Debian Med Biology development packages

The Bioperl project is a coordinated effort to collect computational methods routinely used in bioinformatics into a set of standard CPAN-style, well-documented, and freely available Perl modules. It is well-accepted throughout the community and used in many high-profile projects, e.g., Ensembl.

When publishing work prepared with this package, you should cite: J.E. Stajich, D. Block, K. Boulez, S.E. Brenner, S.A. Chervitz, C. Dagdigian, G. Fuellen, J.G. Gilbert, I. Korf, H. Lapp, H. Lehvaslaiho, C. Matsalla, C.J. Mungall, B.I. Osborne, M.R. Pocock, P. Schattner, M. Senger, L.D. Stein, E. Stupka, M.D. Wilkinson, E. Birney (2002) "The Bioperl toolkit: Perl modules for the life sciences." Genome Res. 12(10):1611-1618.

Contains modules that provide a Perl interface to various bioinformatics applications to allow them to be used with common BioPerl objects.

Not all the wrappable applications are packaged in Debian. The ones that are are "Suggested" by this package.

SQUID is a library of C code functions for sequence analysis. It also includes a number of small utility programs to convert, show statistics, manipulate and do other functions on sequence files.

The original name of the package is "squid", but since there is already a squid on the archive (a proxy cache), it was renamed to "biosquid".

AcePerl is an object-oriented Perl interface for the AceDB database. It provides functionality for connecting to remote AceDB databases, performing queries, fetching ACE objects, and updating databases. The programmer's API is compatible with the JADE Java API, and interoperable with the API used by BoulderIO.

AceDB is a genome database system developed since 1989 primarily by Jean Thierry-Mieg (CNRS, Montpellier) and Richard Durbin (Sanger Institute). It was originally developed for the C.elegans genome project , from which its name was derived (A C. elegans DataBase).

This package contains the header and development files needed to build programs and packages using libajax.

The Bio::Graphics::Panel class provides drawing and formatting services for any object that implements the Bio::SeqFeatureI interface, including Ace::Sequence::Feature, Das::Segment::Feature and Bio::DB::Graphics objects. It can be used to draw sequence annotations, physical (contig) maps, protein domains, or any other type of map in which a set of discrete ranges need to be laid out on the number line.

MAGE-TAB (MicroArray Gene Expression Tabular) format is a standard from the Microarray Gene Expression Data Society (MGED). This package contains Perl modules in the Bio::MAGE hierarchy to manipulate MIAME-compliant (Minimum Information About a Microarray Experiment) records of microarray ("DNA chips") experiments.

 The Bio::MAGE module contains the following Bio::MAGE classes:
   * NameValueType
   * Extendable
   * Identifiable
   * Describable

Bio::PrimerDesigner provides a low-level interface to the primer3 and epcr binary executables and supplies methods to return the results. In addition to accessing local installations of primer3 or e-PCR, it also offers the ability to accessing the primer3 binary via a remote server.

BioRuby project aims to implement an integrated environment for Bioinformatics with Ruby language. Design philosophy of the BioRuby library is KISS (keep it simple and stupid) to maximize the usability and the efficiency for biologists as a daily tool. The project was started in Japan and supported by University of Tokyo (Human Genome Center), Kyoto University (Bioinformatics Center) and the Open Bio Foundation.

This project is a dependency package, which depends on Debian's default Ruby version (currently 1.8.x)

BioJava is an open-source project dedicated to providing a Java framework for processing biological data. It includes objects for manipulating sequences, file parsers, DAS client and server support, access to BioSQL and Ensembl databases, and powerful analysis and statistical routines including a dynamic programming toolkit.

BioJava is provided by a vibrant community which meets annually at the Bioinformatics Open Source Conference (BOSC) that traditionally accompanies the Intelligent Systems in Molecular Biology (ISMB) meeting. Much like BioPerl, the employment of this library is valuable for everybody active in the field because of the many tricks of the trade one learns just by communicating on the mailing list.

If using BioJava, please cite: R.C.G. Holland, T. Down, M. Pocock, A. Prlić, D. Huen, K. James, S. Foisy, A. Dräger, A. Yates, M. Heuer; M.J. Schreiber (2008) "BioJava: an Open-Source Framework for Bioinformatics" Bioinformatics 24(18):2096-2097.

This is a wrapper package which should enable smooth upgrades to new versions.

libGenome is a freely available toolkit for developing bioinformatic related software in C++. It is intended to take the hassle out of performing common tasks on genetic sequence and annotation data.

