Thu, 30 Jul 2020

Package subscreen updated to version 3.0.0 with previous version 2.0.1 dated 2019-01-07

Title: Systematic Screening of Study Data for Subgroup Effects
Description: Identifying outcome relevant subgroups has now become as simple as possible! The formerly lengthy and tedious search for the needle in a haystack will be replaced by a single, comprehensive and coherent presentation. The central result of a subgroup screening is a diagram in which each single dot stands for a subgroup. The diagram may show thousands of them. The position of the dot in the diagram is determined by the sample size of the subgroup and the statistical measure of the treatment effect in that subgroup. The sample size is shown on the horizontal axis while the treatment effect is displayed on the vertical axis. Furthermore, the diagram shows the line of no effect and the overall study results. For small subgroups, which are found on the left side of the plot, larger random deviations from the mean study effect are expected, while for larger subgroups only small deviations from the study mean can be expected to be chance findings. So for a study with no conspicuous subgroup effects, the dots in the figure are expected to form a kind of funnel. Any deviations from this funnel shape hint to conspicuous subgroups. This approach was presented in Muysers (2020) <doi:10.1007/s43441-019-00082-6> and referenced in Ballarini (2020) <doi:10.1002/pst.2012>. New to version 3 is the Automatic Screening of one- or MUlti-factorial Subgroups (ASMUS) for documentation of the structured review of subgroup findings.
Author: Bodo Kirsch, Steffen Jeske, Susanne Lippert, Thomas Schmelter, Christoph Muysers, Hermann Kulmann
Maintainer: Bodo Kirsch <bodo.kirsch@bayer.com>

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Package spsur updated to version 1.0.1.4 with previous version 1.0.1.3 dated 2020-04-07

Title: Spatial Seemingly Unrelated Regression Models
Description: A collection of functions to test and estimate Seemingly Unrelated Regression (usually called SUR) models, with spatial structure, by maximum likelihood and three-stage least squares. The package estimates the most common spatial specifications, that is, SUR with Spatial Lag of X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM), SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM), SUR with Spatial Durbin Error Model (called SUR-SDEM), SUR with Spatial Autoregressive terms and Spatial Autoregressive Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM). The methodology of these models can be found in next references Mur, J., Lopez, F., and Herrera, M. (2010) <doi:10.1080/17421772.2010.516443> Lopez, F.A., Mur, J., and Angulo, A. (2014) <doi:10.1007/s00168-014-0624-2>.
Author: Ana Angulo [aut], Fernando A Lopez [aut], Roman Minguez [aut, cre], Jesus Mur [aut]
Maintainer: Roman Minguez <roman.minguez@uclm.es>

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Package image.binarization updated to version 0.1.1 with previous version 0.1.0 dated 2020-07-27

Title: Binarize Images for Enhancing Optical Character Recognition
Description: Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful as a preprocessing step for optical character recognition or handwritten text recognition.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Brandon M. Petty [ctb, cph] (Files in src/Doxa)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>

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New package assertive.reflection with initial version 0.0-5
Package: assertive.reflection
Type: Package
Title: Assertions for Checking the State of R
Version: 0.0-5
Date: 2020-07-30
Author: Richard Cotton [aut, cre]
Maintainer: Richard Cotton <richierocks@gmail.com>
Authors@R: person("Richard", "Cotton", role = c("aut", "cre"), email = "richierocks@gmail.com")
Description: A set of predicates and assertions for checking the state and capabilities of R, the operating system it is running on, and the IDE being used. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
URL: https://bitbucket.org/richierocks/assertive.reflection
BugReports: https://bitbucket.org/richierocks/assertive.reflection/issues
Depends: R (>= 3.0.0)
Imports: assertive.base (>= 0.0-7), utils
Suggests: testthat
License: GPL (>= 3)
LazyLoad: yes
LazyData: yes
Acknowledgments: Development of this package was partially funded by the Proteomics Core at Weill Cornell Medical College in Qatar <http://qatar-weill.cornell.edu>. The Core is supported by 'Biomedical Research Program' funds, a program funded by Qatar Foundation.
Collate: 'imports.R' 'assert-is-32-64-bit.R' 'assert-is-current.R' 'assert-is-decimal-point.R' 'assert-is-ide.R' 'assert-is-on-os-path.R' 'assert-is-os.R' 'assert-is-r-mode.R' 'assert-is-r-version.R' 'assert-r-has-capability.R' 'is-32-64-bit.R' 'is-current.R' 'is-decimal-point.R' 'is-ide.R' 'is-on-os-path.R' 'is-os.R' 'is-r-mode.R' 'is-r-version.R' 'locale.R' 'r-has-capability.R'
RoxygenNote: 7.1.1
Repository: CRAN
NeedsCompilation: no
Packaged: 2020-07-30 21:23:39 UTC; richie
Date/Publication: 2020-07-31 01:00:14 UTC

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Package crul updated to version 1.0.0 with previous version 0.9.0 dated 2019-11-06

Title: HTTP Client
Description: A simple HTTP client, with tools for making HTTP requests, and mocking HTTP requests. The package is built on R6, and takes inspiration from Ruby's 'faraday' gem (<https://rubygems.org/gems/faraday>). The package name is a play on curl, the widely used command line tool for HTTP, and this package is built on top of the R package 'curl', an interface to 'libcurl' (<https://curl.haxx.se/libcurl>).
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package SMARTAR updated to version 1.1.0 with previous version 1.0.0 dated 2019-11-05

