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https://github.com/CRG-Barcelona/bwtool/wiki
A command-line utility for bigWig files designed to read bigWig files rapidly and efficiently, providing functionality for extracting data and summarizing it in several ways, globally or at specific regions. Its functionality is subdivided into subprograms that roughly fall into three categories: data extraction, analysis, and data modification, although e.g. in the case of the matrix program or the sax program, the boundary between data extraction and analysis isn't very strong. The data modification programs all have the behavior that a bigWig is inputted and a new bigWig is outputted.
Proper citation: bwtool (RRID:SCR_003035) Copy
http://cran.r-project.org/web/packages/enviPat/
Software for fast and very memory-efficient calculation of isotope patterns, subsequent convolution to theoretical envelopes (profiles) plus valley detection and centroidization or intensoid calculation. Batch processing, resolution interpolation, wrapper, adduct calculations and molecular formula parsing.
Proper citation: enviPat (RRID:SCR_003034) Copy
https://code.google.com/p/mosdi/
Sequence analysis toolkit that contains a lot of sequence analysis algorithms, including methods for 1) motif statistics, e.g. compute the exact occurrence count distribution of a motif, 2) exact motif discovery: extraction of motifs with provably optimal p-value, 3) analysis of pattern matching algorithms: compute (for given algorithm and pattern) the exact distribution of the number of character accesses caused by searching a random text, 4) statistics of fragment masses resulting from proteolytic cleavage of proteins, 5) computing the expectated read length of sequencing reads for a given dispensation order (for 454 or IonTorrent) and 6) analysing sensitivity of spaced alignment seeds.
Proper citation: MoSDi (RRID:SCR_003037) Copy
Open source database of curated, non-redundant set of profiles derived from published collections of experimentally defined transcription factor binding sites for multicellular eukaryotes. Consists of open data access, non-redundancy and quality. JASPAR CORE is smaller set that is non-redundant and curated. Collection of transcription factor DNA-binding preferences, modeled as matrices. These can be converted into Position Weight Matrices (PWMs or PSSMs), used for scanning genomic sequences. Web interface for browsing, searching and subset selection, online sequence analysis utility and suite of programming tools for genome-wide and comparative genomic analysis of regulatory regions. New functions include clustering of matrix models by similarity, generation of random matrices by sampling from selected sets of existing models and a language-independent Web Service applications programming interface for matrix retrieval.
Proper citation: JASPAR (RRID:SCR_003030) Copy
https://github.com/PacificBiosciences/DevNet/wiki/SMRT-View
An open source Genome Browser that visualizes data generated by PacBio Sequencing Systems. * Users can explore and interact with all types of analysis results, including resequencing, De novo, cDNA, and barcoding. * Users can also visualize base modifications, base identification and motifs analysis results.
Proper citation: SMRT View (RRID:SCR_003029) Copy
https://github.com/PacificBiosciences/pbh5tools
Software tools for manipulating HDF5 files produced by Pacific Biosciences. Specifically, this package provides functionality for manipulating and extracting data from cmp.h5 and bas.h5 files.
Proper citation: pbh5tools (RRID:SCR_003027) Copy
http://www.tongji.edu.cn/~zhanglab/DiNuP/
Software that compares the nucleosome profiles generated by high-throughput sequencing between different conditions. It provides a statistical p-value for each identified RDNP based on the difference of read distributions. DiNuP also empirically estimates the FDR as a cutoff when two samples have different sequencing depths and differentiate reliable RDNPs from the background noise.
Proper citation: DiNuP (RRID:SCR_003046) Copy
https://code.google.com/p/prorata/
A quantitative proteomics software program for accurate protein abundance ratio estimation with confidence interval evaluation.
Proper citation: ProRata (RRID:SCR_002988) Copy
BioPerl is a community effort to produce Perl code which is useful in biology. This toolkit of perl modules is useful in building bioinformatics solutions in Perl. It is built in an object-oriented manner so that many modules depend on each other to achieve a task. The collection of modules in the bioperl-live repository consist of the core of the functionality of bioperl. Additionally auxiliary modules for creating graphical interfaces (bioperl-gui), persistent storage in RDMBS (bioperl-db), running and parsing the results from hundreds of bioinformatics applications (Run package), software to automate bioinformatic analyses (bioperl-pipeline) are all available as Git modules in our repository. The BioPerl toolkit provides a library of hundreds of routines for processing sequence, annotation, alignment, and sequence analysis reports. It often serves as a bridge between different computational biology applications assisting the user to construct analysis pipelines. This chapter illustrates how BioPerl facilitates tasks such as writing scripts summarizing information from BLAST reports or extracting key annotation details from a GenBank sequence record. BioPerl includes modules written by Sohel Merchant of the GO Consortium for parsing and manipulating OBO ontologies. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: BioPerl (RRID:SCR_002989) Copy
http://www.broadinstitute.org/gsea/
Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.
Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy
http://r3cseq.genereg.net/Site/index.html
An R/Bioconductor package to identify chromosomal interaction regions generated by chromosome conformation capture (3C) coupled to next-generation sequencing (NGS), a technique termed 3C-seq. It performs data analysis for a number of different experimental designs, as it can analyze 3C-seq data with or without a control experiment and it can be used to facilitate data analysis for experiments with multiple replicates. The r3Cseq package provides functions to perform data normalization, statistical analysis for cis/trans interactions and visualization in order to help scientists identify genomic regions that physically interact with the given viewpoints of interest. This tool greatly facilitates hypothesis generation and the interpretation of experimental results.
