Last data update: 2014.03.03

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DataLoader : Import Multiple File Types

Package: DataLoader
Title: Import Multiple File Types
Version: 1.3
Type: Package
Date: 2015-10-09
Author: Srivenkatesh Gandhi<srivenkateshg@sase.ssn.edu.in>,
Kreshnaa Raam S Bethusamy <kreshnaaraamsb@sase.ssn.edu.in>
Maintainer: Srivenkatesh Gandhi <srivenkateshg@sase.ssn.edu.in>
Description: Functions to import multiple files of multiple data file types ('.xlsx', '.xls', '.csv', '.txt')
from a given directory into R data frames.
Depends: readxl, plyr, tools, xlsx, rChoiceDialogs
Suggests: testthat
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: no
Packaged: 2015-10-29 17:12:03 UTC; kresh
Repository: CRAN
Date/Publication: 2015-11-01 17:53:09

● Data Source: CranContrib
● 0 images, 8 functions, 0 datasets
● Reverse Depends: 0

ELT : Experience Life Tables

Package: ELT
Type: Package
Title: Experience Life Tables
Version: 1.6
Date: 2016-04-10
Author: Julien Tomas, Frederic Planchet, Wassim Youssef
Maintainer: Wassim Youssef <Wassim.G.Youssef@gmail.com>
Description: Build experience life tables.
License: GPL (>= 2)
Depends: R (>= 2.10.0), locfit, lattice, latticeExtra, xlsx
Encoding: latin1
Packaged: 2016-04-10 10:32:05 UTC; root
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-04-11 09:06:26

● Data Source: CranContrib
● 0 images, 22 functions, 3 datasets
● Reverse Depends: 0

ImportExport : Import and Export Data

Package: ImportExport
Type: Package
Title: Import and Export Data
Version: 1.1
Date: 2015-09-18
Author: Roger Pros, Isaac Subirana, Joan Vila.
Maintainer: Isaac Subirana <isubirana@imim.es>
Description: Import and export data from the most common statistical formats by using
R functions that guarantee the least loss of the data information, giving special
attention to the date variables and the labelled ones.
Depends: xlsx, gdata, Hmisc, chron, RODBC
Imports: haven, utils
Suggests: shiny, shinyBS, shinythemes, compareGroups, foreign
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2015-09-19 12:50:06 UTC; instalar
Repository: CRAN
Date/Publication: 2015-09-19 19:50:28

● Data Source: CranContrib
● 0 images, 10 functions, 0 datasets
● Reverse Depends: 0

cosmosR : cosmosR

Package: cosmosR
Type: Package
Title: cosmosR
Version: 1.0
Date: 2013-09-18
Author: Maxime Wack
Maintainer: Maxime Wack <maximewack@free.fr>
Depends: xlsx
Description: This package aims at the easy production of descriptive and
bivariate statistics tables in HTML. It can load files in csv, xls/xlsx
formats, and read labels and formats from SAS or plain text files. It is
intended to be usable by absolute R beginners. Ce paquet permet la
production facile de tableaux HTML descriptifs et comparatifs, meme pour
les debutants sous R.
License: GPL-3
Packaged: 2014-01-03 13:04:15 UTC; u992093
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-01-03 15:05:40

● Data Source: CranContrib
● 0 images, 8 functions, 0 datasets
● Reverse Depends: 0

RJafroc : Analysis of Data Acquired Using the Receiver Operating Characteristic Paradigm and Its Extensions