Title: Sequential Multiple Assignment Randomized Trial and Adaptive Randomization
Description: Primary data analysis for sequential multiple assignment randomization trial (SMART) and calibration tools for clinical trial planning purposes. \n The methods used for this package include: \n (1) Likelihood-based global test (hypothesis test, power calculation) by in Zhong X., Cheng, B., Qian M., Cheung Y.K. (2019) <doi: 10.1016/j.cct.2019.105830>. \n (2) IPWE-based global test (hypotehsis test, power calculation) by Ogbagaber S.B., Karp J., Wahed A.S. (2016) <doi:10.1002/sim.6747>. \n (3) G estimates (pairwise comparison, power calculation) by Lavori R., Dawson P.W. (2012) <doi: 10.1093/biostatistics/kxr016>. \n (4) IPW estimates (pairwise comparison, power calculation) by Murphy S.A. (2005) <doi: 10.1002/sim.2022>. \n (5) SAMRT with adaptive randomization by Cheung Y.K. (2015) <doi: 10.1111/biom.12258>.
Author: Tony Zhong <xiaobo.zhong@mountsinai.org> \n Xinru Wang <xw2676@cumc.columbia.edu> \n Bin Cheng <bc2159@cumc.columbia.edu> \n Ying Kuen Cheung <yc632@cumc.columbia.edu>
Maintainer: Tony Zhong <xiaobo.zhong@mountsinai.org>

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Package assertive.datetimes updated to version 0.0-3 with previous version 0.0-2 dated 2016-05-10

Title: Assertions to Check Properties of Dates and Times
Description: A set of predicates and assertions for checking the properties of dates and times. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
Author: Richard Cotton [aut, cre]
Maintainer: Richard Cotton <richierocks@gmail.com>

Diff between assertive.datetimes versions 0.0-2 dated 2016-05-10 and 0.0-3 dated 2020-07-30

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Package missMethods updated to version 0.2.0 with previous version 0.1.0 dated 2020-04-01

Title: Methods for Missing Data
Description: Supply functions for the creation and handling of missing data as well as tools to evaluate missing data methods. Nearly all possibilities of generating missing data discussed by Santos et. al (2019) <doi:10.1109/ACCESS.2019.2891360> and some additional are implemented. Functions are supplied to compare parameter estimates and imputed values to true values to evaluate missing data methods. Evaluations of these types are done, for example, by Cetin-Berber et al. (2019) <doi:10.1177/0013164418805532> and Kim et al. (2005) <doi:10.1093/bioinformatics/bth499>.
Author: Tobias Rockel [aut, cre]
Maintainer: Tobias Rockel <Rockel.To@gmail.com>

Diff between missMethods versions 0.1.0 dated 2020-04-01 and 0.2.0 dated 2020-07-30

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More information about missMethods at CRAN
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Package foghorn updated to version 1.2.3 with previous version 1.2.2 dated 2020-07-22

Title: Summarize CRAN Check Results in the Terminal
Description: The CRAN check results and where your package stands in the CRAN submission queue in your R terminal.
Author: Francois Michonneau [aut, cre], Ben Bolker [ctb]
Maintainer: Francois Michonneau <francois.michonneau@gmail.com>

Diff between foghorn versions 1.2.2 dated 2020-07-22 and 1.2.3 dated 2020-07-30

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Package R2SWF updated to version 0.9-4 with previous version 0.9-3 dated 2020-05-09

Title: Convert R Graphics to Flash Animations
Description: Using the 'Ming' library <http://www.libming.org/> to create Flash animations. Users can either use the 'SWF' device swf() to generate 'SWF' file directly through plotting functions like plot() and lines(), or convert images of other formats ('SVG', 'PNG', 'JPEG') into 'SWF'.
Author: Yixuan Qiu, Yihui Xie, Cameron Bracken and authors of included software. See file AUTHORS for details.
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

Diff between R2SWF versions 0.9-3 dated 2020-05-09 and 0.9-4 dated 2020-07-30

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Package iDINGO updated to version 1.0.4 with previous version 1.0.3 dated 2019-09-06

Title: Integrative Differential Network Analysis in Genomics
Description: Fits covariate dependent partial correlation matrices for integrative models to identify differential networks between two groups. The methods are described in Class et. al., (2018) <doi:10.1093/bioinformatics/btx750> and Ha et. al., (2015) <doi:10.1093/bioinformatics/btv406>.
Author: Caleb A. Class <cclass@butler.edu>, Min Jin Ha <mjha@mdanderson.org>
Maintainer: Caleb A. Class <cclass@butler.edu>

Diff between iDINGO versions 1.0.3 dated 2019-09-06 and 1.0.4 dated 2020-07-30

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Package prioritizr updated to version 5.0.2 with previous version 5.0.1 dated 2020-05-15

Title: Systematic Conservation Prioritization in R
Description: Conservation prioritization using integer programming techniques. To solve large-scale problems, users should install the 'gurobi' optimizer (available from <http://www.gurobi.com/>).
Author: Jeffrey O Hanson [aut] (<https://orcid.org/0000-0002-4716-6134>), Richard Schuster [aut, cre] (<https://orcid.org/0000-0003-3191-7869>), Nina Morrell [aut], Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Matthew E Watts [aut], Peter Arcese [aut] (<https://orcid.org/0000-0002-8097-482X>), Joseph Bennett [aut] (<https://orcid.org/0000-0002-3901-9513>), Hugh P Possingham [aut] (<https://orcid.org/0000-0001-7755-996X>)
Maintainer: Richard Schuster <richard.schuster@glel.carleton.ca>

Diff between prioritizr versions 5.0.1 dated 2020-05-15 and 5.0.2 dated 2020-07-30

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More information about prioritizr at CRAN
Permanent link

Package xplain updated to version 0.2.2 with previous version 0.2.1 dated 2018-05-02

Title: Providing Interactive Interpretations and Explanations of Statistical Results
Description: Allows to provide live interpretations and explanations of statistical functions in R. These interpretations and explanations are shown when the explained function is called by the user. They can interact with the values of the explained function's actual results to offer relevant, meaningful insights. The 'xplain' interpretations and explanations are based on an easy-to-use XML format that allows to include R code to interact with the returns of the explained function.
Author: Joachim Zuckarelli [aut, cre] (<https://orcid.org/0000-0002-9280-3016>)
Maintainer: Joachim Zuckarelli <joachim@zuckarelli.de>

Diff between xplain versions 0.2.1 dated 2018-05-02 and 0.2.2 dated 2020-07-30

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 MD5                    |   15 ++++++----
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More information about xplain at CRAN
Permanent link

Package KTensorGraphs updated to version 1.0 with previous version 0.2 dated 2019-10-01

