Modified items

All recently modified items, latest first.

R-biomaRt-2.18.0-4.lbn19.noarch: In recent years a wealth of biological data has become available in public data repositories. Easy access to these valuable data resources and firm integration with data analysis is needed for comprehensive bioinformatics data analysis. biomaRt provides an interface to a growing collection of databases implementing the BioMart software suite (http://www.biomart.org). The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.

R-biglm-0.9.1-5.lbn19.x86_64: Regression for data too large to fit in memory.

R-affyio-1.32.0-4.lbn19.x86_64: Routines for parsing Affymetrix data files based upon file format information. Primary focus is on accessing the CEL and CDF file formats.

R-affydata-1.16.0-2.lbn19.noarch: Example data sets of a slightly large size. They represent 'real world examples', unlike the artificial examples included in the package affy.

R-affy-1.40.0-5.lbn19.x86_64: The package contains functions for exploratory oligonucleotide array analysis. The dependancy to tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.

R-acepack-1.3.3.3-5.lbn19.x86_64: ACE and AVAS (additivity and variance stabilization) are used to estimate transformations for regression.

R-abind-1.4.0-10.lbn19.noarch: Combine multi-dimensional arrays. This is a generalization of cbind and rbind. Takes a sequence of vectors, matrices, or arrays and produces a single array of the same or higher dimension.

R-XVector-0.12.1-1.lbn19.x86_64: Memory efficient S4 classes for storing sequences "externally" (behind an R external pointer, or on disk).

R-XML-3.98.1.1-6.lbn19.x86_64: This package provides many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. It also offers access to an XPath "interpreter".

R-SummarizedExperiment-1.2.3-1.lbn19.noarch: The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.

R-S4Vectors-0.10.3-1.lbn19.x86_64: The S4Vectors package defines the Vector and List virtual classes and a set of generic functions that extend the semantic of ordinary vectors and lists in R. Package developers can easily implement vector-like or list-like objects as concrete subclasses of Vector or List. In addition, a few low-level concrete subclasses of general interest (e.g. DataFrame, Rle, and Hits) are implemented in the S4Vectors package itself (many more are implemented in the IRanges package and in other Bioconductor infrastructure packages).

R-Rsolid-0.9.31-18.lbn19.x86_64: Rsolid is an R package for normalizing fluorescent intensity data from ABI/SOLiD second generation sequencing platform. It has been observed that the color-calls provided by factory software contain technical artifacts, where the proportions of colors called are extremely variable across sequencing cycles. Under the random DNA fragmentation assumption, these proportions should be equal across sequencing cycles and proportional to the dinucleotide frequencies of the sample. Rsolid implements a version of the quantile normalization algorithm that transforms the intensity values before calling colors. Results show that after normalization, the total number of mappable reads increases by around 5%, and number of perfectly mapped reads increases by 10%. Moreover a 2-5% reduction in overall error rates is observed, with a 2-6% reduction in the rate of valid adjacent color mis-matches. The latter is important, since it leads to a decrease in false-positive SNP calls. The normalization algorithm is computationally efficient. In a test we are able to process 300 million reads in 2 hours using 10 computer cluster nodes. The engine functions of the package are written in C for better performance.

R-Rsamtools-1.24.0-1.lbn19.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-Rcpp-0.12.6-1.lbn19.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-0.93.2-13.lbn19.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-RUnit-0.4.26-11.lbn19.noarch: R functions implementing a standard Unit Testing framework, with additional code inspection and report generation tools

R-RSQLite-0.11.4-5.lbn19.x86_64: A SQLite database interface definition for communication between R and SQLite databases.


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