Package: RJafroc
Type: Package
Title: Analysis of Data Acquired Using the Receiver Operating
Characteristic Paradigm and Its Extensions
Version: 0.1.1
Date: 2015-08-14
Authors@R: c(person("Xuetong", "Zhai", role = c("aut", "cre"), email = "xuetong.zhai@gmail.com"),
person("Dev", "Chakraborty", role = c("aut", "ths"), email = "dpc10ster@gmail.com"))
Maintainer: Xuetong Zhai <xuetong.zhai@gmail.com>
Depends: tools, xlsx, ggplot2, stringr, utils, stats, shiny
Suggests: knitr
VignetteBuilder: knitr
Description: A common task in medical imaging is assessing whether a new imaging system or device is an improvement over an existing one. Observer performance methodology, such as receiver operating characteristic analysis, is widely used for this purpose. Receiver operating characteristic studies are often required for regulatory approval of new devices. The purpose of this work is to software for the analysis of data acquired using the receiver operating characteristic paradigm and its location specific extensions. It is an enhanced implementation of existing Windows software (http://www.devchakraborty.com). In this paradigm the radiologist rates each image for confidence in presence of disease. The images are typically split equally between actually non-diseased and diseased. A common figure of merit is the area under the receiver operating characteristic curve, which has the physical interpretation as the probability that a diseased image is rated higher than a non-diseased one. In receiver operating characteristic studies a number of radiologists (readers) rate images in two or more treatments, and the object of the analysis is to determine the significance of the inter-treatment difference between reader-averaged figures of merit. In the free-response paradigm the reader marks the locations of suspicious regions and rates each region for confidence in presence of disease, and credit for detection is only given if a true lesion is correctly localized. In the region of interest paradigm each image is divided into a number of regions and the reader rates each region. Each paradigm requires definition of a valid figure of merit that rewards correct decisions and penalizes incorrect ones and specialized significance testing procedures are applied. The package reads data in all currently used data formats including Excel. Significance testing uses two models in widespread use, a jackknife pseudo-value based model and an analysis of variance model with correlated errors. Included are tools for (1) calculating a variety of free-response figures of merit; (2) sample size estimation for planning a future study based on pilot data; (3) viewing empirical operating characteristics in receiver operating characteristic and free-response paradigms; (4) producing formatted report files; and (5) saving a data file in appropriate format for analysis with alternate software. In addition to open-source access to the functions, the package includes a graphical interface for users already familiar with the Windows software, who simply wish to run the program.
License: GPL-3
LazyData: true
URL: http://www.devchakraborty.com
NeedsCompilation: no
Packaged: 2015-08-14 15:39:50 UTC; XuetongZhai
Author: Xuetong Zhai [aut, cre],
Dev Chakraborty [aut, ths]
Repository: CRAN
Date/Publication: 2015-08-14 20:13:33

● Data Source: CranContrib
4 images, 16 functions, 0 datasets
● Reverse Depends: 0

caRpools : CRISPR AnalyzeR for Pooled CRISPR Screens

Package: caRpools
Type: Package
Title: CRISPR AnalyzeR for Pooled CRISPR Screens
Version: 0.83
Date: 2015-12-06
Author: Jan Winter, Florian Heigwer
Maintainer: Jan Winter <jan.winter@dkfz-heidelberg.de>
Description: CRISPR-Analyzer for pooled CRISPR screens (caRpools) provides an end-to-end analysis of CRISPR screens including quality control, hit candidate analysis, visualization and automated report generation using R markdown. Needs MAGeCK (http://sourceforge.net/p/mageck/wiki/Home/), bowtie2 for all functions. CRISPR (clustered regularly interspaced short palindromic repeats) is a method to perform genome editing. See <https://en.wikipedia.org/wiki/CRISPR> for more information on
CRISPR.
Depends: R (>= 3.1.0)
Imports:
rmarkdown,VennDiagram,DESeq2,sm,biomaRt,seqinr,scatterplot3d,xlsx
Suggests: BiocGenerics, knitr, stringi
SystemRequirements: MAGeCK (=0.51, from
http://sourceforge.net/p/mageck/wiki/Home/), bowtie2
(http://bowtie-bio.sourceforge.net/bowtie2/index.shtml)
License: GPL
URL: http://www.crispr-analyzer.de
https://github.com/boutroslab/caRpools
BugReports: https://github.com/boutroslab/caRpools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2015-12-05 18:38:31 UTC; janwinter
Repository: CRAN
Date/Publication: 2015-12-06 13:31:59

● Data Source: CranContrib
● 0 images, 28 functions, 14 datasets
● Reverse Depends: 0