This package provides a curated dataset of publicly available ChIP-sequencing of transcription factors, chromatin remodelers and histone modifications in the 3T3-L1 pre-adipocyte cell line. The package document the data collection, pre-processing and processing of the data. In addition to the documentation, the package contains the scripts that was used to generated the data.

Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger.

Visualize clonal expansion via circle-packing. APackOfTheClones extends scRepertoire to produce a publication-ready visualization of clonal expansion at a single cell resolution, by representing expanded clones as differently sized circles. The method was originally implemented by Murray Christian and Ben Murrell in the following immunology study: Ma et al. (2021) <doi:10.1126/sciimmunol.abg6356>.

This package provides a set of functions and a class to connect, extract and upload information from the LSEG Datastream database. This package uses the DSWS API and server used by the Datastream DFO addin'. Details of this API are available at <https://www.lseg.com/en/data-analytics>. Please report issues at <https://github.com/CharlesCara/DatastreamDSWS2R/issues>.

Calculates landscape metrics for categorical landscape patterns in a tidy workflow. landscapemetrics reimplements the most common metrics from FRAGSTATS (<https://www.fragstats.org/>) and new ones from the current literature on landscape metrics. This package supports terra SpatRaster objects as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.

This package provides a selection of tools that make it easier to place elements onto a (base R) plot exactly where you want them. It allows users to identify points and distances on a plot in terms of inches, pixels, margin lines, data units, and proportions of the plotting space, all in a manner more simple than manipulating par().

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

Brings a set of tools to help and automatically realise the description of principal component analyses (from FactoMineR functions). Detection of existing outliers, identification of the informative components, graphical views and dimensions description are performed threw dedicated functions. The Investigate() function performs all these functions in one, and returns the result as a report document (Word, PDF or HTML).

Assorted files generated from droplet-based single-cell protocols, to be used for testing functions in DropletUtils. Primarily intended for storing files that directly come out of processing pipelines like 10X Genomics CellRanger software, prior to the formation of a SingleCellExperiment object. Unlike other packages, this is not designed to provide objects that are immediately ready for analysis.

Make acoustic cues to use with the R package ndl. The package implements functions used in the PLoS ONE paper "Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit." doi:10.1371/journal.pone.0174623

Set of tools to simplify application of atomic forecast verification metrics for (comparative) verification of ensemble forecasts to large data sets. The forecast metrics are imported from the SpecsVerification package, and additional forecast metrics are provided with this package. Alternatively, new user-defined forecast scores can be implemented using the example scores provided and applied using the functionality of this package.

Non linear dot plots are diagrams that allow dots of varying size to be constructed, so that columns with a large number of samples are reduced in height. Implementation of algorithm described in: Nils Rodrigues and Daniel Weiskopf, "Nonlinear Dot Plots", IEEE Transactions on Visualization and Computer Graphics, vol. 24, no. 1, pp. 616-625, 2018. <doi:10.1109/TVCG.2017.2744018>.

Aggregate Business Tendency Survey Data (and other qualitative surveys) to time series at various aggregation levels. Run aggregation of survey data in a speedy, re-traceable and a easily deployable way. Aggregation is substantially accelerated by use of data.table. This package intends to provide an interface that is less general and abstract than data.table but rather geared towards survey researchers.

This tiny crate checks that the running or installed rustc meets some version requirements. The version is queried by calling the Rust compiler with --version. The path to the compiler is determined first via the RUSTC environment variable. If it is not set, then rustc is used. If that fails, no determination is made, and calls return None.

This tiny crate checks that the running or installed rustc meets some version requirements. The version is queried by calling the Rust compiler with --version. The path to the compiler is determined first via the RUSTC environment variable. If it is not set, then rustc is used. If that fails, no determination is made, and calls return None.

The package uses PStricks and pst-solides3d to draw three dimensional ribbons on a cylinder, torus, sphere, cone or paraboloid. The width of the ribbon, the number of turns, the colour of the outer and the inner surface of the ribbon may be set. In the case of circular and conical helices, one may also choose the number of ribbons.

Fits Bayesian models (amongst others) to dissolution data sets that can be used for dissolution testing. The package was originally constructed to include only the Bayesian models outlined in Pourmohamad et al. (2022) <doi:10.1111/rssc.12535>. However, additional Bayesian and non-Bayesian models (based on bootstrapping and generalized pivotal quanties) have also been added. More models may be added over time.

These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.

Serves as a R wrapper for the University of California San Francisco's [Industry Documents Digital Library]<https://www.industrydocuments.ucsf.edu/> API. The API, and this wrapper, serve to pull metadata about of items within the digital library. For more information the API, see the [API's documentation]<https://www.industrydocuments.ucsf.edu/wp-content/uploads/2020/08/IndustryDocumentsDataAPI_v7.pdf>.

This package provides access to BAM files generated from RNA-seq data produced with different levels of gDNA contamination. It currently allows one to download a subset of the data published by Li et al., BMC Genomics, 23:554, 2022. This subset of data is formed by BAM files with about 100,000 alignments with three different levels of gDNA contamination.

This crate is an async version of std::process. A background thread named async-process is lazily created on first use, which waits for spawned child processes to exit and then calls the wait() syscall to clean up the ``zombie'' processes.

This is unlike the process API in the standard library, where dropping a running Child leaks its resources.

This crate is an async version of std::process. A background thread named async-process is lazily created on first use, which waits for spawned child processes to exit and then calls the wait() syscall to clean up the ``zombie'' processes.

This is unlike the process API in the standard library, where dropping a running Child leaks its resources.

Compute a non-overlapping layout of text boxes to label multiple overlain curves. For each curve, iteratively search for an adjacent x,y position for the text box that does not overlap with the other curves. If this process fails, then offsets are computed to add to the y values for each curve, that results in sufficient space to add all of the text labels.