Title: Co-Tucker3 Analysis of Two Sequences of Matrices
Description: Provides a function called COTUCKER3() (Co-Inertia Analysis + Tucker3 method) which performs a Co-Tucker3 analysis of two sequences of matrices, as well as other functions called PCA() (Principal Component Analysis) and BGA() (Between-Groups Analysis), which perform analysis of one matrix, COIA() (Co-Inertia Analysis), which performs analysis of two matrices, PTA() (Partial Triadic Analysis), STATIS(), STATISDUAL() and TUCKER3(), which perform analysis of a sequence of matrices, and BGCOIA() (Between-Groups Co-Inertia Analysis), STATICO() (STATIS method + Co-Inertia Analysis), COSTATIS() (Co-Inertia Analysis + STATIS method), which also perform analysis of two sequences of matrices.
Author: Miguel Rodriguez-Rosa <miguel_rosa90@usal.es> [aut, cre]
Maintainer: Miguel Rodriguez-Rosa <miguel_rosa90@usal.es>

Diff between KTensorGraphs versions 0.2 dated 2019-10-01 and 1.0 dated 2020-07-30

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More information about KTensorGraphs at CRAN
Permanent link

Package ff updated to version 4.0.2 with previous version 2.2-14.2 dated 2020-04-16

Title: Memory-Efficient Storage of Large Data on Disk and Fast Access Functions
Description: The ff package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section (pagesize) in main memory - the effective virtual memory consumption per ff object. ff supports R's standard atomic data types 'double', 'logical', 'raw' and 'integer' and non-standard atomic types boolean (1 bit), quad (2 bit unsigned), nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), single (4 byte float with NAs). For example 'quad' allows efficient storage of genomic data as an 'A','T','G','C' factor. The unsigned types support 'circular' arithmetic. There is also support for close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and custom close-to-atomic types. ff not only has native C-support for vectors, matrices and arrays with flexible dimorder (major column-order, major row-order and generalizations for arrays). There is also a ffdf class not unlike data.frames and import/export filters for csv files. ff objects store raw data in binary flat files in native encoding, and complement this with metadata stored in R as physical and virtual attributes. ff objects have well-defined hybrid copying semantics, which gives rise to certain performance improvements through virtualization. ff objects can be stored and reopened across R sessions. ff files can be shared by multiple ff R objects (using different data en/de-coding schemes) in the same process or from multiple R processes to exploit parallelism. A wide choice of finalizer options allows to work with 'permanent' files as well as creating/removing 'temporary' ff files completely transparent to the user. On certain OS/Filesystem combinations, creating the ff files works without notable delay thanks to using sparse file allocation. Several access optimization techniques such as Hybrid Index Preprocessing and Virtualization are implemented to achieve good performance even with large datasets, for example virtual matrix transpose without touching a single byte on disk. Further, to reduce disk I/O, 'logicals' and non-standard data types get stored native and compact on binary flat files i.e. logicals take up exactly 2 bits to represent TRUE, FALSE and NA. Beyond basic access functions, the ff package also provides compatibility functions that facilitate writing code for ff and ram objects and support for batch processing on ff objects (e.g. as.ram, as.ff, ffapply). ff interfaces closely with functionality from package 'bit': chunked looping, fast bit operations and coercions between different objects that can store subscript information ('bit', 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows to work interactively with selections of large datasets and quickly modify selection criteria. Further high-performance enhancements can be made available upon request.
Author: Daniel Adler [aut], Christian Gläser [aut], Oleg Nenadic [aut], Jens Oehlschlägel [aut, cre], Martijn Schuemie [aut], Walter Zucchini [aut]
Maintainer: Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com>

Diff between ff versions 2.2-14.2 dated 2020-04-16 and 4.0.2 dated 2020-07-30

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More information about ff at CRAN
Permanent link

New package dracor with initial version 0.2.1
Package: dracor
Type: Package
Title: Decode Draco Format 3D Mesh Data
Version: 0.2.1
Date: 2020-07-22
Authors@R: c( person("Gregory", "Jefferis", email="jefferis@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0587-9355")), person("Google Inc", role=c("aut", "cph"), comment="for the Draco library") )
Description: Decodes meshes and point cloud data encoded by the Draco mesh compression library from Google. Note that this is only designed for basic decoding and not intended as a full scale wrapping of the Draco library.
License: Apache License (>= 2.0)
Imports: Rcpp (>= 1.0.5)
LinkingTo: Rcpp
Enhances: rgl
Suggests: testthat, spelling
URL: https://github.com/jefferis/dracor, https://github.com/google/draco
BugReports: https://github.com/jefferis/dracor/issues
RoxygenNote: 7.1.0
Encoding: UTF-8
Language: en-GB
NeedsCompilation: yes
Packaged: 2020-07-25 16:16:01 UTC; jefferis
Author: Gregory Jefferis [aut, cre] (<https://orcid.org/0000-0002-0587-9355>), Google Inc [aut, cph] (for the Draco library)
Maintainer: Gregory Jefferis <jefferis@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-30 11:00:02 UTC

More information about dracor at CRAN
Permanent link

New package BWGS with initial version 0.1.0
Package: BWGS
Type: Package
Title: BreedWheat Genomic Selection Pipeline
Version: 0.1.0
Authors@R: c(person("Gilles", "Charmet", email = "gilles.charmet@inra.fr", role = "aut"), person("Louis Gautier", "Tran", role = "aut"), person("Bangyou", "Zheng", email = "bangyou.zheng@csiro.au", role = "cre"))
Description: Package for Breed Wheat Genomic Selection Pipeline. The R package 'BWGS' is developed by Gilles Charmet <gilles.charmet@inra.fr>. This repository is forked from original repository <https://forgemia.inra.fr/umr-gdec/bwgs> and modified as a R package.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: rrBLUP, BGLR, glmnet, randomForest, brnn, e1071
URL: https://github.com/byzheng/BWGS
BugReports: https://github.com/byzheng/BWGS/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-07-25 14:43:40 UTC; zhe00a
Author: Gilles Charmet [aut], Louis Gautier Tran [aut], Bangyou Zheng [cre]
Maintainer: Bangyou Zheng <bangyou.zheng@csiro.au>
Repository: CRAN
Date/Publication: 2020-07-30 11:02:13 UTC

