Extracted data from 369 TCGA Head and Neck Cancer DNA methylation samples. The extracted data serve as an example dataset for the package shinyMethyl. Original samples are from 450k methylation arrays, and were obtained from The Cancer Genome Atlas (TCGA). 310 samples are from tumor, 50 are matched normals and 9 are technical replicates of a control cell line.

This package adds a single command dired-rsync which allows the user to copy marked files in a Dired buffer via rsync. This is useful, especially for large files, because the copy happens in the background and doesn’t lock up Emacs. It is also more efficient than using Tramp's own encoding methods for moving data between systems.

This package adds a single command dired-rsync which allows the user to copy marked files in a Dired buffer via rsync. This is useful, especially for large files, because the copy happens in the background and doesn’t lock up Emacs. It is also more efficient than using Tramp's own encoding methods for moving data between systems.

This package implements handy macros @recipe and @series which will define a custom transformation and attach attributes for user types. Its design is an attempt to simplify and generalize the summary and display of types and data from external packages. With this package it is possible to describe visualization routines that can be used as components in more complex visualizations.

systemPipeRdata complements the systemPipeR workflow management system (WMS) by offering a collection of pre-designed data analysis workflow templates. These templates are easily accessible and can be readily loaded onto a user's system with a single command. Once loaded, the WMS can immediately utilize these templates for efficient end-to-end analysis, serving a wide range of data analysis needs.

Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. This type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondence between different data sources.

This package provides a tool to search and download a collection of publicly available single cell ATAC-seq datasets and their metadata. scATAC-Explorer aims to act as a single point of entry for users looking to study single cell ATAC-seq data. Users can quickly search available datasets using the metadata table and download datasets of interest for immediate analysis within R.

This package provides genome wide annotation for E coli strain K12, primarily based on mapping using Entrez Gene identifiers. Entrez Gene is National Center for Biotechnology Information (NCBI)’s database for gene-specific information. Entrez Gene maintains records from genomes which have been completely sequenced, which have an active research community to submit gene-specific information, or which are scheduled for intense sequence analysis.

This NGINX module provides streaming with the RTMP, DASH, and HLS protocols. It allows NGINX to accept incoming RTMP streams for recording or redistribution. It also supports on-demand streaming from a file on disk and pulling from an upstream RTMP stream. Remote control of the module is possible over HTTP.

Radio Beam is a simple toolkit for reading beam information from FITS headers and manipulating beams. Some example applications include:

• Convolution and deconvolution

• Unit conversion (Jy to/from K)

• Handle sets of beams for spectral cubes with varying resolution between channels

• Find the smallest common beam from a set of beams

• Add the beam shape to a matplotlib plot

JLine is a Java library for handling console input. It is similar in functionality to BSD editline and GNU readline but with additional features that bring it in par with ZSH line editor. People familiar with the readline/editline capabilities for modern shells (such as bash and tcsh) will find most of the command editing features of JLine to be familiar.

This package includes the line reader.

MetaboCoreUtils defines metabolomics-related core functionality provided as low-level functions to allow a data structure-independent usage across various R packages. This includes functions to calculate between ion (adduct) and compound mass-to-charge ratios and masses or functions to work with chemical formulas. The package provides also a set of adduct definitions and information on some commercially available internal standard mixes commonly used in MS experiments.

This package lets you compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.

Rofi-pass provides a way to manipulate information stored using password-store through rofi interface:

1. open URLs of entries with hotkey;

2. type any field from entry;

3. auto-typing of user and/or password fields;

4. auto-typing username based on path;

5. auto-typing of more than one field, using the autotype entry;

6. bookmarks mode (open stored URLs in browser, default: Alt+x).

This package provides Wayland support by default.