Among other things, libGenome can help you:

• Read and write Multi-FastA format files
• Read and write GenBank flat file database entries
• Append, chop, truncate, reverse, complement, translate, and otherwise mangle sequence data
• Access annotation in GenBank flat files

This is the development package containing the statically linked library and the header files.

This is a collection of perl code for dealing with Gene Ontologies (GO) and Open Biomedical Ontologies (OBO) style ontologies. It is part of the ‘go-dev’ distribution, but this Debian package is made from the CPAN archive. This package contains both scripts (which can be used with no knowledge of perl), and libraries which will be of use to perl programmers using GO or OBO.

This package is for developers or people who want to compile programs only. In addition to development headers and libraries, it contains the utilities asntool and errhdr.

This package contains the header and development files needed to build programs and packages using libnucleus.

qsearch is a library for universal hierarchical clustering using an arbitrary distance matrix as input. It searches through the space of all possible unrooted trees of a given size and finds the closest match based on a weighted quartet cost function determined by the distance matrix. When used in combination with other feature extraction libraries such as libcomplearn this system can be used for fast and accurate phylogenetic reconstruction, linguistic analysis, or stemmatology.

SRF (sort for Sequence Read Format) is a generic format capable of storing data generated by any DNA sequencing technology. This library is an implementation of SRF and provides basic input-output functions.

This package contains the header and development files needed to build programs and packages using the Staden io_lib.

The io_lib from the Staden package is a library of file reading and writing code to provide a general purpose trace file (and Experiment File) reading interface. It has been compiled and tested on a variety of unix systems, MacOS X and MS Windows.

The TFBS perl modules comprise a set of routines to interact with the Transfac and Jaspar databases that describe a special family of proteins, the transcription factors. These bind to genomic DNA to initiate (or prevent) the readout of a gene. Once multiple binding sites are known for a transcription factor, these are gathered in a single file and are aligned in order to find position-specific characteristica that might be used to predict such binding events in novel DNA sequences.

If you use TFBS in your work, please cite "Lenhard B., Wasserman W.W. (2002) TFBS: Computational framework for transcription factor binding site analysis. Bioinformatics 18:1135-1136".

Vibrant allows you to develop portable (Motif, MS-Windows, Mac-OS) graphic biological applications.

The MCL package is an implementation of the MCL algorithm, and offers utilities for manipulating sparse matrices (the essential data structure in the MCL algorithm) and conducting cluster experiments.

MCL is currently being used in sciences like biology (protein family detection, genomics), computer science (node clustering in Peer-to-Peer networks), and linguistics (text analysis).

This package provides functions to do work in bioinformatics in Octave, a numerical computation software. It contains functions to convert amino acid characters into integers (aa2int), convert between amino acid representations (aminolookup), cleave peptides (cleave), convert integers into amino acid characters (int2aa) and reverse a nucleotide sequence (seqreverse).

This Octave add-on package is part of the Octave-Forge project.

The Biopython Project is an international association of developers of freely available Python tools for computational molecular biology.

It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. The source code is made available under the Biopython License, which is extremely liberal and compatible with almost every license in the world. We work along with the Open Bioinformatics Foundation, who generously provide web and CVS space for the project.

Classes and methods for handling genetic data. Includes The package provides a library for the statistics environment R that contains classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, and more.

NOTE: THIS PACKAGE IS NOW OBSOLETE.

The R-Genetics project has developed an set of enhanced genetics packages to replace 'genetics'. Please visit the project homepage at http://rgenetics.org for information.

The package provides routines for the GNU R statistics environment for statistical Analysis of indirectly measured Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em, haplo.glm, haplo.score, haplo.power, and seqhap.

SeqAn is a C++ template library of efficient algorithms and data structures for the analysis of sequences with the focus on biological data. This library applies a unique generic design that guarantees high performance, generality, extensibility, and integration with other libraries. SeqAn is easy to use and simplifies the development of new software tools with a minimal loss of performance. This package contains the developer files, documentation and examples.

ROC graphs, sensitivity/specificity curves, lift charts, and precision/recall plots are popular examples of trade-off visualizations for specific pairs of performance measures. ROCR is a flexible tool for creating cutoff-parametrized 2D performance curves by freely combining two from over 25 performance measures (new performance measures can be added using a standard interface). Curves from different cross-validation or bootstrapping runs can be averaged by different methods, and standard deviations, standard errors or box plots can be used to visualize the variability across the runs. The parametrization can be visualized by printing cutoff values at the corresponding curve positions, or by coloring the curve according to cutoff. All components of a performance plot can be quickly adjusted using a flexible parameter dispatching mechanism. Despite its flexibility, ROCR is easy to use, with only three commands and reasonable default values for all optional parameters.