More information about BWGS at CRAN
Permanent link

New package bsub with initial version 1.0.0
Package: bsub
Type: Package
Title: Submitter and Monitor of the 'LSF Cluster'
Version: 1.0.0
Date: 2020-07-25
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>
Depends: R (>= 3.0.0)
Imports: GlobalOptions (>= 0.1.1), GetoptLong (>= 0.1.8), digest, utils, stats, clisymbols, crayon, methods, grDevices, graphics
Suggests: knitr, ssh, DT (>= 0.13), shiny (>= 1.0.0), shinyjqui, igraph, graph, Rgraphviz
biocViews: Software, Infrastructure
Description: It submits R code/R scripts/shell commands to 'LSF cluster' (<https://en.wikipedia.org/wiki/Platform_LSF>, the 'bsub' system) without leaving R. There is also an interactive 'shiny' app for monitoring the job status.
URL: https://github.com/jokergoo/bsub
License: MIT + file LICENSE
NeedsCompilation: no
SystemRequirements: Platform LSF, bsub
Packaged: 2020-07-25 11:43:10 UTC; jokergoo
Repository: CRAN
Date/Publication: 2020-07-30 11:00:06 UTC

More information about bsub at CRAN
Permanent link

Package bit64 updated to version 4.0.2 with previous version 0.9-7.1 dated 2020-07-15

Title: A S3 Class for Vectors of 64bit Integers
Description: Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. These are useful for handling database keys and exact counting in +-2^63. WARNING: do not use them as replacement for 32bit integers, integer64 are not supported for subscripting by R-core and they have different semantics when combined with double, e.g. integer64 + double => integer64. Class integer64 can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as 'match' and 'order' support inter- active data exploration and manipulation and optionally leverage caching.
Author: Jens Oehlschlägel [aut, cre], Leonardo Silvestri [ctb]
Maintainer: Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com>

Diff between bit64 versions 0.9-7.1 dated 2020-07-15 and 4.0.2 dated 2020-07-30

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Permanent link

Package bit updated to version 4.0.3 with previous version 1.1-15.2 dated 2020-02-10

Title: Classes and Methods for Fast Memory-Efficient Boolean Selections
Description: Provided are classes for boolean and skewed boolean vectors, fast boolean methods, fast unique and non-unique integer sorting, fast set operations on sorted and unsorted sets of integers, and foundations for ff (range index, compression, chunked processing).
Author: Jens Oehlschlägel [aut, cre], Brian Ripley [ctb]
Maintainer: Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com>

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More information about bit at CRAN
Permanent link

New package pureseqtmr with initial version 1.2
Package: pureseqtmr
Title: Predict Transmembrane Protein Topology
Version: 1.2
Authors@R: c( person("Richèl J.C.", "Bilderbeek", email = "richel@richelbilderbeek.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1107-7049")))
Description: Proteins reside in either the cell plasma or in the cell membrane. A membrane protein goes through the membrane at least once. Given the amino acid sequence of a membrane protein, the tool 'PureseqTM' (<https://github.com/PureseqTM/pureseqTM_package>, as described in "Efficient And Accurate Prediction Of Transmembrane Topology From Amino acid sequence only.", Wang, Qing, et al (2019), <doi:10.1101/627307>), can predict the topology of a membrane protein. This package allows one to use 'PureseqTM' from R.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: ggplot2, plyr, rappdirs, stringr, tibble
Suggests: testthat, knitr, rmarkdown
URL: https://github.com/richelbilderbeek/pureseqtmr
BugReports: https://github.com/richelbilderbeek/pureseqtmr
VignetteBuilder: knitr
SystemRequirements: PureseqTM (https://github.com/PureseqTM/pureseqTM_package)
NeedsCompilation: no
Packaged: 2020-07-25 13:10:07 UTC; richel
Author: Richèl J.C. Bilderbeek [aut, cre] (<https://orcid.org/0000-0003-1107-7049>)
Maintainer: Richèl J.C. Bilderbeek <richel@richelbilderbeek.nl>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-07-30 10:50:02 UTC

More information about pureseqtmr at CRAN
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New package OpenRepGrid.ic with initial version 0.3.0
Package: OpenRepGrid.ic
License: MIT + file LICENSE
Title: Interpretive Clustering for Repertory Grids
Type: Package
LazyLoad: yes
Authors@R: c(person("Mark", "Heckmann", email = "heckmann.mark@gmail.com", role = c("aut", "cre", "cph")), person("Viv", "Burr", role = "aut"), person("Nigel", "King", role = "aut"))
Description: Shiny UI to identify cliques of related constructs in repertory grid data. See Burr, King, & Heckmann (2020) <doi:10.1080/14780887.2020.1794088> for a description of the interpretive clustering (IC) method.
Version: 0.3.0
Date: 2020-07-16
Imports: graphics, grDevices, utils, shiny, shinyjs, shinyBS, shinythemes, shinyWidgets, shinydashboard, shinydashboardPlus, shinycssloaders, shinyFeedback, rintrojs, formattable, openxlsx, DT, magrittr, tidyverse, dplyr, stringr, reshape2, scales, splines, igraph, testthat, tidyr
Suggests: knitr, rmarkdown, covr
Encoding: UTF-8
URL: https://github.com/markheckmann/OpenRepGrid.ic.git
BugReports: https://github.com/markheckmann/OpenRepGrid.ic/issues
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-07-24 19:36:11 UTC; heckm
Author: Mark Heckmann [aut, cre, cph], Viv Burr [aut], Nigel King [aut]
Maintainer: Mark Heckmann <heckmann.mark@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-30 10:30:02 UTC

