Modified items

All recently modified items, latest first.

R-Rsamtools-1.28.0-3.lbn25.x86_64: This package provides an interface to the 'samtools', 'bcftools', and 'tabix' utilities (see 'LICENCE') for manipulating SAM (Sequence Alignment / Map), binary variant call (BCF) and compressed indexed tab-delimited (tabix) files.

R-Rmpfr-0.7.0-1.lbn25.x86_64: Arithmetic (via S4 classes and methods) for arbitrary precision floating point numbers, including transcendental ("special") functions. To this end, the package interfaces to the 'LGPL' licensed 'MPFR' (Multiple Precision Floating-Point Reliable) Library which itself is based on the 'GMP' (GNU Multiple Precision) Library.

R-RcppCCTZ-0.2.3-2.lbn25.x86_64: 'Rcpp' Access to the 'CCTZ' timezone library is provided. 'CCTZ' is a C++ library for translating between absolute and civil times using the rules of a time zone.

R-Rcpp-0.12.16-1.lbn25.x86_64: The Rcpp package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about Rcpp is provided by several vignettes included in this package, via the Rcpp Gallery site at http://gallery.rcpp.org, the paper by Eddelbuettel and Francois (2011, JSS), and the book by Eddelbuettel (2013, Springer). See citation("Rcpp") for details on the last two.

R-Rcompression-0.93.2-17.lbn25.x86_64: This package is a basic R interface to the zlib and bzip2 facilities for compressing and uncompressing data that are in memory rather than in files.

R-RSQLite-1.1.2-4.lbn25.x86_64: A SQLite database interface definition for communication between R and SQLite databases.

R-RInside-0.2.14-6.lbn25.x86_64: The RInside packages makes it easier to have "R inside" your C++ application by providing a C++ wrapper class providing the R interpreter.

R-RCurl-1.95.4.10-1.lbn25.x86_64: The package allows one to compose general HTTP requests and provides convenient functions to fetch URIs, get & post forms, etc. and process the results returned by the Web server. This provides a great deal of control over the HTTP/FTP/... connection and the form of the request while providing a higher-level interface than is available just using R socket connections. Additionally, the underlying implementation is robust and extensive, supporting FTP/FTPS/TFTP (uploads and downloads), SSL/HTTPS, telnet, dict, ldap, and also supports cookies, redirects, authentication, etc.

R-R.utils-2.6.0-1.lbn25.noarch: Utility functions useful when programming and developing R packages.

R-R.rsp-0.42.0-1.lbn25.noarch: The RSP markup language makes any text-based document come alive. RSP provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. 'Today's date is <%=Sys.Date()%>'. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. Functions rstring() and rcat() make it easy to process RSP strings, rsource() sources an RSP file as it was an R script, while rfile() compiles it (even online) into its final output format, e.g. rfile('report.tex.rsp') generates 'report.pdf' and rfile('report.md.rsp') generates 'report.html'. RSP is ideal for self-contained scientific reports and R package vignettes. It's easy to use - if you know how to write an R script, you'll be up and running within minutes.

R-R.oo-1.22.0-1.lbn25.noarch: Methods and classes for object-oriented programming in R with or without references. Large effort has been made on making definition of methods as simple as possible with a minimum of maintenance for package developers. The package has been developed since 2001 and is now considered very stable. This is a cross-platform package implemented in pure R that defines standard S3 classes without any tricks.

R-R.methodsS3-1.7.1-2.lbn25.noarch: Methods that simplify the setup of S3 generic functions and S3 methods. Major effort has been made in making definition of methods as simple as possible with a minimum of maintenance for package developers. For example, generic functions are created automatically, if missing, and naming conflict are automatically solved, if possible. The method setMethodS3() is a good start for those who in the future may want to migrate to S4. This is a cross-platform package implemented in pure R that generates standard S3 methods.

R-R.devices-2.15.1-2.lbn25.noarch: Functions for creating plots and image files in a unified way regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default device options as well as scales and aspect ratios are controlled in a uniform way across all device types. Switching output format requires minimal changes in code. This package is ideal for large-scale batch processing, because it will never leave open graphics devices or incomplete image files behind, even on errors or user interrupts.

R-R.cache-0.13.0-1.lbn25.noarch: Memoization can be used to speed up repetitive and computational expensive function calls. The first time a function that implements memoization is called the results are stored in a cache memory. The next time the function is called with the same set of parameters, the results are momentarily retrieved from the cache avoiding repeating the calculations. With this package, any R object can be cached in a key-value storage where the key can be an arbitrary set of R objects. The cache memory is persistent (on the file system).

R-IRanges-2.12.0-1.lbn25.x86_64: The IRanges class and its extensions are low-level containers for storing sets of integer ranges. A typical use of these containers in biology is for representing a set of chromosome regions. More specific extensions of the IRanges class will typically allow the storage of additional information attached to each chromosome region as well as a hierarchical relationship between these regions.

R-GenomicRanges-1.30.3-1.lbn25.x86_64: The ability to efficiently store genomic annotations and alignments is playing a central role when it comes to analyze high-throughput sequencing data (a.k.a. NGS data). The package defines general purpose containers for storing genomic intervals as well as more specialized containers for storing alignments against a reference genome.


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