ROCR features: ROC curves, precision/recall plots, lift charts, cost curves, custom curves by freely selecting one performance measure for the x axis and one for the y axis, handling of data from cross-validation or bootstrapping, curve averaging (vertically, horizontally, or by threshold), standard error bars, box plots, curves that are color-coded by cutoff, printing threshold values on the curve, tight integration with Rs plotting facilities (making it easy to adjust plots or to combine multiple plots), fully customizable, easy to use (only 3 commands).

Performance measures that ROCR knows: Accuracy, error rate, true positive rate, false positive rate, true negative rate, false negative rate, sensitivity, specificity, recall, positive predictive value, negative predictive value, precision, fallout, miss, phi correlation coefficient, Matthews correlation coefficient, mutual information, chi square statistic, odds ratio, lift value, precision/recall F measure, ROC convex hull, area under the ROC curve, precision/recall break-even point, calibration error, mean cross-entropy, root mean squared error, SAR measure, expected cost, explicit cost.

Bio::Das provides access to genome sequencing and annotation databases that export their data in Distributed Annotation System (DAS) format version 1.5. Both unencrypted (http:) and SSL-encrypted (https:) DAS servers are supported.

LibSBML is a library designed to help you read, write, manipulate, translate, and validate SBML files and data streams. It is not an application itself (though it does come with many example programs), but rather a library you can embed in your own applications.

LibSBML is written in ISO C and C++ but as a library it may be used from all the programming languages listed to the left. In fact, we strive to adhere to the natural idioms of each particular language to make the libSBML programming experience seamless. For example, SBML elements behave like lists and sequences in Python, but vectors in Matlab. Also, the C and C++ interfaces are completely distinct (it's possible to program in pure C), but in C++ the C APIs may be called without sacrifcing type safety.

The LibSBML code is very portable and is supported on Linux, Windows (native), and Mac OS X.

Bioconductor is an open source and open development software project to provide tools for the analysis and comprehension of genomic data.

The Bioconductor core team is based primarily at the Biostatistics Unit of the Dana Farber Cancer Institute at the Harvard Medical School/Harvard School of Public Health. Other members come from various US and international institutions.

The broad goals of the projects are to

• provide access to a wide range of powerful statistical and graphical methods for the analysis of genomic data;
• facilitate the integration of biological metadata in the analysis of experimental data: e.g. literature data from PubMed, annotation data from LocusLink;
• allow the rapid development of extensible, scalable, and interoperable software;
• promote high-quality documentation and reproducible research;
• provide training in computational and statistical methods for the analysis of genomic data.

A nice overview about all modules of BioDonductor is given at http://www.bioconductor.org/packages/release/bioc/

MAGE-TAB (MicroArray Gene Expression Tabular) format is a standard from the Microarray Gene Expression Data Society (MGED). This package contains Perl modules in the Bio::MAGE hierarchy to manipulate MIAME-compliant (Minimum Information About a Microarray Experiment) records of microarray ("DNA chips") experiments.

Bio-MAGE-Utils contains extra modules for handling MAGE XML and MGED ontology, as well as SQL utilities.

libMems is a freely available software development library to support DNA string matching and comparative genomics. Among other things, libMems implements an algorithm to perform approximate multi-MUM and multi-MEM identification. The algorithm uses spaced seed patterns in conjunction with a seed-and-extend style hashing method to identify matches. The method is efficient, requiring a maximum of only 16 bytes per base of the largest input sequence, and this data can be stored externally (i.e. on disk) to further reduce memory requirements.

GFF (Gene Finding Feature) is a format for describing genes and other features associated with DNA, RNA and Protein sequences.

This package provides a Perl module to use GFF objects.

Limma is an essential package of the bioconductor.org effort to investigate gene expression data from microarrays with the statistical package R.

The Bioclipse project is aimed at creating a Java-based, open source, visual platform for chemo- and bioinformatics based on the Eclipse Rich Client Platform (RCP). Bioclipse, as any RCP application, is based on a plugin architecture that inherits basic functionality and visual interfaces from Eclipse, such as help system, software updates, preferences, cross-platform deployment etc.

Bioclipse will provide functionality for chemo- and bioinformatics, and extension points that easily can be extended by plugins to provide added functionality. The first version of Bioclipse includes a CDK-plugin (bc_cdk) to provide a chemoinformatic backend, a Jmol-plugin (bc_jmol) for 3D-visualization and a general logging plugin. To stay updated on upcoming features, releases, new plugins etc, please register for the mailing list bioclipse-announce. The development is best followed on the Bioclipse Wiki where we document the progress and ideas of the development on a daily basis.