The RIT font collection provides versions of ten font families in Malayalam (the language spoken in the southern Indian state of Kerala) script in TrueType and WOFF2 formats. The fonts are: RIT Rachana, RIT Panmana, RIT MeeraNew, RIT TN Joy, RIT Karuna, RIT Keralayeeam, RIT Sundar, RIT Uroob, RIT Ezhuthu, and RIT Kutty.

A LaTeX package that will help users to make use of these Unicode-compliant fonts in LaTeX documents with XeTeX or LuaTeX is also provided.

This package provides a Shiny app that can disconnect for a variety of reasons: an unrecoverable error occurred in the app, the server went down, the user lost internet connection, or any other reason that might cause the Shiny app to lose connection to its server. With shinydisconnect, you can call disonnectMessage anywhere in a Shiny app's UI to add a nice message when this happens. It works locally (running Shiny apps within RStudio) and on Shiny servers.

Online data collection tools like Google Forms often export multiple-response questions with data concatenated in cells. The concat.split (cSplit) family of functions provided by this package splits such data into separate cells. This package also includes functions to stack groups of columns and to reshape wide data, even when the data are "unbalanced"---something which reshape (from base R) does not handle, and which melt and dcast from reshape2 do not easily handle.

This package contains a collection of 9 datasets, andrews and bakulski cord blood, blood gse35069, blood gse35069 chen, blood gse35069 complete, combined cord blood, cord bloo d gse68456, gervin and lyle cord blood, guintivano dlpfc and saliva gse48472. The data are used to estimate cell counts using Extrinsic epigenetic age acceleration (EEAA) method. It also contains a collection of 12 datasets to use with MethylClock package to estimate chronological and gestational DNA methylation with estimators to use with different methylation clocks.

This package provides the data that were used in the http://quinlanlab.org/tutorials/bedtools/bedtools.html. It includes a subset of the DnaseI hypersensitivity data from "Maurano et al. Systematic Localization of Common Disease-Associated Variation in Regulatory DNA. Science. 2012. Vol. 337 no. 6099 pp. 1190-1195." The rest of the tracks were originally downloaded from the UCSC table browser. See the HelloRanges vignette for a port of the bedtools tutorial to R.

Volcano plots represent a useful way to visualise the results of differential expression analyses. This package provides a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many point labels in the plot window as possible, thus avoiding clogging up the plot with labels that could not otherwise have been read. Other functionality allows the user to identify up to 4 different types of attributes in the same plot space via color, shape, size, and shade parameter configurations.

CukeModeler facilitates modeling a test suite that is written in Gherkin (e.g. Cucumber, SpecFlow, Lettuce, etc.). It does this by providing an abstraction layer on top of the Abstract Syntax Tree (AST) that the cucumber-gherkin generates when parsing features, as well as providing models for feature files and directories in order to be able to have a fully traversable model tree of a test suite's structure. These models can then be analyzed or manipulated more easily than the underlying AST layer.

This library is a collection of pseudo random number generators.

While Common Lisp does provide a RANDOM function, it does not allow the user to pass an explicit SEED, nor to portably exchange the random state between implementations. This can be a headache in cases like games, where a controlled seeding process can be very useful.

For both curiosity and convenience, this library offers multiple algorithms to generate random numbers, as well as a bunch of generally useful methods to produce desired ranges.

This package provides a set of tools and methods for making and manipulating transcript centric annotations. With these tools the user can easily download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database (more sources will be supported in the future). This information is then stored in a local database that keeps track of the relationship between transcripts, exons, cds and genes. Flexible methods are provided for extracting the desired features in a convenient format.

This package aggregateBioVar contains tools to summarize single cell gene expression profiles at the level of subject for single cell RNA-seq data collected from more than one subject (e.g. biological sample or technical replicates). A SingleCellExperiment object is taken as input and converted to a list of SummarizedExperiment objects, where each list element corresponds to an assigned cell type. The SummarizedExperiment objects contain aggregate gene-by-subject count matrices and inter-subject column metadata for individual subjects that can be processed using downstream bulk RNA-seq tools.