This package performs a sensitivity analysis using weighted rank tests in observational studies with I blocks of size J; see Rosenbaum (2024) <doi:10.1080/01621459.2023.2221402>. The package can perform adaptive inference in block designs; see Rosenbaum (2012) <doi:10.1093/biomet/ass032>. The main functions are wgtRank()
, wgtRankCI()
and wgtRanktt()
.
AnVILBilling
helps monitor AnVIL-related
costs in R, using queries to a BigQuery
table to which costs are exported daily. Functions are defined to help categorize tasks and associated expenditures, and to visualize and explore expense profiles over time. This package will be expanded to help users estimate costs for specific task sets.
This package provides a user-friendly interface to map on-targets and off-targets of CRISPR gRNA
spacer sequences using bowtie. The alignment is fast, and can be performed using either commonly-used or custom CRISPR nucleases. The alignment can work with any reference or custom genomes. Both DNA- and RNA-targeting nucleases are supported.
This package aims to quantify and remove putative double strand DNA from a strand-specific RNA sample. There are also options and methods to plot the positive/negative proportions of all sliding windows, which allow users to have an idea of how much the sample was contaminated and the appropriate threshold to be used for filtering.
This package implements a method to rapidly assess cell type identity using both functional and random gene sets and it allows users to quantify cell type replicability across datasets using neighbor voting. MetaNeighbor
works on the basis that cells of the same type should have more similar gene expression profiles than cells of different types.
This package is designed to improve and simplify the analysis of scRNA-seq data. It uses the Seurat object for this purpose. It provides an array of enhanced visualization tools, an integrated functional and pathway analysis pipeline, seamless integration with popular Python tools, and a suite of utility functions to aid in data manipulation and presentation.
This package provides a client package that makes the KorAP
web service API accessible from R. The corpus analysis platform KorAP
has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the German Reference Corpus DeReKo
or the Corpus of the Contemporary Romanian Language CoRoLa
', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The RKorAPClient
package provides access to KorAP
and the corpora behind it for user-created R code, as a programmatic alternative to the KorAP
web user-interface. You can learn more about KorAP
and use it directly on DeReKo
at <https://korap.ids-mannheim.de/>.
Implementations in cpp of the BayesProject
algorithm (see G. Hahn, P. Fearnhead, I.A. Eckley (2020) <doi:10.1007/s11222-020-09966-2>) which implements a fast approach to compute a projection direction for multivariate changepoint detection, as well as the sum-cusum and max-cusum methods, and a wild binary segmentation wrapper for all algorithms.
An interactive mapping tool for geographically weighted correlation and partial correlation. Geographically weighted partial correlation coefficients are calculated following (Percival and Tsutsumida, 2017)<doi:10.1553/giscience2017_01_s36> and are described in greater detail in (Tsutsumida et al., 2019)<doi:10.5194/ica-abs-1-372-2019> and (Percival et al., 2021)<arXiv:2101.03491>
.
This package provides functions to assess the strength and statistical significance of the relationship between species occurrence/abundance and groups of sites [De Caceres & Legendre (2009) <doi:10.1890/08-1823.1>]. Also includes functions to measure species niche breadth using resource categories [De Caceres et al. (2011) <doi:10.1111/J.1600-0706.2011.19679.x>].
Get image statistics based on processing fluency theory. The functions provide scores for several basic aesthetic principles that facilitate fluent cognitive processing of images: contrast, complexity / simplicity, self-similarity, symmetry, and typicality. See Mayer & Landwehr (2018) <doi:10.1037/aca0000187> and Mayer & Landwehr (2018) <doi:10.31219/osf.io/gtbhw> for the theoretical background of the methods.
Two functions for running and then post-estimating an Interrupted Time Series Analysis model. This is a solution for running time series analyses on temporally short data. See English (2019) The its.analysis R package - Modelling short time series data <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3398189> for an overview of the method.
Graphical methods testing multivariate normality assumption. Methods including assessing score function, and moment generating functions,independent transformations and linear transformations. For more details see Tran (2024),"Contributions to Multivariate Data Science: Assessment and Identification of Multivariate Distributions and Supervised Learning for Groups of Objects." , PhD
thesis, <https://our.oakland.edu/items/c8942577-2562-4d2f-8677-cb8ec0bf6234>.
Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) <doi:10.1080/07350015.2020.1816176>, BiaÅ ek (2019) <doi:10.2478/jos-2019-0014> or BiaÅ ek (2020) <doi:10.2478/jos-2020-0037>.
Manage optional data for your package. The data can be hosted anywhere, and you have to give a Uniform Resource Locator (URL) for each file. File integrity checks are supported. This is useful for package authors who need to ship more than the 5 Megabyte of data currently allowed by the the Comprehensive R Archive Network (CRAN).
Provision of the S4 SpatialGraph
class built on top of objects provided by igraph and sp packages, and associated utilities. See the documentation of the SpatialGraph-class
within this package for further description. An example of how from a few points one can arrive to a SpatialGraph
is provided in the function sl2sg()
.
Uses read counts for biallelic single nucleotide polymorphisms (SNPs) to compare the likelihoods for the observed read counts given that a sample is either diploid or triploid. It allows parameters to be specified to account for sequencing error rates and allelic bias. For details of the algorithm, please see Delomas (2019) <doi:10.1111/1755-0998.13073>.
This package contains variable, diversity, and joining sequences and accompanying functions that enable both the extraction of and comparison between immune V-D-J genomic segments from a variety of species. Sources include IMGT from MP Lefranc (2009) <doi:10.1093/nar/gkn838> and Vgenerepertoire from publication DN Olivieri (2014) <doi:10.1007/s00251-014-0784-3>.
This packages provides a flexible, fast and accurate method for targeted pre-processing of GC-MS data. The user provides a (often very large) set of GC chromatograms and a metabolite library of targets. The package will automatically search those targets in the chromatograms resulting in a data matrix that can be used for further data analysis.
mkmf-lite
is a light version of Ruby's mkmf.rb
designed for use as a library. It does not create packages, builds, or log files of any kind. Instead, it provides mixin methods that you can use in FFI or tests to check for the presence of header files, constants, and so on.
Record your test suite's HTTP interactions and replay them during future test runs for fast, deterministic, accurate tests. This is an older version of VCR that is free software under the Expat license. The project later switched to the Hippocratic license, which is non-free. Do not use it in new free software projects.
Code for a variety of nonlinear conditional independence tests: Kernel conditional independence test (Zhang et al., UAI 2011, <arXiv:1202.3775>
), Residual Prediction test (based on Shah and Buehlmann, <arXiv:1511.03334>
), Invariant environment prediction, Invariant target prediction, Invariant residual distribution test, Invariant conditional quantile prediction (all from Heinze-Deml et al., <arXiv:1706.08576>
).
This package provides data on countries and their main city or agglomeration and the different distance measures and dummy variables indicating whether two countries are contiguous, share a common language or a colonial relationship. The reference article for these datasets is Mayer and Zignago (2011) <http://www.cepii.fr/CEPII/en/publications/wp/abstract.asp?NoDoc=3877>
.
Given two samples of size n_1 and n_2 from a data set where each sample consists of K functional observations (channels), each recorded on T grid points, the function energy method implements a hypothesis test of equality of channel-wise mean at each channel using the bootstrapped distribution of maximum energy to control family wise error.