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New package genieclust with initial version 0.9.3
Package: genieclust
Type: Package
Title: The Genie++ Hierarchical Clustering Algorithm with Noise Points Detection
Version: 0.9.3
Date: 2020-07-25
Authors@R: c( person("Marek", "Gagolewski", role = c("aut", "cre", "cph"), email = "marek@gagolewski.com", comment = c(ORCID = "0000-0003-0637-6028")), person("Maciej", "Bartoszuk", role = c("ctb")), person("Anna", "Cena", role = c("ctb")), person("Peter M.", "Larsen", role = c("ctb")) )
Description: A retake on the Genie algorithm - a robust hierarchical clustering method (Gagolewski, Bartoszuk, Cena, 2016 <DOI:10.1016/j.ins.2016.05.003>). Now faster and more memory efficient; determining the whole hierarchy for datasets of 10M points in low dimensional Euclidean spaces or 100K points in high-dimensional ones takes only 1-2 minutes. Allows clustering with respect to mutual reachability distances so that it can act as a noise point detector or a robustified version of 'HDBSCAN*' (that is able to detect a predefined number of clusters and hence it does not dependent on the somewhat fragile 'eps' parameter). The package also features an implementation of economic inequity indices (the Gini, Bonferroni index) and external cluster validity measures (partition similarity scores; e.g., the adjusted Rand, Fowlkes-Mallows, adjusted mutual information, pair sets index). See also the 'Python' version of 'genieclust' available on 'PyPI', which supports sparse data, more metrics, and even larger datasets.
BugReports: https://github.com/gagolews/genieclust/issues
URL: https://genieclust.gagolewski.com/
License: AGPL-3
Imports: Rcpp (>= 1.0.4), stats, utils
Suggests: datasets, emstreeR
LinkingTo: Rcpp
Encoding: UTF-8
SystemRequirements: OpenMP, C++11
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-25 07:37:17 UTC; gagolews
Author: Marek Gagolewski [aut, cre, cph] (<https://orcid.org/0000-0003-0637-6028>), Maciej Bartoszuk [ctb], Anna Cena [ctb], Peter M. Larsen [ctb]
Maintainer: Marek Gagolewski <marek@gagolewski.com>
Repository: CRAN
Date/Publication: 2020-07-30 10:40:03 UTC

More information about genieclust at CRAN
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New package dbnlearn with initial version 0.1.0
Package: dbnlearn
Type: Package
Title: Dynamic Bayesian Network Structure Learning, Parameter Learning and Forecasting
Version: 0.1.0
Depends: R (>= 3.4)
Authors@R: person("Robson", "Fernandes", email = "robson.fernandes@usp.br", role = c("aut", "cre", "cph"))
Description: It allows to learn the structure of univariate time series, learning parameters and forecasting. Implements a model of Dynamic Bayesian Networks with temporal windows, with collections of linear regressors for Gaussian nodes, based on the introductory texts of Korb and Nicholson (2010) <doi:10.1201/b10391> and Nagarajan, Scutari and Lèbre (2013) <doi:10.1007/978-1-4614-6446-4>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Repository: CRAN
Imports: bnlearn, bnviewer, ggplot2
NeedsCompilation: no
Packaged: 2020-07-24 15:01:02 UTC; robsonfernandes
Author: Robson Fernandes [aut, cre, cph]
Maintainer: Robson Fernandes <robson.fernandes@usp.br>
Date/Publication: 2020-07-30 10:10:02 UTC

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New package bayefdr with initial version 0.1.0
Package: bayefdr
Type: Package
Title: Bayesian Estimation and Optimisation of Expected False Discovery Rate
Version: 0.1.0
Date: 2020-07-24
Authors@R: c( person("Alan", "O'Callaghan", email = "alan.ocallaghan@outlook.com", role = c("aut", "cre") ), person("Catalina", "Vallejos", role = "aut") )
Description: Implements the Bayesian FDR control described by Newton et al. (2004), <doi:10.1093/biostatistics/5.2.155>. Allows optimisation and visualisation of expected error rates based on tail posterior probability tests. Based on code written by Catalina Vallejos for BASiCS, see Beyond comparisons of means: understanding changes in gene expression at the single-cell level Vallejos et al. (2016) <doi:10.1186/s13059-016-0930-3>.
Imports: ggplot2, reshape2, assertthat, utils, stats
License: GPL-3
BugReports: https://github.com/VallejosGroup/bayefdr/issues
RoxygenNote: 7.1.1
Encoding: UTF-8
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-07-24 11:29:18 UTC; alan
Author: Alan O'Callaghan [aut, cre], Catalina Vallejos [aut]
Maintainer: Alan O'Callaghan <alan.ocallaghan@outlook.com>
Repository: CRAN
Date/Publication: 2020-07-30 10:00:02 UTC

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New package wkutils with initial version 0.1.0
Package: wkutils
Title: Utilities for Well-Known Geometry Vectors
Version: 0.1.0
Authors@R: person(given = "Dewey", family = "Dunnington", role = c("aut", "cre"), email = "dewey@fishandwhistle.net", comment = c(ORCID = "0000-0002-9415-4582"))
Description: Provides extra utilities for well-known formats in the 'wk' package that are outside the scope of that package. Utilities to parse coordinates from data frames, plot well-known geometry vectors, extract meta information from well-known geometry vectors, and calculate bounding boxes are provided.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: wk (>= 0.3.1), Rcpp, tibble, vctrs
LinkingTo: wk, Rcpp
Suggests: testthat
URL: https://paleolimbot.github.io/wkutils, https://github.com/paleolimbot/wkutils
BugReports: https://github.com/paleolimbot/wkutils/issues
NeedsCompilation: yes
Packaged: 2020-07-23 23:33:30 UTC; dewey
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>
Repository: CRAN
Date/Publication: 2020-07-30 09:00:02 UTC

More information about wkutils at CRAN
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Package srvyr updated to version 0.4.0 with previous version 0.3.10 dated 2020-05-26

Title: 'dplyr'-Like Syntax for Summary Statistics of Survey Data
Description: Use piping, verbs like 'group_by' and 'summarize', and other 'dplyr' inspired syntactic style when calculating summary statistics on survey data using functions from the 'survey' package.
Author: Greg Freedman Ellis [aut, cre], Thomas Lumley [ctb], Tomasz Żółtak [ctb], Ben Schneider [aut, ctb]
Maintainer: Greg Freedman Ellis <greg.freedman@gmail.com>

