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2025-09-24 |
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r-vcr
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public |
Record test suite 'HTTP' requests and replays them during future runs. A port of the Ruby gem of the same name (<https://github.com/vcr/vcr/>). Works by hooking into the 'webmockr' R package for matching 'HTTP' requests by various rules ('HTTP' method, 'URL', query parameters, headers, body, etc.), and then caching real 'HTTP' responses on disk in 'cassettes'. Subsequent 'HTTP' requests matching any previous requests in the same 'cassette' use a cached 'HTTP' response.
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2025-09-24 |
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r-tidycdisc
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public |
Provides users a quick exploratory dive into common visualizations without writing a single line of code given the users data follows the Analysis Data Model (ADaM) standards put forth by the Clinical Data Interchange Standards Consortium (CDISC) <https://www.cdisc.org>. Prominent modules/ features of the application are the Table Generator, Population Explorer, and the Individual Explorer. The Table Generator allows users to drag and drop variables and desired statistics (frequencies, means, ANOVA, t-test, and other summary statistics) into bins that automagically create stunning tables with validated information. The Population Explorer offers various plots to visualize general trends in the population from various vantage points. Plot modules currently include scatter plot, spaghetti plot, box plot, histogram, means plot, and bar plot. Each plot type allows the user to plot uploaded variables against one another, and dissect the population by filtering out certain subjects. Last, the Individual Explorer establishes a cohesive patient narrative, allowing the user to interact with patient metrics (params) by visit or plotting important patient events on a timeline. All modules allow for concise filtering & downloading bulk outputs into html or pdf formats to save for later.
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2025-09-24 |
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r-eicu.demo
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public |
The eICU Collaborative Research Database is a multi-center
database comprised of deidentified health data for over 200,000 admissions
to ICUs across the United States between 2014-2015. The database includes
vital sign measurements, care plan documentation, severity of illness
measures, diagnosis information, and treatment information. An open-access
subset of eICU, comprising 2,500 unit stays selected from 20 of the larger
hospitals in the eICU Collaborative Research Database is distributed under
the Open Database License (ODbL) v1.0 and is provided as R package for
convenience.
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2025-09-24 |
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r-simdesign
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public |
Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, implicitly supports parallel processing with high-quality random number generation, and provides tools for managing high-performance computing (HPC) array jobs submitted to schedulers such as SLURM. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.
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2025-09-24 |
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r-sparklyr.nested
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public |
A 'sparklyr' extension adding the capability to work easily with nested data.
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2025-09-24 |
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r-mrfdepth
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public |
Tools to compute depth measures and implementations of related tasks such as outlier detection, data exploration and classification of multivariate, regression and functional data.
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2025-09-24 |
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r-knn.covertree
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public |
Similarly to the 'FNN' package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) <doi:10.1145/1143844.1143857>.
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2025-09-24 |
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r-sparkr
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public |
Provides an R Front end for 'Apache Spark' <https://spark.apache.org>.
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2025-09-24 |
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r-quickmatch
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public |
Provides functions for constructing near-optimal generalized full matching. Generalized full matching is an extension of the original full matching method to situations with more intricate study designs. The package is made with large data sets in mind and derives matches more than an order of magnitude quicker than other methods.
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2025-09-24 |