Proper citation: r3Cseq (RRID:SCR_003198) Copy
http://creskolab.uoregon.edu/stacks/
A software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. It was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.
Proper citation: Stacks (RRID:SCR_003184) Copy
http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/
Software tool for finding the minimum free energy hybridization of a long and a short RNA. The hybridization is performed in a kind of domain mode, i.e., the short sequence is hybridized to the best fitting part of the long one. The tool is primarily meant as a means for microRNA target prediction.
Proper citation: RNAhybrid (RRID:SCR_003252) Copy
http://cal.tongji.edu.cn/PlantLoc/index.jsp
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 4,2023. An accurate web server for predicting plant protein subcellular localization by substantiality motif.
Proper citation: PlantLoc (RRID:SCR_003138) Copy
https://github.com/mozack/abra
Software that is a realigner for next generation sequencing data. It uses localized assembly and global realignment to align reads more accurately, thus improving downstream analysis (detection of indels and complex variants in particular).
Proper citation: Assembly Based ReAligner (RRID:SCR_003277) Copy
http://iimcb.genesilico.pl/MetaLocGramN/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023.A tool for subcellular localization prediction of Gram-negative proteins. You can also use MetaGramLocN via SOAP. SOAP enables you to invoke our method from scripts written in your programming language of choice.
Proper citation: MetaLocGramN (RRID:SCR_003154) Copy
http://genecruiser.broadinstitute.org/genecruiser3/
A web service and web application for the annotation of microarray data providing integrated access to genomic information freely available from public data sources.
Proper citation: GeneCruiser (RRID:SCR_003153) Copy
Initiative to define community standards for data representation in proteomics to facilitate data comparison, exchange and verification. The main organizational unit is the work group, with a Gel Electrophoresis (GEL) work group, a Mass Spectrometry (MS) work group, a Molecular Interactions (MI) work group, a Protein Modifications (MOD) work group, a Proteomics Informatics (PI) work group, and a Sample Processing (SP) work group. The Gel Electrophoresis (GEL) work group aims to develop reporting requirements that supplement the Minimum Information About a Proteomics Experiment (MIAPE) parent document, describing the minimum information that should be reported about gel-based experimental techniques used in proteomics. The group will also develop data formats for capturing MIAPE-compliant data about gel electrophoresis and informatics performed on gel images. The Mass Spectrometry Standards Working Group defines community data formats and controlled vocabulary terms facilitating data exchange and archiving in the field of proteomics mass spectrometry. A past achievement is the mzData standard, which captures mass spectrometry output data. mzData's aim is to unite the large number of current formats (pkl's, dta's, mgf's, .....) into a single format. mzData has been released but is now deprecated in favor of mzML. The Molecular Interactions workgroup is concentrating on improving the annotation and representation of molecular interaction data wherever it is published, be this in journal articles, authors web-sites or public domain databases; and improving the accessibility of molecular interaction data to the user community. By using a common standard data can be downloaded from multiple sources and easily combined using a single parser. The protein modification workgroup focuses on developing a consensus nomenclature and provide an ontology reconciling in a hierarchical representation the complementary descriptions of residue modifications. The protein modification ontology (PSI-MOD) is available in OBO format or in OBO.xml. A spreadsheet containing the mapping of the descriptive labels used in various databases and search engines, the consensus list of proposed short name for protein modifications established by collaborative effort of mass spectrometry community, and the proposed rules and recommendations for this nomenclature are available. These short names are included in the ontology as synonyms of the corresponding terms. The Proteomics Informatics Standards Group (PSI-PI) goals are to provide a set of minimal reporting requirements which augment the MIAPE reporting guidelines with respect to analysis of data derived from proteomics experiments; to provide vendor-neutral and standard formats for representing results of analyzing and processing experimental data; to foster adoption of the format by highlighting efforts made by vendors and individuals that utilize the format in their products. The remit of the Sample Processing Working Group is to produce reporting guidelines, data exchange formats and controlled vocabulary covering all separation techniques not considered to be "classical" one- or two-dimensional gel electrophoresis (cf. the Gel WG home page), along with other kinds of sample handling and processing (for example, "tagging" proteins or peptides, splitting, combining and storing samples). Where possible we seek to develop our products in collaboration with all proteomics stakeholders and, where relevant, developers from other standards communities, most notably metabolomics. * Minimum reporting requirements: The evolving Minimum Information About a Proteomics Experiment (MIAPE) documents offer guidelines on how to adequately report a proteomics experiment. It is expected that these documents will be published, and that the requirements within will be enforced by journals, compliant repositories and funders (cf. MIAME). * XML formats for data exchange: Derived from the FuGE general object model, the formats developed by this workgroup are designed to function both as standalone files and as part of a "parent" FuGE-ML document. These formats will facilitate data exchange between researchers, and submission to repositories or journals. * Controlled vocabularies (CVs) and ontology: Lists of clearly defined terms are crucial for the construction of unambiguously worded data files. In addition to providing supporting CVs for the individual data capture formats as part of the integrated PSI CV, the Sample Processing WG will contribute terms to the Functional Genomics Ontology (FuGO).
Proper citation: HUPO Proteomics Standards Initiative (RRID:SCR_003158) Copy
https://code.google.com/p/peakrots/
Bioinformatics analysis software tool for optimized ChIP-seq peak detection written in R.
Proper citation: peakrots (RRID:SCR_007453) Copy
https://github.com/steinmann/peakzilla
An algorithm to identify transcription factor binding sites from ChIP-seq data.
Proper citation: Peakzilla (RRID:SCR_007471) Copy
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