Diff between srvyr versions 0.3.10 dated 2020-05-26 and 0.4.0 dated 2020-07-30

 DESCRIPTION                              |   19 +-
 MD5                                      |   48 ++---
 NAMESPACE                                |    2 
 NEWS.md                                  |    7 
 R/group-by.r                             |    6 
 R/manip.r                                |   33 ++-
 R/srvyr.r                                |    9 -
 R/summarise.r                            |  110 +++++++++++--
 R/survey_count_tally.R                   |   27 ---
 R/survey_statistics.r                    |   64 ++++++-
 R/survey_statistics_helpers.R            |    9 -
 build/vignette.rds                       |binary
 inst/doc/extending-srvyr.html            |   26 ++-
 inst/doc/srvyr-database.html             |  256 ++++++++++++++++---------------
 inst/doc/srvyr-vs-survey.R               |    4 
 inst/doc/srvyr-vs-survey.Rmd             |    4 
 inst/doc/srvyr-vs-survey.html            |  198 +++++++++++++----------
 man/summarise.Rd                         |    5 
 tests/testthat/test_as_survey_twophase.r |   12 +
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 tests/testthat/test_filter.R             |  116 ++++++++++++++
 tests/testthat/test_survey_count_tally.R |   91 +++++++++++
 tests/testthat/test_survey_mean_factor.r |  107 ++++++++++++
 tests/testthat/test_survey_statistics.r  |   75 +++++++--
 vignettes/srvyr-vs-survey.Rmd            |    4 
 25 files changed, 1049 insertions(+), 343 deletions(-)

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New package qtl2fst with initial version 0.22-7
Package: qtl2fst
Version: 0.22-7
Date: 2020-07-24
Title: Database Storage of Genotype Probabilities for QTL Mapping
Description: Uses the 'fst' package to store genotype probabilities on disk for the 'qtl2' package. These genotype probabilities are a central data object for mapping quantitative trait loci (QTL), but they can be quite large. The facilities in this package enable the genotype probabilities to be stored on disk, leading to reduced memory usage with only a modest increase in computation time.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), Brian S Yandell [aut] (<https://orcid.org/0000-0002-8774-9377>), Petr Simecek [aut] (<https://orcid.org/0000-0002-2922-7183>)
Maintainer: Karl W Broman <broman@wisc.edu>
Authors@R: c(person("Karl W", "Broman", role=c("aut", "cre"), email="broman@wisc.edu", comment=c(ORCID = "0000-0002-4914-6671")), person("Brian S", "Yandell", role="aut", email="byandell@wisc.edu", comment=c(ORCID = "0000-0002-8774-9377")), person("Petr", "Simecek", role="aut", comment=c(ORCID = "0000-0002-2922-7183")))
Depends: R (>= 3.1.0)
Imports: fst, qtl2 (>= 0.15-1)
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
URL: https://github.com/rqtl/qtl2fst
LazyData: true
ByteCompile: true
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-07-24 17:49:59 UTC; kbroman
Repository: CRAN
Date/Publication: 2020-07-30 09:30:07 UTC

More information about qtl2fst at CRAN
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New package fec16 with initial version 0.1.0
Package: fec16
Title: Data Package for the 2016 United States Federal Elections
Version: 0.1.0
Authors@R: c( person(given = "Marium", family = "Tapal", role = c("aut", "cre"), email = "mariumtapal@gmail.com", comment = c(ORCID = "0000-0001-5093-6462")), person(given = "Rana", family = "Gahwagy", role = "aut", email = "r.w.g1@hotmail.com"), person(given = "Irene", family = "Ryan", role = "aut", email = "ryan.irene3@gmail.com"), person(given = "Benjamin S.", family = "Baumer", role = "aut", email = "ben.baumer@gmail.com") )
Maintainer: Marium Tapal <mariumtapal@gmail.com>
Description: Easily analyze relational data from the United States 2016 federal election cycle as reported by the Federal Election Commission. This package contains data about candidates, committees, and a variety of different financial expenditures. Data is from <https://www.fec.gov/data/browse-data/?tab=bulk-data>.
License: CC0
Depends: R (>= 3.2.4), dplyr, readr
Suggests: testthat (>= 2.1.0), scales, knitr, rmarkdown, fs, lubridate, vroom, ggplot2, stringr, usethis, utf8
Encoding: UTF-8
LazyData: true
URL: http://github.com/baumer-lab/fec16
BugReports: https://github.com/baumer-lab/fec16/issues
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-07-23 19:36:12 UTC; mariumtapal
Author: Marium Tapal [aut, cre] (<https://orcid.org/0000-0001-5093-6462>), Rana Gahwagy [aut], Irene Ryan [aut], Benjamin S. Baumer [aut]
Repository: CRAN
Date/Publication: 2020-07-30 09:00:06 UTC

More information about fec16 at CRAN
Permanent link

New package faq with initial version 0.1.0
Package: faq
Title: Create FAQ Page
Version: 0.1.0
Authors@R: c(person(given = "Jiena", family = "McLellan", role = c("aut", "cre", "cph"), email = "jienagu90@gmail.com", comment = c(ORCID = "0000-0002-5578-088X")), person(given = "Michael", family = "Condouris", role = "ctb", comment = c(ORCID = "0000-0002-8862-4250")), person(given = "Alex", family = "Lais", role = "ctb"), person(given = "Jason", family = "Forrest", role = "ctb"), person(given = "Gunvansh", family = "Khanna", role = "ctb"))
Description: A fast tool to create an interactive and toggle styling Frequently Asked Questions page by using R data.
BugReports: https://github.com/jienagu/faq/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: MIT + file LICENSE
Imports: htmlwidgets, jsonlite
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-07-23 15:26:25 UTC; Jiena_Mclellan
Author: Jiena McLellan [aut, cre, cph] (<https://orcid.org/0000-0002-5578-088X>), Michael Condouris [ctb] (<https://orcid.org/0000-0002-8862-4250>), Alex Lais [ctb], Jason Forrest [ctb], Gunvansh Khanna [ctb]
Maintainer: Jiena McLellan <jienagu90@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-30 09:00:09 UTC

More information about faq at CRAN
Permanent link

Package ckanr updated to version 0.5.0 with previous version 0.4.0 dated 2019-10-11

Title: Client for the Comprehensive Knowledge Archive Network ('CKAN') API
Description: Client for 'CKAN' API (<https://ckan.org/>). Includes interface to 'CKAN' 'APIs' for search, list, show for packages, organizations, and resources. In addition, provides an interface to the 'datastore' API.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Imanuel Costigan [aut], Wush Wu [aut] (<https://orcid.org/0000-0001-5180-0567>), Florian Mayer [aut] (<https://orcid.org/0000-0003-4269-4242>), Sharla Gelfand [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between ckanr versions 0.4.0 dated 2019-10-11 and 0.5.0 dated 2020-07-30

 ckanr-0.4.0/ckanr/inst/doc/ckanr.R                            |only
 ckanr-0.5.0/ckanr/DESCRIPTION                                 |   13 
 ckanr-0.5.0/ckanr/LICENSE                                     |    2 
 ckanr-0.5.0/ckanr/MD5                                         |  314 +++++-----
 ckanr-0.5.0/ckanr/NAMESPACE                                   |   13 
 ckanr-0.5.0/ckanr/NEWS.md                                     |   23 
 ckanr-0.5.0/ckanr/R/as-ckan_group.R                           |    8 
 ckanr-0.5.0/ckanr/R/as-ckan_organization.R                    |   22 
 ckanr-0.5.0/ckanr/R/as-ckan_package.R                         |   53 +
 ckanr-0.5.0/ckanr/R/as-ckan_related.R                         |   14 
 ckanr-0.5.0/ckanr/R/as-ckan_resource.R                        |   11 
 ckanr-0.5.0/ckanr/R/as-ckan_tag.R                             |   10 
 ckanr-0.5.0/ckanr/R/as-ckan_user.R                            |   10 
 ckanr-0.5.0/ckanr/R/changes.R                                 |    2 
 ckanr-0.5.0/ckanr/R/ckan_classes.R                            |   21 
 ckanr-0.5.0/ckanr/R/ckan_fetch.R                              |   58 +
 ckanr-0.5.0/ckanr/R/ckan_info.R                               |   16 
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 ckanr-0.5.0/ckanr/R/dashboard_activity_list.R                 |    3 
 ckanr-0.5.0/ckanr/R/dashboard_count.R                         |    2 
 ckanr-0.5.0/ckanr/R/dplyr.R                                   |    2 
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 ckanr-0.5.0/ckanr/R/ds_create_dataset.R                       |    7 
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 ckanr-0.5.0/ckanr/R/group_delete.R                            |    9 
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 ckanr-0.5.0/ckanr/R/package_activity_list.R                   |    5 
 ckanr-0.5.0/ckanr/R/package_create.R                          |   98 +--
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 ckanr-0.5.0/ckanr/R/tag_create.R                              |    2 
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 ckanr-0.5.0/ckanr/man/ds_search.Rd                            |   66 +-
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 ckanr-0.5.0/ckanr/man/group_delete.Rd                         |    6 
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 ckanr-0.5.0/ckanr/man/tag_create.Rd                           |   12 
 ckanr-0.5.0/ckanr/man/tag_list.Rd                             |   15 
 ckanr-0.5.0/ckanr/man/tag_search.Rd                           |   23 
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 ckanr-0.5.0/ckanr/man/user_list.Rd                            |   12 
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 ckanr-0.5.0/ckanr/tests/test-all.R                            |only
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 ckanr-0.5.0/ckanr/tests/testthat/test-package_activity_list.R |   10 
 ckanr-0.5.0/ckanr/tests/testthat/test-package_list.R          |    6 
 ckanr-0.5.0/ckanr/tests/testthat/test-resource_search.R       |    8 
 ckanr-0.5.0/ckanr/tests/testthat/test-resource_update.R       |   31 
 ckanr-0.5.0/ckanr/tests/testthat/test-tag_list.R              |    6 
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 160 files changed, 2730 insertions(+), 1659 deletions(-)

More information about ckanr at CRAN
Permanent link

New package BBcor with initial version 1.0.0
Package: BBcor
Type: Package
Title: Bayesian Bootstrapping Correlations
Version: 1.0.0
Authors@R: person("Donald", "Williams", email = "drwwilliams@ucdavis.edu", role = c("aut", "cre"))
Description: Efficiently draw samples from the posterior distribution of various correlation coefficients with the Bayesian bootstrap described in Rubin (1981) <doi:10.1214/aos/1176345338>. There are five correlation coefficients, including Pearson, Kendall, Spearman, Blomqvist, and polychoric.
Depends: R (>= 4.0.0)
License: GPL-2
Imports: parallel, pbapply (>= 1.4-2), psych (>= 1.9.12.31), wdm (>= 0.2.1), stats, utils, methods
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-07-23 16:44:36 UTC; Donny
Author: Donald Williams [aut, cre]
Maintainer: Donald Williams <drwwilliams@ucdavis.edu>
Repository: CRAN
Date/Publication: 2020-07-30 09:02:17 UTC

More information about BBcor at CRAN
Permanent link

New package AEenrich with initial version 1.0.0
Package: AEenrich
Version: 1.0.0
Title: Adverse Event Enrichment Tests
Type: Package
Description: We extend existing gene enrichment tests to perform adverse event enrichment analysis. Unlike the continuous gene expression data, adverse event data are counts. Therefore, adverse event data has many zeros and ties. We propose two enrichment tests. One is a modified Fisher's exact test based on pre-selected significant adverse events, while the other is based on a modified Kolmogorov-Smirnov statistic. "Adverse event enrichment tests using VAERS" Shuoran Li, Lili Zhao (2020) <arXiv:2007.02266>.
Authors@R: c( person(given = "Shuoran", family = "Li", role = c("aut"), email = "shuoranl@umich.edu"), person(given = "Lili", family = "Zhao", role = c("aut"), email = "zhaolili@med.umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("aut", "cre"), email = "mkleinsa@umich.edu"))
License: GPL-2
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.5.0)
Imports: dplyr, magrittr, qvalue
biocViews:
URL: https://github.com/umich-biostatistics/AEenrich
BugReports: https://github.com/umich-biostatistics/AEenrich/issues
RoxygenNote: 7.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-07-23 21:27:31 UTC; mkleinsa
Author: Shuoran Li [aut], Lili Zhao [aut], Michael Kleinsasser [aut, cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
Repository: CRAN
Date/Publication: 2020-07-30 09:02:21 UTC

More information about AEenrich at CRAN
Permanent link

Package idiogramFISH updated to version 1.16.1 with previous version 1.15.3 dated 2020-07-02

Title: Idiograms with Marks and Karyotype Indices
Description: Plot idiograms of karyotypes, plasmids, circular chr. having a set of data.frames for chromosome data and optionally mark data. Two styles of chromosomes can be used: without or with visible chromatids (when not circular). Supports micrometers, cM and Mb or any unit. Two styles of centromeres are available: triangular and rounded; and six styles of marks: square (squareLeft), dots, cM (cMLeft), cenStyle, upArrow, downArrow; its legend (label) can be drawn inline or to the right of karyotypes. Idiograms can also be plotted in concentric circles. It is possible to calculate chromosome indices by Levan et al. (1964) <doi:10.1111/j.1601-5223.1964.tb01953.x>, karyotype indices of Watanabe et al. (1999) <doi:10.1007/PL00013869> and Romero-Zarco (1986) <doi:10.2307/1221906> and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).
Author: Fernando Roa [aut, cre], Mariana PC Telles [ctb]
Maintainer: Fernando Roa <froao@unal.edu.co>

Diff between idiogramFISH versions 1.15.3 dated 2020-07-02 and 1.16.1 dated 2020-07-30

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Package pedmut updated to version 0.2.0 with previous version 0.1.0 dated 2019-10-01

Title: Mutation Models for Pedigree Likelihood Computations
Description: A collection of functions for modeling mutations in pedigrees with marker data, as used e.g. in likelihood computations with microsatellite data. Implemented models include proportional and stepwise models, as well as random models for experimental work, and custom models allowing the user to apply any valid mutation matrix. Allele lumping is done following the lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922.
Author: Magnus Dehli Vigeland [aut, cre] (<https://orcid.org/0000-0002-9134-4962>)
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

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Package assertive (with last version 0.3-5.1) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2020-07-17 0.3-5.1
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2015-03-24 0.2-4
2015-02-04 0.2-1
2013-10-13 0.1-8
2013-01-05 0.1-7
2012-05-29 0.1-4

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Package assertive.reflection (with last version 0.0-4.1) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2020-07-17 0.0-4.1
2016-12-30 0.0-4
2016-03-29 0.0-3
2016-03-06 0.0-2
2015-10-06 0.0-1

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Package miceadds updated to version 3.10-28 with previous version 3.9-14 dated 2020-05-09

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are included. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>), substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>), and features for the generation of synthetic datasets (Reiter, 2005, <doi:10.1111/j.1467-985X.2004.00343.x>; Nowok, Raab, & Dibben, 2016, <doi:10.18637/jss.v074.i11>).
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>), Simon Grund [aut] (<https://orcid.org/0000-0002-1290-8986>), Thorsten Henke [ctb]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package gRain updated to version 1.3-6 with previous version 1.3-5 dated 2020-06-14

Title: Graphical Independence Networks
Description: Probability propagation in graphical independence networks, also known as Bayesian networks or probabilistic expert systems. Documentation of the package is provided in vignettes included in the package and in the paper by Højsgaard (2012, <doi:10.18637/jss.v046.i10>). See 'citation("gRain")' for details.
Author: Søren Højsgaard <sorenh@math.aau.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

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Package CCAMLRGIS updated to version 3.0.5 with previous version 3.0.4 dated 2020-06-07

Title: Antarctic Spatial Data Manipulation
Description: Loads and creates spatial data, including layers and tools that are relevant to the activities of the Commission for the Conservation of Antarctic Marine Living Resources. Provides two categories of functions: load functions and create functions. Load functions are used to import existing spatial layers from the online CCAMLR GIS such as the ASD boundaries. Create functions are used to create layers from user data such as polygons and grids.
Author: Stephane Thanassekos [aut, cre], Keith Reid [aut], Lucy Robinson [aut], Michael D. Sumner [ctb], Roger Bivand [ctb]
Maintainer: Stephane Thanassekos <stephane.thanassekos@ccamlr.org>

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Package wdpar updated to version 1.0.3 with previous version 1.0.2 dated 2020-04-15

Title: Interface to the World Database on Protected Areas
Description: Fetch and clean data from the World Database on Protected Areas (WDPA). Data is obtained from Protected Planet <http://protectedplanet.net>.
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

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Package RBF updated to version 2.0.1 with previous version 1.0.0 dated 2019-06-14

Title: Robust Backfitting
Description: A robust backfitting algorithm for additive models based on (robust) local polynomial kernel smoothers. It includes both bounded and re-descending (kernel) M-estimators, and it computes predictions for points outside the training set if desired. See Boente, Martinez and Salibian-Barrera (2017) <doi:10.1080/10485252.2017.1369077> for details.
Author: Matias Salibian-Barrera [aut, cre], Alejandra Martinez [aut]
Maintainer: Matias Salibian-Barrera <matias@stat.ubc.ca>

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Package mapr updated to version 0.5.0 with previous version 0.4.0 dated 2018-03-21

Title: Visualize Species Occurrence Data
Description: Utilities for visualizing species occurrence data. Includes functions to visualize occurrence data from 'spocc', 'rgbif', and other packages. Mapping options included for base R plots, 'ggplot2', 'ggmap', 'leaflet' and 'GitHub' 'gists'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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